Tersoff-style three-body potential for SiC developed by Tersoff (1994) v000

Jerry Tersoff

doi:10.25950/2ecced5d

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Tersoff_LAMMPS_Tersoff_1994_SiC__MO_794973922560_000

Interatomic potential for Carbon (C), Silicon (Si).
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Title A single sentence description.	Tersoff-style three-body potential for SiC developed by Tersoff (1994) v000
Description A short description of the Model describing its key features including for example: type of model (pair potential, 3-body potential, EAM, etc.), modeled species (Ac, Ag, ..., Zr), intended purpose, origin, and so on.	This is a three-body Tersoff potential for SiC. This parameterization uses the interactions from the author's 1990 Si-C potential and the cutoff of author's 1989 Si-C potential, with a slight correction for heat of mixing
Species The supported atomic species.	C, Si
Disclaimer A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.	None
Content Origin	https://www.ctcms.nist.gov/potentials/entry/1994--Tersoff-J--Si-C/

Contributor	I Nikiforov
Maintainer	I Nikiforov
Developer	Jerry Tersoff
Published on KIM	2022
How to Cite	This Model originally published in [1] is archived in OpenKIM [2-5]. [1] Tersoff J. Chemical order in amorphous silicon carbide. Phys Rev B [Internet]. 1994Jun;49(23):16349–52. Available from: https://link.aps.org/doi/10.1103/PhysRevB.49.16349 doi:10.1103/PhysRevB.49.16349 — (Primary Source) A primary source is a reference directly related to the item documenting its development, as opposed to other sources that are provided as background information. [2] Tersoff J. Tersoff-style three-body potential for SiC developed by Tersoff (1994) v000. OpenKIM; 2022. doi:10.25950/2ecced5d [3] Brink T, Thompson AP, Farrell DE, Wen M, Tersoff J, Nord J, et al. Model driver for Tersoff-style potentials ported from LAMMPS v005. OpenKIM; 2021. doi:10.25950/9a7dc96c [4] Tadmor EB, Elliott RS, Sethna JP, Miller RE, Becker CA. The potential of atomistic simulations and the Knowledgebase of Interatomic Models. JOM. 2011;63(7):17. doi:10.1007/s11837-011-0102-6 [5] Elliott RS, Tadmor EB. Knowledgebase of Interatomic Models (KIM) Application Programming Interface (API). OpenKIM; 2011. doi:10.25950/ff8f563a Click here to download the above citation in BibTeX format.
Citations This panel presents information regarding the papers that have cited the interatomic potential (IP) whose page you are on. The OpenKIM machine learning based Deep Citation framework is used to determine whether the citing article actually used the IP in computations (denoted by "USED") or only provides it as a background citation (denoted by "NOT USED"). For more details on Deep Citation and how to work with this panel, click the documentation link at the top of the panel. The word cloud to the right is generated from the abstracts of IP principle source(s) (given below in "How to Cite") and the citing articles that were determined to have used the IP in order to provide users with a quick sense of the types of physical phenomena to which this IP is applied. The bar chart shows the number of articles that cited the IP per year. Each bar is divided into green (articles that USED the IP) and blue (articles that did NOT USE the IP). Users are encouraged to correct Deep Citation errors in determination by clicking the speech icon next to a citing article and providing updated information. This will be integrated into the next Deep Citation learning cycle, which occurs on a regular basis. OpenKIM acknowledges the support of the Allen Institute for AI through the Semantic Scholar project for providing citation information and full text of articles when available, which are used to train the Deep Citation ML algorithm.	This panel provides information on past usage of this interatomic potential (IP) powered by the OpenKIM Deep Citation framework. The word cloud indicates typical applications of the potential. The bar chart shows citations per year of this IP (bars are divided into articles that used the IP (green) and those that did not (blue)). The complete list of articles that cited this IP is provided below along with the Deep Citation determination on usage. See the Deep Citation documentation for more information. 203 Citations (73 used) Show Model Used Show All Help us to determine which of the papers that cite this potential actually used it to perform calculations. If you know, click the . M. S. Islam et al., “Molecular dynamics study of thermal transport in single-layer silicon carbide nanoribbons,” AIP Advances. 2020. link Times cited: 17 Abstract: Aiming to solve the heat dissipation problem of next generat… read more Abstract: Aiming to solve the heat dissipation problem of next generation energy-efficient nanoelectronics, we have explored the thermal transport behavior of monolayer silicon carbide nanoribbons (SiCNRs) using equilibrium molecular dynamics simulation based on Green-Kubo formalism. Our comprehensive analysis includes the calculation of thermal conductivity both for armchair and zigzag edged SiCNRs as a function of temperature, ribbon width, and length. At a temperature of 300 K, the thermal conductivity of 10 nm × 3 nm SiCNRs is found to be 23.92 ± 4.01 W/m K and 26.26 ± 4.18 W/m K for the armchair and zigzag direction, respectively. With the increase in temperature and length, a decreasing behavior of the thermal conductivity is observed for both directions of the SiCNRs, while the thermal conductivity increases with the increase in the ribbon width. Besides, to explain the size-dependent thermal transport phenomena, the acoustic phonon density of states is calculated using velocity autocorrelation of atoms. The variation of different low-frequency phonon modes validates the explored thermal conductivity at varying widths and lengths. These results would provide insight into and inspiration to design next-generation nanoelectronics with enhanced thermal efficiency using novel SiCNRs.Aiming to solve the heat dissipation problem of next generation energy-efficient nanoelectronics, we have explored the thermal transport behavior of monolayer silicon carbide nanoribbons (SiCNRs) using equilibrium molecular dynamics simulation based on Green-Kubo formalism. Our comprehensive analysis includes the calculation of thermal conductivity both for armchair and zigzag edged SiCNRs as a function of temperature, ribbon width, and length. At a temperature of 300 K, the thermal conductivity of 10 nm × 3 nm SiCNRs is found to be 23.92 ± 4.01 W/m K and 26.26 ± 4.18 W/m K for the armchair and zigzag direction, respectively. With the increase in temperature and length, a decreasing behavior of the thermal conductivity is observed for both directions of the SiCNRs, while the thermal conductivity increases with the increase in the ribbon width. Besides, to explain the size-dependent thermal transport phenomena, the acoustic phonon density of states is calculated using velocity autocorrelation of atoms. The... read less A. C. Hansen-Dorr, L. Wilkens, A. Croy, A. Dianat, G. Cuniberti, and M. Kastner, “Combined molecular dynamics and phase-field modelling of crack propagation in defective graphene,” Computational Materials Science. 2019. link Times cited: 14 Y. Liu, Y. Liu, and J. Luo, “Atomic Scale Simulation on the Fracture Mechanism of Black Phosphorus Monolayer under Indentation,” Nanomaterials. 2018. link Times cited: 3 Abstract: Molecular dynamics simulations on the indentation process of… read more Abstract: Molecular dynamics simulations on the indentation process of freestanding and Pt(111)-supported black phosphorus (BP) monolayer were conducted to study the fracture mechanism of the membrane. For the freestanding BP monolayer, crack grows firstly along armchair direction and then zigzag direction during the indentation process. Whereas, for the Pt(111)-supported BP monolayer, crack growth shows no obvious directionality, with irregular distribution of crack tips. Further study on stress distribution shows that maximum normal stress component at elastic stage is in zigzag direction for the freestanding BP monolayer, and in vertical direction for the Pt(111)-supported BP monolayer. As BP monolayer is remarkably anisotropic for in-plane mechanical properties and homogeneous for out-of-plane mechanical properties, the difference of stress state may be a key reason for the different fracture behavior in these two cases. These findings may help to understand the failure mechanism of BP, when applied in nano-devices. read less Z. Wu, W. Liu, and L. Zhang, “Critical loading conditions of amorphization, phase transformation, and dilation cracking in 6H‐silicon carbide,” Journal of the American Ceramic Society. 2018. link Times cited: 15 Abstract: Amorphization, phase transformation, and dilation cracking a… read more Abstract: Amorphization, phase transformation, and dilation cracking are 3 major deformation/failure mechanisms of monocrystalline 6H-SiC. This paper studies their critical formation conditions and mechanisms under hydrostatic pressure and uniaxial compression and tension with the aid of large-scale molecular dynamics simulations. It was found that under hydrostatic pressure the major deformation mechanism is amorphization, that under uniaxial compression the major mechanism turns to phase transformation at low temperature and amorphization at high temperature, and that under uniaxial tension the dominating mechanism becomes dilation cracking. Increasing the temperature reduces the thresholds significantly and brings about a heterogeneous deformation mode. The study further concluded that these deformation mechanisms and their thresholds can be predicted theoretically. read less C. Xiao, H. He, J. Li, and W. Zhu, “Kapitza resistance for nanoscale crystalline and amorphous silicon carbide,” 2018 19th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE). 2018. link Times cited: 0 Abstract: The interface between nanoscale films plays a very important… read more Abstract: The interface between nanoscale films plays a very important role in semiconductor industry. In this paper, the interfacial thermal resistance (Kapitza resistance) of a crystalline and amorphous silicon carbide (SiC) heterojunction has been investigated by using molecular dynamics simulations. It is found that Kapitza resistance at crystalline and amorphous SiC interface depends on the interfacial coupling strength remarkably. Kapitza resistance in the strong interfacial coupling is significantly lower than that in weak coupling. The thickness of the heterojunction and temperature dependence of Kapitza resistance have also been examined. The results have shown that the Kapitza resistance decreases monotonically with the increase of temperature (from 300K to 800K). Moreover, Kapitza resistance can be effectively tuned by cross-plane strain. A 5% compressive strain is able to reduce the Kapitza resistance by 380% in weak coupling case. In contrast, a 5% tensile strain can increase Kapitza resistance by 13%. Our study provides useful guidance to the thermal management and heat dissipation across nanoscale crystalline and amorphous silicon carbide interface, in particular, for the design of silicon carbide nanowire based nano electronics devices. read less M. Li, J. Zhang, X. Hu, and Y. Yue, “Thermal transport across graphene/SiC interface: effects of atomic bond and crystallinity of substrate,” Applied Physics A. 2015. link Times cited: 56 M. Li and Y. Yue, “Molecular dynamics study of thermal transport in amorphous silicon carbide thin film,” RSC Advances. 2014. link Times cited: 15 Abstract: The emergence of amorphous silicon carbide (a-SiC) thin film… read more Abstract: The emergence of amorphous silicon carbide (a-SiC) thin film based photovoltaic applications has provoked great interest in its physical properties. In this work, we report the first comprehensive study of thermal transport in the a-SiC thin film from 10 nm to 50 nm under various conditions using empirical molecular dynamic (MD) simulations. The thermal conductivity increases from 1.38 to 1.75 W m−1K−1 as temperature increases from 100 K to 1100 K. A similar increase in the thermal conductivity from 1.4 to 2.09 W m−1K−1 is obtained with densities from 2.7 to 3.24 g cm−3. Besides, a slight increase in the thermal conductivity (15%) with calculation domain from 10 nm to 50 nm is observed, indicating that the size dependence of thermal transport also exists in nanoscale amorphous structures. For the physical interpretation of simulation results, the phonon mean free path (MFP) and specific heat are calculated, which are responsible for the temperature dependence of the thermal conductivity. The phonon group velocity is the key factor for the change in thermal conductivity with density. The results also show that the phonon MFP decreases rapidly with temperature and is subject to the Matthiessen's rule. read less N. Swaminathan, M. Wojdyr, D. Morgan, and I. Szlufarska, “Radiation interaction with tilt grain boundaries in β-SiC,” Journal of Applied Physics. 2012. link Times cited: 21 Abstract: Interaction between grain boundaries and radiation is studie… read more Abstract: Interaction between grain boundaries and radiation is studied in 3C-SiC by conducting molecular dynamics cascade simulations on bicrystal samples with different misorientation angles. The damage in the in-grain regions was found to be unaffected by the grain boundary type and is comparable to damage in single crystal SiC. Radiation-induced chemical disorder in the grain boundary regions is quantified using the homonuclear to heteronuclear bond ratio (χ). We found that χ increases nearly monotonically with the misorientation angle, which behavior has been attributed to the decreasing distance between the grain boundary dislocation cores with an increasing misorientation angle. The change in the chemical disorder due to irradiation was found to be independent of the type of the grain boundary. read less R. Atta-Fynn and P. Biswas, “Atomistic modeling of amorphous silicon carbide: an approximate first-principles study in constrained solution space,” Journal of Physics: Condensed Matter. 2009. link Times cited: 8 Abstract: Localized basis ab initio molecular dynamics simulation with… read more Abstract: Localized basis ab initio molecular dynamics simulation within the density functional framework has been used to generate realistic configurations of amorphous silicon carbide (a-SiC). Our approach consists of constructing a set of smart initial configurations that conform to essential geometrical and structural aspects of the materials obtained from experimental data, which is subsequently driven via a first-principles force field to obtain the best solution in a reduced solution space. A combination of a priori information (primarily structural and topological) along with the ab initio optimization of the total energy makes it possible to model a large system size (1000 atoms) without compromising the quantum mechanical accuracy of the force field to describe the complex bonding chemistry of Si and C. The structural, electronic and vibrational properties of the models have been studied and compared to existing theoretical models and available data from experiments. We demonstrate that the approach is capable of producing large, realistic configurations of a-SiC from first-principles simulation that display its excellent structural and electronic properties. Our study reveals the presence of predominant short range order in the material originating from heteronuclear Si–C bonds with a coordination defect concentration as small as 5% and a chemical disorder parameter of about 8%. read less F. Ribeiro, É. Castelier, M. Bertolus, and M. Defranceschi, “Molecular Dynamics as a tool to interpret macroscopic amorphization-induced swelling in silicon carbide,” The European Physical Journal B - Condensed Matter and Complex Systems. 2006. link Times cited: 5 S. Nakano, S. Muto, and T. Tanabe, “Change in mechanical properties of ion-irradiated ceramics studied by nanoindentation,” Materials Transactions. 2005. link Times cited: 16 Abstract: Changes in hardness of several representative ceramics and s… read more Abstract: Changes in hardness of several representative ceramics and semiconductors associated with ion irradiation were systematically studied, using a combined method of nanoindentation and finite element analysis. We established a new method for precisely extracting hardness of the embedded damaged layer of ion-irradiated samples. The method was applied to silicon carbide, α-quartz, silica glass and silicon. To semi-quantitatively discuss their mechanical properties changed by irradiation, we introduced a phenomenological model expressed by a set of kinetic equations, and extracted material parameters by fitting the experimental data with the theoretical model. Finally we propose a new atomistic mechanism for plastic deformations of covalent amorphous materials. The present results would give a standard framework to discuss the mechanical property changes of ceramics irradiated with energetic particle. read less V. Ivashchenko et al., “Gap states in a-SiC from optical measurements and band structure models,” Journal of Physics: Condensed Matter. 2002. link Times cited: 11 Abstract: Undoped and boron-doped a-Si1-xCx:H, for x≈0.5, films have b… read more Abstract: Undoped and boron-doped a-Si1-xCx:H, for x≈0.5, films have been prepared by means of plasma-enhanced chemical-vapour deposition using methyltrichlorosilane. The optical absorption spectra of these films demonstrate three characteristic peaks at about 1.6, 2.0 and 2.5 eV consistent with other experimental measurements. To explain the observed peculiarities of the spectra, the atomic and electronic structures of a-SiC have been investigated using both molecular dynamics simulations based on an empirical potential and the recursion method. The results of the calculations show that five-coordinated (T5) atoms (floating-bond atoms), anomalous four-coordinated (T4a) sites (weak-bond atoms), three-coordinated (T3) defects (dangling-bond atoms) and normal four-coordinated (T4n) atoms which are nearest neighbours of T3, T4a or T5 atoms give rise to three gap peaks. It was established that three peaks in the low-energy region of the optical absorption spectra are due to the electronic transitions: the valence band → the empty gap peak and two occupied gap peaks → the conduction band. Boron doping effects upon the optical spectra was not revealed. read less S. Goel, X. Luo, A. Agrawal, and R. Reuben, “Diamond machining of silicon: A review of advances in molecular dynamics simulation,” International Journal of Machine Tools & Manufacture. 2015. link Times cited: 314 Y. Gao et al., “Investigation of interfacial matching between 3C-SiC substrate crystals and its surface layer deposited Cu elements using molecular dynamics simulations,” Surfaces and Interfaces. 2023. link Times cited: 0 J. Q. Zhang, B. B. He, and B. Zhang, “On the transition of failure mechanisms during machining process with varied speeds: A molecular dynamics study,” Journal of Manufacturing Processes. 2023. link Times cited: 0 K. W. Kayang and A. N. Volkov, “Turning nanopowder into nanomaterial: Effect of continuous SiC coating on mechanical properties of Si nanoparticle arrays,” Materialia. 2023. link Times cited: 0 Z. Chang et al., “Simulation study of nucleation mechanism of grown-in dislocations near grain boundary during solidification of silicon,” Physica B: Condensed Matter. 2023. link Times cited: 0 C. Pan, L. Zhang, W. Jiang, R. Wang, L. Chen, and T. Wang, “Atomistic simulation of brittle-to-ductile transition in silicon carbide embedded with nano-sized helium bubbles,” Journal of Physics D: Applied Physics. 2023. link Times cited: 0 Abstract: The tensile response of cubic silicon carbide (SiC) bulk con… read more Abstract: The tensile response of cubic silicon carbide (SiC) bulk containing cavities (voids and He bubbles) has been investigated using molecular dynamic simulations. The formation of cavities in SiC leads to a significant degradation in the mechanical properties of SiC with more influence on material fracture than initial elastic deformation. The brittle-to-ductile transition occurs in cavity-embedded SiC as the pressure in He bubbles increases. This is associated with the deformation mechanism that bond breaking at a low He bubble pressure transfers to extensive dislocation activities at a higher He bubble pressure. The cavities can effectively concentrate stress around them in the direction perpendicular to the tension, which leads to preferred cracking in the region with a higher tensile stress. The failure mechanism as revealed by this study improves understanding of property degradation in SiC that may be useful for applications of SiC in advanced nuclear energy systems. read less J. Costantini, G. Gutierrez, M. Guillaumet, and G. Lelong, “Optical spectroscopy study of damage in ion-irradiated 3C-SiC epilayers on a silicon substrate,” Journal of Applied Physics. 2023. link Times cited: 0 Abstract: Epitaxial cubic (100) 3C-SiC films on a (100) silicon wafer … read more Abstract: Epitaxial cubic (100) 3C-SiC films on a (100) silicon wafer were irradiated at room temperature with 2.3-MeV Si+ or 3.0-MeV Kr+ ions up to a fluence of 1 × 1016 cm−2. The evolutions of the epilayer and the substrate were followed as a function of ion fluence by using micro-Raman spectroscopy, optical absorption, and diffuse reflectance spectroscopy in the UV-visible and near infrared range. Raman spectra evidence the amorphization of SiC films at an estimated dose of about 0.1 displacement per atom (dpa) for both ion irradiations. The narrow peaks of the Raman-allowed TO and LO modes of SiC and Si are recorded in the virgin sample, together with few peaks assigned to zone-edge modes of SiC arising from the intrinsic disorder in the strained films. Those crystal phonon peaks broaden or disappear with increasing fluence. The spectra finally exhibit broad extra peaks assigned to the formation of Si–Si and C–C wrong homonuclear bonds in the local order of the amorphous phase. The optical transmission and diffuse reflectance spectra feature interference fringe patterns in the SiC film that are smoothened out with irradiation due to the matching of refractive indices of the amorphous SiC film and Si substrate. The evolution of the refractive index of SiC and optical gap of Si are deduced from those spectra. The respective roles of ballistic effects and electronic excitations in the radiation damage of both SiC and Si are discussed for those two ions with about the same electronic stopping power and about one order-of-magnitude difference in nuclear stopping power. The damage is dominated by the nuclear collision processes and rather well correlated with the estimated irradiation dose in dpa. Optical spectra show that electronic excitations induce damage recovery of the amorphized substrate below the SiC/Si interface. Raman spectra and optical absorption/reflection spectra yield complementary pictures of the radiation damage. read less E. Mørtsell, D. Zhao, A. Autruffe, Y. Chen, M. Sabatino, and Y. Li, “The Nature of a Low Angle Grain-Boundary in a Si Bi-Crystal with Added Fe Impurities,” SSRN Electronic Journal. 2023. link Times cited: 0 V. Ivashchenko, P. Turchi, R. V. Shevchenko, L. Gorb, J. Leszczynski, and A. Kozak, “An effect of nitrogen incorporation on the structure and properties of amorphous SiC: first-principles molecular dynamics simulations,” Thin Solid Films. 2022. link Times cited: 0 L. Xue, G. Feng, and S. Liu, “Molecular dynamics study of temperature effect on deformation behavior of m-plane 4H–SiC film by nanoindentation,” Vacuum. 2022. link Times cited: 5 M. Roshan, A. Akbarzadeh, S. Sadeghzadeh, and A. Maleki, “Tailoring the hardness of aluminum surface reinforced with graphene and C3N nanosheets,” Diamond and Related Materials. 2022. link Times cited: 1 F. Z. Zanane, K. Sadki, L. B. Drissi, and E. H. Saidi, “Graphene-based SiC Van der Waals heterostructures: nonequilibrium molecular dynamics simulation study,” Journal of Molecular Modeling. 2022. link Times cited: 3 W. Li et al., “Rate dependence and anisotropy of SiC response to ramp and wave-free quasi-isentropic compression,” International Journal of Plasticity. 2021. link Times cited: 13 W. Li, E. Hahn, X. Yao, T. Germann, B. Feng, and X. Zhang, “On the grain size dependence of shock responses in nanocrystalline sic ceramics at high strain rates,” Acta Materialia. 2020. link Times cited: 26 J. Luo, C. Zhou, Y. Cheng, and L. Liu, “Assessing the EDIP potential for atomic simulation of carbon diffusion, segregation and solubility in silicon melt,” Journal of Crystal Growth. 2020. link Times cited: 2 Y. Yang, S. Li, Y. Liang, and B. Li, “Effect of temperature on wetting kinetics in Al/SiC system: a molecular dynamic investigation,” Composite Interfaces. 2020. link Times cited: 8 Abstract: ABSTRACT It is well known that liquid Al wetting on a SiC su… read more Abstract: ABSTRACT It is well known that liquid Al wetting on a SiC substrate is an important process, especially when manufacturing Al/SiC composite materials. Many researchers have attempted to investigate Al/SiC wetting kinetics; however, it is difficult since Al/SiC wetting occurs at high temperatures. It was found that the measured results showed diverse Al/SiC contact angles. Under such circumstances, molecular dynamic (MD) simulations were performed for spreading of Al/SiC and Al-12 at.%Si/SiC, each process merged with heating at 973–1533 K, by which qualitative analysis of temperature effects on atomic distribution, dissolution, and composition were made, those results demonstrated that the temperature change dominated the kinetics of Al/SiC wetting. In accordance with reactive wetting mechanisms, thermal energy successively activated liquid/solid dissolution and interactions in Al/SiC. Increased temperature was attributed to the enhancement of Al/SiC wettability through the increased Al diffusion coefficient. Graphical Abstract read less M. Kohestanian, Z. sohbatzadeh, and S. Rezaee, “Mechanical properties of continuous fiber composites of cubic silicon carbide (3C-SiC) / different types of carbon nanotubes (SWCNTs, RSWCNTs, and MWCNTs): A molecular dynamics simulation,” Materials today communications. 2020. link Times cited: 11 K. Lim et al., “Design and Simulation of Symmetric Wafer-to-Wafer Bonding Compesating a Gravity Effect,” 2020 IEEE 70th Electronic Components and Technology Conference (ECTC). 2020. link Times cited: 0 Abstract: In this study, a process optimization methodology was propos… read more Abstract: In this study, a process optimization methodology was proposed to minimize the alignment error between contact pads during the direct wafer-to-wafer bonding process. The reason of occurring alignment error in the conventional wafer-to- wafer bonding process is that there is a deformation difference between upper wafer and lower wafer during the bonding process. This deformation difference is occurred by asymmetric pressure head for initiating the bond, wafer anisotropy, and gravitational influence during bonding. In this study, a FEA (Finite Element Analysis) model which can simulate the WtW bonding for optimization of bonding process was developed. In order to define the bonding force acting between the wafers during bonding, characteristics of wafer surface were analyzed by molecular dynamics analysis using SiCN surface model that is plasma-treated with oxide. The bonding force with respect to the distance obtained by analysis were implemented as subroutine and applied to the wafer bonding simulation model in ABAQUS, which is commercial FEA software. The simulation model was verified through comparing bonding propagation distance and alignment error measurement results. We conducted the process optimization to minimize the alignment error using our FEA model. As a result of optimization, wafer-to-wafer bonding process that has an alignment error about tens nm level was proposed. read less R. Feng et al., “Molecular Dynamics Simulation to Investigate the Rake Angle Effects on Nanometric Cutting of Single Crystal Ni3Al,” International Journal of Precision Engineering and Manufacturing. 2019. link Times cited: 1 Z. Wu, W. Liu, and L. Zhang, “Effect of structural anisotropy on the dislocation nucleation and evolution in 6H SiC under nanoindentation,” Ceramics International. 2019. link Times cited: 23 Z. Wu, W. Liu, L. Zhang, and S. Lim, “Amorphization and Dislocation Evolution Mechanisms of Single Crystalline 6H-SiC,” Materials Engineering eJournal. 2019. link Times cited: 67 Abstract: The amorphization and dislocation evolution mechanisms of a … read more Abstract: The amorphization and dislocation evolution mechanisms of a single crystal 6H-SiC were systematically investigated by using nano-indentation, high-resolution transmitted electron microscope (HRTEM), molecular dynamics (MD) simulations and the generalized stacking fault (GSF) energy surface analysis. Two major plastic deformation mechanisms of 6H-SiC under nano-indentation were revealed by HRTEM, i.e., (1) an amorphization region near the residual indentation mark, and (2) dislocations below the amorphization region in both the basal and prismatic planes. MD results showed that the amorphization process corresponds to the first “pop-in” event of the indentation load-displacement curve, while the dislocation nucleation and propagation are related to the consequent “pop-in” events. The amorphization is confirmed to achieve via an initial transformation from wurtzite structure to an intermediate structure, and then a further amorphization process. read less S. Gur, M. Sadat, G. Frantziskonis, S. Bringuier, L. Zhang, and K. Muralidharan, “The effect of grain-size on fracture of polycrystalline silicon carbide: A multiscale analysis using a molecular dynamics-peridynamics framework,” Computational Materials Science. 2019. link Times cited: 23 C. Huang, X. Peng, B. Yang, S. Weng, Y. Zhao, and T. Fu, “Grain size dependence of tensile properties in nanocrystalline diamond,” Computational Materials Science. 2019. link Times cited: 17 C. Huang et al., “Effects of strain rate and annealing temperature on tensile properties of nanocrystalline diamond,” Carbon. 2018. link Times cited: 33 T. Narumi, Y. Shibuta, and T. Yoshikawa, “Molecular dynamics simulation of interfacial growth of SiC from Si–C solution on different growth planes,” Journal of Crystal Growth. 2018. link Times cited: 3 C. Huang et al., “Molecular dynamics simulations for responses of nanotwinned diamond films under nanoindentation,” Ceramics International. 2017. link Times cited: 40 L. Wang, W. Yu, and S. Shen, “Fracture of β-SiC bulk with a void of different shapes under different loading modes,” Engineering Fracture Mechanics. 2017. link Times cited: 6 C. Xiao, H. He, J. Li, S. Cao, and W. Zhu, “Thermal conductivity of thin finite-size β-SiC calculated by molecular dynamics combined with quantum correction,” 2017 18th International Conference on Electronic Packaging Technology (ICEPT). 2017. link Times cited: 0 Abstract: Silicon carbide (SiC) is a most promising alternative materi… read more Abstract: Silicon carbide (SiC) is a most promising alternative material for the next generation of high-power and high-temperature devices duo to excellent performance, such as larger thermal conductivity compared with Silicon. The thermal conductivity of SiC bulk, as well as temperature dependence of thermal conductivity has been investigated in terms of simulations and experiments. However, when the characteristic size of materials is down to nanoscale, the thermal properties will be significantly different from bulk materials. Thus, it is important to understand the heat transport behavior of SiC thin films for developing nanoscale SiC devices. Nevertheless, thermal properties of SiC thin films have not been investigated systematically. In this paper, a non-equilibrium molecular dynamics model combined with quantum correction is presented for characterizing the thermal conductivity of thin finite-size β-SiC. Adopting the Tersoff empirical potential, temperature effect on thermal conductivity is predicted based on this model. It is found that the uncorrected lattice thermal conductivity diminishes evidently with decrease of temperature. Unlike the uncorrected results, the corrected results display a slight increase with temperature to a maximum value at ∼760 K This work provides a possible theoretical and computational basis for heat transfer and dissipation applications of nanoscale β-SiC thin film, and would also help the design of thermal barriers or new thermoelectric materials. read less T. Kuwahara, H. Ito, K. Kawaguchi, Y. Higuchi, N. Ozawa, and M. Kubo, “Origin of Chemical Order in a-SixCyHz: Density-Functional Tight-Binding Molecular Dynamics and Statistical Thermodynamics Calculations,” Journal of Physical Chemistry C. 2016. link Times cited: 2 Abstract: We investigate the growth mechanisms and structures of hydro… read more Abstract: We investigate the growth mechanisms and structures of hydrogenated amorphous silicon carbide (a-SixCyHz) during chemical vapor deposition (CVD) by using density-functional tight-binding molecular dynamics (DFTB MD) and statistical thermodynamics (ST) calculations. Our multiscale modeling from an atomic to an experimental scale allows us to bridge the gap between micro- and macroscopic knowledge. As in any compound, the degree of chemical order in a-SixCyHz is of practical importance. However, the origin of chemical order and effects of composition on the degree of chemical order remain unknown. First, CVD simulations are performed by the impingement of CH3 and SiH3 radicals on a Si(001)-(2 × 1):H surface with DFTB MD. The initial growth process consists of an abstraction-adsorption mechanism, where a CH3 or SiH3 radical abstracts a H atom and forms a dangling bond (DB) on the surface, and a subsequent CH3 or SiH3 radical is adsorbed on the DB. A surface-adsorbed CH2 species with a DB is inserted into a n... read less W. Lee, X. Yao, W. Jian, and Q. Han, “High-velocity shock compression of SiC via molecular dynamics simulation,” Computational Materials Science. 2015. link Times cited: 25 K. Kang, T. Eun, M.-C. Jun, and B.-J. Lee, “Governing factors for the formation of 4H or 6H-SiC polytype during SiC crystal growth: An atomistic computational approach,” Journal of Crystal Growth. 2014. link Times cited: 30 H. Lan and C. Liu, “The hardness of amorphous Si-DLC films by molecular dynamics simulations,” Journal of Wuhan University of Technology-Mater. Sci. Ed. 2013. link Times cited: 4 D. Huang, J. Pu, Z. Lu, and Q. Xue, “Microstructure and surface roughness of graphite‐like carbon films deposited on silicon substrate by molecular dynamic simulation,” Surface and Interface Analysis. 2012. link Times cited: 14 Abstract: Molecular dynamics simulations are performed on the atomic o… read more Abstract: Molecular dynamics simulations are performed on the atomic origin of the growth process of graphite‐like carbon film on silicon substrate. The microstructure, mass density, and internal stress of as‐deposited films are investigated systematically. A strong energy dependence of microstructure and stress is revealed by varying the impact energy of the incident atoms (in the range 1–120 eV). As the impact energy is increased, the film internal stress converts from tensile stress to compressive stress, which is in agreement with the experimental results, and the bonding of C‐Si in the film is also increased for more substrate atoms are sputtered into the grown film. At the incident energy 40 eV, a densification of the deposited material is observed and the properties such as density, sp3 fraction, and compressive stress all reach their maximums. In addition, the effect of impact energy on the surface roughness is also studied. The surface morphology of the film exhibits different characteristics with different incident energy. When the energy is low (<40 eV), the surface roughness is reduced with the increasing of incident energy, and it reaches the minimum at 50 eV. Copyright © 2012 John Wiley & Sons, Ltd. read less S. Goel, X. Luo, R. Reuben, and W. B. Rashid, “Atomistic aspects of ductile responses of cubic silicon carbide during nanometric cutting,” Nanoscale Research Letters. 2011. link Times cited: 84 H. Lan, T. Kato, and C. Liu, “Molecular dynamics simulations of atomic-scale tribology between amorphous DLC and Si-DLC films,” Tribology International. 2011. link Times cited: 23 D. Bai, “Size, Morphology and Temperature Dependence of the Thermal Conductivity of Single-Walled Silicon Carbide Nanotubes,” Fullerenes, Nanotubes and Carbon Nanostructures. 2011. link Times cited: 11 Abstract: The thermal conductivity of single-walled silicon carbide na… read more Abstract: The thermal conductivity of single-walled silicon carbide nanotubes (SW-SiCNTs) has been investigated by molecular dynamics (MD) simulation using the many-body Tersoff potential. To validate the reliability of the simulations code, the following measures have been taken: The calculated potential energies of SW-SiCNTs and the calculated thermal conductivities of single-walled carbon nanotubes (SWCNTs) are, respectively, compared with available data, and both comparisons are in good agreement. To investigate the size (tube length and diameter), morphology (chirality and the atom arrangement) and temperature dependence of the thermal conductivity of SW-SiCNTs, the thermal conductivities of SW-SiCNTs with different sizes, morphologies and temperatures, are calculated and compared with each other. It is found that (1) as the temperature increases, the thermal conductivity decreases at different rate, which depends on the tube morphology; (2) as long as the length increases, the thermal conductivity increases correspondingly; (3) the thermal conductivity depends on the tube diameter and exhibits a peaking behavior as a function of diameter; (4) atom arrangement strongly affects the thermal conductivity not only in quantity but also in the extent of dependence on chirality; and (5) the thermal conductivity is dependent on the chirality of nanotube with different extent. read less N. Swaminathan, P. Kamenski, D. Morgan, and I. Szlufarska, “Effects of grain size and grain boundaries on defect production in nanocrystalline 3C–SiC,” Acta Materialia. 2010. link Times cited: 83 K. Morishita, Y. Watanabe, A. Kohyama, H. Heinisch, and F. Gao, “Nucleation and growth of vacancy clusters in β-SiC during irradiation,” Journal of Nuclear Materials. 2009. link Times cited: 15 K. Biswas, C. Myles, M. Sanati, and G. Nolas, “Thermal properties of guest-free Si136 and Ge136 clathrates: A first-principles study,” Journal of Applied Physics. 2008. link Times cited: 16 Abstract: We have used the generalized gradient approximation (GGA) to… read more Abstract: We have used the generalized gradient approximation (GGA) to density functional theory to study the vibrational and thermal properties of guest-free Si136 and Ge136 clathrates. In order to study the effects of supercell size on our results, we have performed both 34 and 136 atom supercell calculations for each material. We find that the 34 atom supercell calculations predict a small frequency downshift (in comparison with the 136 atom supercell calculations) in the vibrational density of states of both materials. The GGA-predicted Γ phonon frequency of Si136 (480 cm−1 at T=0 K) obtained from the 136 atom calculations is in very good agreement with the experimental value for Na1Si136 (484 cm−1 at T=300 K). Using the results from our 136 atom calculations, we have also calculated the temperature dependence of the vibrational contributions to the Helmholtz free energy, the entropy, and the specific heat (CV) of the guest-free Si136 and Ge136 clathrates. The predicted and experimental heat capacities of Si136... read less V. Ivashchenko, P. Turchi, and V. Shevchenko, “Simulations of the mechanical properties of crystalline, nanocrystalline, and amorphous SiC and Si,” Physical Review B. 2007. link Times cited: 84 Abstract: Molecular-dynamics simulations of crystalline (c), nanocryst… read more Abstract: Molecular-dynamics simulations of crystalline (c), nanocrystalline (nc), and amorphous (a) silicon carbides and silicon were carried out to investigate their vibrational and mechanical properties. The atomic configurations, vibrational spectra, and stress-strain curves were calculated at room temperature. In the case of the nanocrystalline structures, these characteristics were analyzed as functions of grain size. Young's and bulk modul and yield and flow stresses were determined from uniaxial deformation of samples under periodic boundary constraints and from experiments on rod extension. For silicon carbides, Young's modulus and flow stress decrease in the sequence ``c-nc-a,'' and with decreasing grain size, which is attributed to a weakening of the Si--C bonds in the amorphous matrix. The enhancement of the strength properties of the homopolar nc--Si structures is attributed to their deformation anisotropy. The calculated vibrational spectra and Young's moduli are in rather good agreement with the corresponding experimental characteristics. read less V. Ivashchenko and P. Turchi, “Atomic-Scale Sliding Friction of Amorphous and Nanostructured SiC and Diamond Surfaces,” Tribology Transactions. 2006. link Times cited: 6 Abstract: Large-scale molecular dynamics simulations are applied to st… read more Abstract: Large-scale molecular dynamics simulations are applied to study the sliding friction of amorphous silicon carbide on amorphous silicon carbide, amorphous silicon carbide on diamond, nano–crystalline silicon carbide on diamond, and crystalline silicon on diamond systems. The friction coefficient and structural evolution of these systems are investigated as functions of sliding velocity, temperature, and normal load. Based on our results, the physics of atomic-scale sliding friction in crystalline, nanocrystalline, and amorphous materials under investigation is clarified. The established regularities are validated with available experimental results. Presented at the STLE Annual Meeting in Las Vegas, Nevada, May 15-19, 2005 Review led by Greg Sawyer read less M. Ishimaru, I. Bae, A. Hirata, Y. Hirotsu, J. Valdez, and K. Sickafus, “Volume swelling of amorphous SiC during ion-beam irradiation,” Physical Review B. 2005. link Times cited: 40 Abstract: Relationships between chemical short-range order and volume … read more Abstract: Relationships between chemical short-range order and volume swelling of amorphous silicon carbide (SiC) under radiation environments have been examined using energy-filtering transmission electron microscopy in combination with imaging plate techniques. Single crystals of 4H-SiC with (0001) orientation were irradiated with 300 keV xenon ions to a fluence of 10{sup 15} cm{sup -2} at cryogenic (120 K) and elevated (373 K) temperatures. A continuous amorphous layer was formed in both specimens, but the magnitude of their volume change was different: volume swelling becomes more pronounced with decreasing irradiation temperatures. From radial distribution function analyses, it was found that the amount of Si-Si atomic pairs increases more rapidly than that of C-C atomic pairs with the progress of chemical disordering. We discuss the ion-beam-induced swelling in amorphous SiC within the context of our results as well as previous observations. read less J. Kim, B. Lee, H. Nam, and D. Kwon, “Effect of substrate temperature on structure and intrinsic stress in vapor-deposited amorphous silicon carbide film,” Thin Solid Films. 2004. link Times cited: 2 V. I. Ivashchenko, P. Turchi, V. Shevchenko, and O. Shramko, “Molecular dynamics simulations of a − SiC films,” Physical Review B. 2004. link Times cited: 19 Abstract: Empirical molecular dynamics simulations combined with a rec… read more Abstract: Empirical molecular dynamics simulations combined with a recursion procedure are applied to the study of the atomic and electronic structures of $a\text{\ensuremath{-}}\mathrm{SiC}$ thin films. The films are generated from the condensation of diluted $\mathrm{Si}\text{\ensuremath{-}}\mathrm{C}$ vapor on a crystalline silicon substrate similarly to atom-by-atom deposition. The as-deposited films are annealed at different temperatures. Growth kinetics, bonding configuration, chemical ordering, cohesion, relaxation effects, surface roughness, atomic level stress, and electronic properties of the films are investigated as functions of the deposition parameters: vapor temperature, applied particle force, and substrate and annealing temperatures. The results are compared with those associated with bulk and film samples of $a\text{\ensuremath{-}}\mathrm{SiC}$ generated from the melt. The main theoretical findings on $a\text{\ensuremath{-}}\mathrm{SiC}$ films are in rather good agreement with experimental evidences. read less J. ·. Kim, B. Lee, H. Nam, and D. Kwon, “Molecular Dynamics Analysis of Structure and Intrinsic Stress in Amorphous Silicon Carbide Film with Deposition Process Parameters,” Materials Science Forum. 2004. link Times cited: 0 Abstract: Amorphous silicon carbide (a-SiC) films were deposited using… read more Abstract: Amorphous silicon carbide (a-SiC) films were deposited using molecular dynamics simulations employing the Tersoff potential. The structure and intrinsic stress of a-SiC films changed dramatically with changes in such principal deposition process parameters as substrate temperature and incident energy. Changes in structure and intrinsic stress with deposition process parameters were analyzed. read less N. Marks, J. Bell, G. Pearce, D. Mckenzie, and M. Bilek, “Atomistic simulation of energy and temperature effects in the deposition and implantation of amorphous carbon thin films,” Diamond and Related Materials. 2003. link Times cited: 28 S. Muto and T. Tanabe, “Local structures and damage processes of electron irradiated α-SiC studied with transmission electron microscopy and electron energy-loss spectroscopy,” Journal of Applied Physics. 2003. link Times cited: 36 Abstract: Damaged structures of α-SiC below and above the critical tem… read more Abstract: Damaged structures of α-SiC below and above the critical temperature of amorphization (Tc) under high-energy electron irradiation were studied by means of transmission electron microscopy and electron energy-loss spectroscopy. Above Tc, crystal fragmentation takes place due to local lattice strains caused by preferential displacements, subsequent outward diffusion of carbon atoms and formation of silicon nano-clusters. On the other hand, the amorphous structure formed below Tc can be well characterized by the formation of Si–Si, Si–C, and sp3 C–C covalent bonds with the tetrahedral coordination locally retained and uniformly distributed. The primary amorphization process under electron irradiation can be interpreted by the defect-accumulation model, in which displaced atoms are frozen at interstitial sites before long-distance diffusion by reconstructing the surrounding structure to relax the local strains. Accordingly the amorphization process is controlled essentially by the mobility of displaced carbon... read less V. Ivashchenko, P. Turchi, V. Shevchenko, L. A. Ivashchenko, and G. V. Rusakov, “Tight-binding molecular-dynamics simulations of amorphous silicon carbides,” Physical Review B. 2002. link Times cited: 24 Abstract: Atomic and electronic structures of amorphous tetrahedral si… read more Abstract: Atomic and electronic structures of amorphous tetrahedral silicon carbide a-SiC are analyzed on the basis of molecular dynamics simulations performed in the framework of a ${\mathrm{sp}}^{3}{s}^{}$ tight-binding force model. The a-SiC samples are generated from dilute vapors and melts. The topology and the local chemical order of the resulting amorphous networks are very sensitive to the initial high-temperature structures. The simulations are used to investigate the electronic distribution in the band gap region and the changes in the density of states caused by the presence of homo-polar bonds, coordination defects, and strongly distorted tetrahedral species. For completeness the results obtained for a-SiC are compared with those from various semiempirical schemes and from ab initio pseudopotential calculations. read less F. Gao, E. Bylaska, W. J. Weber, and L. Corrales, “Native defect properties in β-SiC: Ab initio and empirical potential calculations,” Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms. 2001. link Times cited: 44 F. Gao, W. J. Weber, and R. Devanathan, “Atomic-scale simulation of displacement cascades and amorphization in β-SiC,” Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms. 2001. link Times cited: 43 F. Gao and W. J. Weber, “Computer simulation of disordering and amorphization by Si and Au recoils in 3C–SiC,” Journal of Applied Physics. 2001. link Times cited: 60 Abstract: Molecular dynamics has been employed to study the disorderin… read more Abstract: Molecular dynamics has been employed to study the disordering and amorphization processes in SiC irradiated with Si and Au ions. The large disordered domains, consisting of interstitials and antisite defects, are created in the cascades produced by Au primary knock-on atoms (PKAs); whereas Si PKAs generate only small interstitial clusters, with most defects being single interstitials and vacancies distributed over a large region. No evidence of amorphization is found at the end of the cascades created by Si recoils. However, the structure analysis indicates that the large disordered domains generated by Au recoils can be defined as an amorphous cluster lacking long-range order. The driving force for amorphization in this material is due to the local accumulation of Frenkel pairs and antisite defects. These results are in good agreement with experimental evidence, i.e., the observed higher disordering rate and the residual disorder after annealing for irradiation with Au2+ are associated with a higher prob... read less L. Malerba and J. Perlado, “Molecular dynamics simulation of irradiation-induced amorphization of cubic silicon carbide,” Journal of Nuclear Materials. 2001. link Times cited: 45 L. Malerba, J. Perlado, A. Sánchez-Rubio, I. Pastor, L. Colombo, and T. D. Rubia, “Molecular dynamics simulation of defect production in irradiated β-SiC,” Journal of Nuclear Materials. 2000. link Times cited: 13 R. Devanathan and W. J. Weber, “Displacement energy surface in 3C and 6H SiC,” Journal of Nuclear Materials. 2000. link Times cited: 190 M. Ishimaru, S. Munetoh, T. Motooka, K. Moriguchi, and A. Shintani, “Behavior of impurity atoms during crystal growth from melted silicon: carbon atoms,” Journal of Crystal Growth. 1998. link Times cited: 3 J. Li, L. Porter, and S. Yip, “Atomistic modeling of finite-temperature properties of crystalline β-SiC: II. Thermal conductivity and effects of point defects,” Journal of Nuclear Materials. 1998. link Times cited: 248 R. Devanathan, W. J. Weber, and T. D. Rubia, “Computer simulation of a 10 keV Si displacement cascade in SiC,” Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms. 1998. link Times cited: 89 L. Xue et al., “Study of deformation mechanism of structural anisotropy in 4H–SiC film by nanoindentation,” Materials Science in Semiconductor Processing. 2022. link Times cited: 5 T. Korkut, “A molecular dynamics study about graphite and boron coated graphite at reactor temperatures,” Annals of Nuclear Energy. 2014. link Times cited: 3 H. Lan, T. Kumagai, and T. Kato, “Research on Silicon Content and Structure Relationship of Amorphous Si-DLC Films by Molecular Dynamics Simulations.” 2009. link Times cited: 1 M. Ishimaru and T. Motooka, “Molecular Dynamics Simulations of Crystal Growth from Melted silicon: Defect Formation Processes,” MRS Proceedings. 1998. link Times cited: 0 Abstract: Molecular dynamics calculations have been performed to simul… read more Abstract: Molecular dynamics calculations have been performed to simulate crystal growth from melted silicon (Si) and defect formation processes based on the ordinary Langevin equation employing the Tersoff interatomic potential. The findings of this investigation are as follows: (1) The [110] bonds at the solid-liquid interface induce the eclipsed configurations or hexagonal Si structures which stabilize microfacets composed of the {l{underscore}brace}111{r{underscore}brace} planes. (2) Defect formation during crystal growth processes is due to misorientations at the {l{underscore}brace}111{r{underscore}brace} interfaces which result in an elementary grown-in defect structure including five- and seven-member rings. (3) The elementary grown-in defect migrates in c-Si by bond-switching motions during further crystal pulling or annealing. read less Y. Huang, Y. Zhou, J. Li, and F. Zhu, “Understanding the role of surface mechanical properties in SiC surface machining,” Materials Science in Semiconductor Processing. 2023. link Times cited: 0 H. Li et al., “Observation of defect density dependent elastic modulus of graphene,” Applied Physics Letters. 2023. link Times cited: 0 Abstract: The recent decade has witnessed a tremendous development of … read more Abstract: The recent decade has witnessed a tremendous development of graphene applications in many fields; however, as one of the key considerations, the mechanical properties of graphene still remain largely unexplored. Herein, by employing focused ion beam irradiation, graphene with various defect levels is obtained and further investigated by using Raman spectroscopy and scanning tunneling microscopy. Specially, our atomic force microscopy based nanomechanical property measurement demonstrates a clear defect density dependent behavior in the elastic modulus of graphene on a substrate as the defect density is higher than a threshold value of 1012 cm−2, where a clear decay is observed in the stiffness of graphene. This defect density dependence is mainly attributed to the appearance of amorphous graphene, which is further confirmed with our molecular dynamics calculations. Therefore, our reported result provides an essential guidance to enable the rational design of graphene materials in nanodevices, especially from the perspective of mechanical properties. read less Y. Liu et al., “Deep learning inter-atomic potential for irradiation damage in 3C-SiC,” Computational Materials Science. 2023. link Times cited: 0 Z. Lou, Y. Yan, C. Li, and Y. Geng, “Deformation behavior of high-entropy alloys under dual-tip probe scratching,” Journal of Alloys and Compounds. 2023. link Times cited: 1 A. Galashev, “Computational Modeling of Doped 2D Anode Materials for Lithium-Ion Batteries,” Materials. 2023. link Times cited: 2 Abstract: Development of high-performance lithium-ion batteries (LIBs)… read more Abstract: Development of high-performance lithium-ion batteries (LIBs) is boosted by the needs of the modern automotive industry and the wide expansion of all kinds of electronic devices. First of all, improvements should be associated with an increase in the specific capacity and charging rate as well as the cyclic stability of electrode materials. The complexity of experimental anode material selection is now the main limiting factor in improving LIB performance. Computer selection of anode materials based on first-principles and classical molecular dynamics modeling can be considered as the main paths to success. However, even combined anodes cannot always provide high LIB characteristics and it is necessary to resort to their alloying. Transmutation neutron doping (NTD) is the most appropriate way to improve the properties of thin film silicon anodes. In this review, the effectiveness of the NTD procedure for silicene/graphite (nickel) anodes is shown. With moderate P doping (up to 6%), the increase in the capacity of a silicene channel on a Ni substrate can be 15–20%, while maintaining the safety margin of silicene during cycling. This review can serve as a starting point for meaningful selection and optimization of the performance of anode materials. read less B. Yao, Z. R. Liu, and R. F. Zhang, “EAPOTc: An integrated empirical interatomic potential optimization platform for compound solids,” Computational Materials Science. 2022. link Times cited: 1 X. Guo, Y. Gao, Z. Meng, and T. Gao, “Effect of Cooling Rate on the Crystal Quality and Crystallization Rate of SiC during Rapid Solidification Based on the Solid–Liquid Model,” Crystals. 2022. link Times cited: 1 Abstract: The silicon carbide (SiC) that can achieve better electron c… read more Abstract: The silicon carbide (SiC) that can achieve better electron concentration and motion control is more suitable for the production of high temperature, high frequency, radiation resistance, and high-power electronic devices. However, the fabrication of the high purity single crystal is challenging, and it is hard to observe the structural details during crystallization. Here, we demonstrate a study of the crystallization of single-crystal SiC by the molecular dynamic simulations. Based on several structure analysis methods, the transition of the solid–liquid SiC interface from a liquid to a zinc-blende structure is theoretically investigated. The results indicate that most of the atoms in the solid–liquid interface begin to crystallize with rapid solidification at low cooling rates, while crystallization does not occur in the system at high cooling rates. As the quenching progresses, the number of system defects decreases, and the distribution is more concentrated in the solid–liquid interface. A maximum crystallization rate is observed for a cooling rate of 1010 K/s. Moreover, when a stronger crystallization effect is observed, the energy is lower, and the system is more stable. read less Z. Lou, Y. Yan, Y. Geng, X. Zhao, and Z. Hao, “The effect of anisotropy of nickel-based single crystal alloys on the surface quality of sub-nanometer and near atomic scale cutting,” Intermetallics. 2022. link Times cited: 6 J. Luo, C. Zhou, Q. Li, and L. Liu, “Thermodynamic Formation Properties of Point Defects in Germanium Crystal,” Materials. 2022. link Times cited: 0 Abstract: Point defects are crucial in determining the quality of germ… read more Abstract: Point defects are crucial in determining the quality of germanium crystals. A quantitative understanding of the thermodynamic formation properties of the point defects is necessary for the subsequent control of the defect formation during crystal growth. Here, molecular dynamics simulations were employed to investigate the formation energies, total formation free energies and formation entropies of the point defects in a germanium crystal. As far as we know, this is the first time that the total formation free energies of point defects in a germanium crystal have been reported in the literature. We found that the formation energies increased slightly with temperature. The formation free energies decreased significantly with an increase in temperature due to the increase in entropy. The estimated total formation free energies at the melting temperature are ~1.3 eV for self-interstitial and ~0.75 eV for vacancy, corresponding to a formation entropy of ~15 kB for both types of point defects. read less M. Eghbalian, R. Ansari, and S. Rouhi, “Effects of geometrical parameters and functionalization percentage on the mechanical properties of oxygenated single-walled carbon nanotubes,” Journal of Molecular Modeling. 2021. link Times cited: 8 B. Yao, Z. Liu, and R. Zhang, “EAPOTs: An integrated empirical interatomic potential optimization platform for single elemental solids,” Computational Materials Science. 2021. link Times cited: 3 J. Luo, Y. Cheng, C. Zhou, T. Sinno, and L. Liu, “A general approach for calculating melt–solid impurity segregation coefficients based on thermodynamic integration,” Journal of Applied Physics. 2021. link Times cited: 1 Abstract: The equilibrium segregation of impurities at the melt–solid … read more Abstract: The equilibrium segregation of impurities at the melt–solid interface during silicon crystallization is a key factor in determining the impurity concentration and distribution in the crystal. Unfortunately, this property is difficult to measure experimentally due to the presence of complex transport physics in the melt. Here, using the Tersoff family of empirical potential models, we describe a thermodynamic integration framework for computing the interstitial oxygen and substitutional carbon segregation coefficients in silicon. Thermodynamic integration using an ideal gas reference state for the impurity atoms is shown to be an efficient and convenient pathway for evaluating impurity chemical potentials in both solid and liquid phases. We find that the segregation coefficient is captured well for substitutional carbon impurity while it is significantly underestimated for interstitial oxygen. The latter discrepancy is partially attributed to the qualitatively incorrect silicon solid-to-liquid density ratio predicted by the empirical interatomic potential. read less C. Huang, X. Peng, and B. Yang, “Effect of heterointerface on the indentation behavior of nano-laminated c-BN/diamond composites,” Ceramics International. 2021. link Times cited: 6 A. Galashev and O. Rakhmanova, “Promising two-dimensional nanocomposite for the anode of the lithium-ion batteries. Computer simulation,” Physica E-low-dimensional Systems & Nanostructures. 2021. link Times cited: 10 D. T. N. Tranh, V. V. Hoang, and T. T. Hanh, “Modeling glassy SiC nanoribbon by rapidly cooling from the liquid: An affirmation of appropriate potentials,” Physica B-condensed Matter. 2021. link Times cited: 6 A. Galashev, K. Ivanichkina, A. Vorob’ev, O. Rakhmanova, K. Katin, and M. Maslov, “Improved lithium-ion batteries and their communication with hydrogen power,” International Journal of Hydrogen Energy. 2021. link Times cited: 9 Z. Hao, Z. Lou, and Y. Fan, “Influence of anisotropy of nickel-based single crystal superalloy in atomic and close-to-atomic scale cutting,” Precision Engineering-journal of The International Societies for Precision Engineering and Nanotechnology. 2020. link Times cited: 13 Q. Liu, Q. Liu, W. Yu, H. Luo, X. Ren, and S. Shen, “Tuning thermal resistance of SiC crystal/amorphous layered nanostructures via changing layer thickness,” Computational Materials Science. 2020. link Times cited: 2 Q. Liu, L. Li, Y. Jeng, G. Zhang, C. Shuai, and X. Zhu, “Effect of interatomic potentials on modeling the nanostructure of amorphous carbon by liquid quenching method,” Computational Materials Science. 2020. link Times cited: 9 T. C. Sagar, V. Chinthapenta, and M. Horstemeyer, “Effect of defect guided out-of-plane deformations on the mechanical properties of graphene,” Fullerenes, Nanotubes and Carbon Nanostructures. 2020. link Times cited: 5 Abstract: In this paper, nanoscale mechanical properties and failure b… read more Abstract: In this paper, nanoscale mechanical properties and failure behavior of graphene with Stone-Wales defect concentration were investigated using molecular dynamics simulations with the latest ReaxFFC-2013 potential that can accurately capture bond breakages of graphitic compounds. The choice of interatomic potential plays an essential role in capturing the deformation mechanism accurately. Stable configuration of two-dimensional graphene experiences out-of-plane deformation leading to ripples and wrinkles in graphene. It is observed that the mechanical properties such as Young’s modulus, ultimate tensile strength, and the fracture strain are dependent on the out-of-plane deformation, temperature, defect concentration, defect orientation, defect layout and loading configuration. It is observed that the post transient phase non-homogenous ripples and wrinkles influence the mechanical properties at low and high defect concentrations, respectively. read less C. Romero-Rangel, A. Guillén‐López, L. M. Mejia-Mendoza, M. Robles, N. D. Espinosa-Torres, and J. Muñiz, “Approaches on the understanding of nanoporous carbon reactivity with polyatomic ions,” Applied Surface Science. 2019. link Times cited: 4 J. Muñiz, N. Espinosa-Torres, A. Guillén‐López, A. Longoria, A. K. Cuentas-Gallegos, and M. Robles, “Insights into the design of carbon electrodes coming from lignocellulosic components pyrolysis with potential application in energy storage devices: A combined in silico and experimental study,” Journal of Analytical and Applied Pyrolysis. 2019. link Times cited: 17 A. Galashev, K. Katin, and M. Maslov, “Morse parameters for the interaction of metals with graphene and silicene,” Physics Letters A. 2019. link Times cited: 40 X. Nie, L. Zhao, S. Deng, and Y. Zhang, “Molecular dynamic study on crossover of equilibrium time of conduction for silicon/silicon and silicon/silicon carbide pairs on nanoscale,” International Communications in Heat and Mass Transfer. 2018. link Times cited: 3 X. Song and L. Niu, “Effect of uniaxial stress on the threshold displacement energy of silicon carbide,” Journal of Applied Physics. 2018. link Times cited: 2 Abstract: Silicon Carbide (SiC) is a very promising nuclear material. … read more Abstract: Silicon Carbide (SiC) is a very promising nuclear material. Understanding the effect of stress field on the irradiation damage behavior of SiC is crucial for the actual service. Numerous experiment and simulation studies have revealed the fundamental irradiation damage mechanism in non-stress SiC. We can learn from the previous simulation studies that though several limits and inaccuracies in calculating the threshold displacement energy(Ed) have been reported, molecular dynamics (MD) methods are still considered valid in general. In this work, we calculate the Eds of both the elements in SiC along 5 primary crystallographic directions under 13 kinds of uniaxial stress fields using the MD method. The Eds obtained under the non-stress condition are consistent with previous research works. The rules of Eds changing with the deformation are discussed in detail, and the corresponding displacement process and displacement configurations are also analyzed. In general, Eds decrease with the increase in deformation whether it is stretching or compressing. Under relatively high stress field, the reduction of Ed is significant, and the anisotropy of Ed also greatly reduces. A transition of preferred displacement configuration from octahedral interstitial to tetrahedral interstitial is reported and discussed.Silicon Carbide (SiC) is a very promising nuclear material. Understanding the effect of stress field on the irradiation damage behavior of SiC is crucial for the actual service. Numerous experiment and simulation studies have revealed the fundamental irradiation damage mechanism in non-stress SiC. We can learn from the previous simulation studies that though several limits and inaccuracies in calculating the threshold displacement energy(Ed) have been reported, molecular dynamics (MD) methods are still considered valid in general. In this work, we calculate the Eds of both the elements in SiC along 5 primary crystallographic directions under 13 kinds of uniaxial stress fields using the MD method. The Eds obtained under the non-stress condition are consistent with previous research works. The rules of Eds changing with the deformation are discussed in detail, and the corresponding displacement process and displacement configurations are also analyzed. In general, Eds decrease with the increase in deformati... read less C. Huang et al., “Anisotropy effects in diamond under nanoindentation,” Carbon. 2018. link Times cited: 46 Y. Liu, B. Li, and L. Kong, “A molecular dynamics investigation into nanoscale scratching mechanism of polycrystalline silicon carbide,” Computational Materials Science. 2018. link Times cited: 51 L. Wang, Q. Liu, W. Yu, and S. Shen, “Shear response of β-SiC bulk dependent on temperature and strain rate,” Acta Mechanica Solida Sinica. 2017. link Times cited: 1 S. Goel, S. Chavoshi, and A. Murphy, “Molecular dynamics simulation (MDS) to study nanoscale machining processes.” 2017. link Times cited: 2 Abstract: 1 Molecular dynamics simulation (MDS) to study nanoscale cut… read more Abstract: 1 Molecular dynamics simulation (MDS) to study nanoscale cutting processes Saurav Goel1, Saeed Zare Chavoshi2 and Adrian Murphy3 1Precision Engineering Institute, School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield, Bedfordshire, MK430AL, UK 2Mechanical Engineering Department, Imperial College London, London, SW7 2AZ, UK 3School of Mechanical and Aerospace Engineering, Queen’s University, Belfast, BT9 5AH, UK Corresponding author Tel.: +44 1234754132, Email address: sgoel.diamond@gmail.com read less C. Tomas, I. Suarez-Martinez, and N. Marks, “Graphitization of amorphous carbons: A comparative study of interatomic potentials,” Carbon. 2016. link Times cited: 160 H. N. Pishkenari and P. G. Ghanbari, “Vibrational properties of C60: A comparison among different inter-atomic potentials,” Computational Materials Science. 2016. link Times cited: 11 W. Su, Y. Li, C. Nie, W. Xiao, and L. Yan, “First principles study of the C/Si ratio effect on the ideal shear strength of β–SiC,” Materials Research Express. 2016. link Times cited: 3 Abstract: The effect of the C/Si atomic ratio on the ideal shear stren… read more Abstract: The effect of the C/Si atomic ratio on the ideal shear strength of β-SiC is investigated with first principles calculations. β − SiC samples with different C/Si ratios are generated by Monte Carlo (MC) simulations with empirical inter-atomic SiC potential. Each SiC sample is sheared along the 〈 100 〉 direction and the stress-strain curve is calculated from first principles. The results show that the ideal shear strength of SiC decreases with the increase of C/Si ratio. For a non-stoichiometric SiC sample, a C–C bond inside a large carbon cluster breaks first under shear strain condition due to the internal strain around the carbon clusters. Because the band gap is narrowed under shear strain conditions, a local maximum stress appears in the elastic region of the stress-strain curve for each SiC sample at certain strain condition. The yield strength may increase with the increase of C/Si ratio. read less Y. Li and W. Xiao, “First principles study of the C/Si ratio effect on the ideal tensile strength of β-SiC,” Computational Materials Science. 2015. link Times cited: 11 T. Feng, B. Qiu, and X. Ruan, “Anharmonicity and necessity of phonon eigenvectors in the phonon normal mode analysis,” Journal of Applied Physics. 2015. link Times cited: 53 Abstract: It is well known that phonon frequencies can shift from thei… read more Abstract: It is well known that phonon frequencies can shift from their harmonic values when elevated to a finite temperature due to the anharmonicity of interatomic potential. Here, we show that phonon eigenvectors also have shifts, but only for compound materials in which each atom has at least two types of anharmonic interactions with other atoms. Using PbTe as the model material, we show that the shifts in some phonon modes may reach as much as 50% at 800 K. Phonon eigenvectors are used in normal mode analysis (NMA) to predict phonon relaxation times and thermal conductivity. We show, from both analytical derivations and numerical simulations, that the eigenvectors are unnecessary in frequency-domain NMA, which gives a critical revision of previous knowledge. This simplification makes the calculation in frequency-domain NMA more convenient since no separate lattice dynamics calculations are needed. On the other hand, we expect our finding of anharmonic eigenvectors may make difference in time-domain NMA and other areas, like wave-packet analysis. read less R. Gustus et al., “Decomposition of amorphous Si2C by thermal annealing,” Thin Solid Films. 2014. link Times cited: 9 S. Kageyama, N. Matsuki, and H. Fujiwara, “Local network structure of a-SiC:H and its correlation with dielectric function,” Journal of Applied Physics. 2013. link Times cited: 8 Abstract: The microscopic disordered structures of hydrogenated amorph… read more Abstract: The microscopic disordered structures of hydrogenated amorphous silicon carbide (a-Si1−xCx:H) layers with different carbon contents have been determined based on the correlations between the dielectric function in the ultraviolet/visible region and the local bonding states studied by high-sensitivity infrared attenuated total reflection spectroscopy. We find that the microscopic structure of the a-Si1−xCx:H layers fabricated by plasma-enhanced chemical vapor deposition shows a sharp structural transition at a boundary of x = 6.3 at. %. In the regime of x ≤ 6.3 at. %, (i) the amplitude of the a-SiC:H dielectric function reduces and (ii) the SiH2 content increases drastically with x, even though most of the C atoms are introduced into the tetrahedral sites without bonding with H. In the regime of x > 6.3 at. %, on the other hand, (i) the amplitude of the dielectric function reduces further and (ii) the concentration of the sp3 CHn (n = 2,3) groups increases. Moreover, we obtained the direct evidence that th... read less W. Yan, Q. Xie, T. Gao, and X. Guo, “MICROSTRUCTURAL EVOLUTION OF SiC DURING MELTING PROCESS,” Modern Physics Letters B. 2013. link Times cited: 2 Abstract: Microstructural evolution of SiC during melting process is s… read more Abstract: Microstructural evolution of SiC during melting process is simulated with Tersoff potential by using molecular dynamics. Microstructural characteristics are analyzed by radial distribution function, angle distribution function and Voronoi polyhedron index. The results show that the melting point of SiC with Tersoff potential is 3249 K. Tersoff potential can exactly describe the changes of bond length, bond angle and Voronoi clusters during the process of melting. Before melting, the length of the C–C bond, Si–Si bond and Si–C bond is 3.2, 3.2 and 1.9 A, respectively. The bond angle distributes near the tetrahedral bond angle 109°, and the Voronoi clusters are all (4 0 0 0) tetrahedron structures. After melting, the C–C bond and Si–Si bond are reduced, while the Si–C bond is almost unchanged. The range of bond angle distribution is wider than before, and most of the (4 0 0 0) structures turn into three-fold coordinated structures, (2 3 0 0), (0 6 0 0) and (2 2 2 0) structures. The simulation results clearl... read less E. F. Souza et al., “A Combined Experimental and Theoretical Study on the Formation of Crystalline Vanadium Nitride (VN) in Low Temperature through a Fully Solid-State Synthesis Route,” Journal of Physical Chemistry C. 2013. link Times cited: 30 Abstract: An efficient method of synthesis of the vanadium nitride (VN… read more Abstract: An efficient method of synthesis of the vanadium nitride (VN) at low temperature is evaluated, and a mechanism for the crystallization process is proposed in this paper. From the mixture of ammonium m-vanadate with guanidinium carbonate an intermediate, guanidinium m-vanadate (GmV), is produced. GmV decomposed and underwent interesting structural transformations with increasing temperatures. This process is studied by theoretical (periodic DFT calculations) and experimental (51V MAS NMR, XRD, FTIR, and elemental analysis) methods. It is proposed that GmV is first decomposed into reactive species, then through solid-state transformations it is converted into vanadium oxynitride (VOxN1–x) with varying stoichiometry, and, last, GmV transforms itself into crystalline NaCl-type structure vanadium nitride. The DFT calculations show that this transformation is energetically favorable, and the formation of a VOxN1–x solid solution is feasible. read less W. Wang, L. Niu, Y. Zhang, and E. Lin, “Tensile mechanical behaviors of cubic silicon carbide thin films,” Computational Materials Science. 2012. link Times cited: 19 W. Wang, L. Niu, and Y. Hou, “Topological modeling of amorphization in SiC nodal network structures using local rules,” Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms. 2012. link Times cited: 0 B. Haberl, “Structural Characterization of Amorphous Silicon.” 2012. link Times cited: 9 Abstract: The structure of amorphous silicon (a-Si) has attracted wide… read more Abstract: The structure of amorphous silicon (a-Si) has attracted wide interest over the recent decades. This substantial interest is twofold. Firstly, a-Si has many, highly significant, technological applications. Secondly, physically it is a fundamentally interesting material which has been regarded as a model system of a covalently bonded continuous random network (CRN). Such a CRN is a random network in which each atom has full four-fold coordination as the only specific structural feature. More recently, improvement of techniques has allowed greater insight into the structural properties of a-Si. Intriguing deviations, not only from the ideal CRN, but especially between different forms of a-Si have been observed. However, to date it remains unclear to what extent the formation method of a-Si influences its structural order. Another critically important parameter in the nature of a-Si is its thermal history. For example, a-Si formed by ion-implantation undergoes structural relaxation – or short-range ordering – upon thermal annealing to a new state that is close to an ideal CRN. It remains unclear however, if other forms of a-Si undergo structural relaxation to the same degree. Thus, despite its widespread use and decades of research, the exact nature of a-Si is still not fully understood and this thesis addresses this topic. Different forms of a-Si was prepared by deposition techniques, rapid quenching from the melt and solid-state amorphization. These different forms were investigated in their as-prepared state as well as in their thermally annealed. A combination of techniques was used, namely nanoindentation, electron-energy-loss spectroscopy, Raman microspectroscopy, electron diffraction and fluctuation electron microscopy. All forms of a-Si were first probed for their uniformity. Films prepared by plasma-enhanced chemical vapour deposition and by rapid quenching from the melt were found to contain voids and nanocrystals which prevented the study of their structural properties. More uniform films prepared by magnetron-sputtering, ion-implantation and the so-called pressure-induced (PI) a-Si however, were studied in depth for their structural properties. Each as-prepared form of a-Si was found to have a unique network with very different structural properties. The magnetron-sputtered a-Si was observed to have significant microstructure. The pure ion-implanted a-Si however, is free of such microstructure although some inhomogeneities are clearly present within the network. Interestingly, PI a-Si possesses very little order on the entire length-scale. Only uniform, pure forms of a-Si without any microstructure undergo structural relaxation upon annealing. In the case of the other forms of a-Si, the presence of voids and nanopores seems to prevent the formation of a more ideal CRN. Intriguingly, for the pure cases however, the structural relaxation results in essentially the same properties for both networks over the entire length-scale. These findings were used to build a framework for the understanding of the… read less K. Xue and L. Niu, “A crossover in the mechanical response of silicon carbide due to the accumulation of chemical disorder,” Journal of Applied Physics. 2010. link Times cited: 7 Abstract: Molecular dynamics simulations of nanoindentation of silicon… read more Abstract: Molecular dynamics simulations of nanoindentation of silicon carbide (SiC) with varying chemical disorder are carried out to investigate the variations in mechanical responses and mechanisms due to the accumulation of chemical disorder. A crossover of deformation mechanisms with increasing chemical disorder is revealed in light of the transition of indentation response (pressure-depth curves) changing from a series of equally spaced load drops to irregularly spaced and less pronounced fluctuations, then to numerous small oscillations. This crossover arises from the interplay between dislocation motions confined to ordered atomic layer fragments and atomic rearrangements localized in embedded chemical and/or topological disordered clusters. At the presence of chemical disorder, the outburst and complete propagation of dislocations dominating in 3C-SiC evolve into discontinuous motions of multiple branched dislocations which are likely to be prematurely trapped by chemical disordered clusters. The extension... read less K. Xue and L. Niu, “Understanding the changes in mechanical properties due to the crystalline-to-amorphization transition in SiC,” Journal of Applied Physics. 2009. link Times cited: 19 Abstract: Atomic-scale simulations of tensile testing are performed on… read more Abstract: Atomic-scale simulations of tensile testing are performed on a series of silicon carbide (SiC) with varying chemical disorder to investigate the changes in mechanical properties due to the accumulation of irradiation damage. The accumulation of chemical disorder, which drives the crystalline-to-amorphization (c-a) transition, plays a significant role on the variations of Young’s modulus and strength, but in different manners. Young’s modulus decreases almost linearly with increasing chemical disorder below some threshold (χ≡NC–C/NC–Si<∼0.54). However, strength exhibits abrupt substantial reduction with the presence of a slight chemical disorder (χ=0.045). Above the threshold, the degradations of Young’s modulus and strength tend to saturate, indicating the completion of c-a transition. The variations of the mechanical properties as a function of chemical disorder are closely correlated with the crossover from homogenous elastic deformation to localized plastic flow percolating through the system. The cros... read less Q. Cheng, H. Wu, Y. Wang, and X. Wang, “Atomistic simulations of shock waves in cubic silicon carbide,” Computational Materials Science. 2009. link Times cited: 8 K. Xue, L. Niu, and H.-ji Shi, “Effects of quench rates on the short- and medium-range orders of amorphous silicon carbide: A molecular-dynamics study,” Journal of Applied Physics. 2008. link Times cited: 20 Abstract: Amorphous silicon carbide (a-SiC) networks generated from me… read more Abstract: Amorphous silicon carbide (a-SiC) networks generated from melted SiC at various quench rates (from 1014 to 5×1011 K/s) are studied with Tersoff potential based molecular-dynamics simulations. With the decreasing quench rates, dramatic changes are observed in chemical order, as well as in its topological orders over both short and medium ranges. The corresponding modification of topological short-range order is manifested not only by improvement of the characteristic tetrahedral configuration, but also by variation in the spatial distributions of the homonuclear bonds. On the other hand, the corresponding development over medium range gives rise to a more compact and more homogeneous structure. The essential mechanisms determining the atomic arrangements on both length scales are further explored. It is reasonable to argue that chemical order, as a function of the quench rate, should be mainly responsible for the topological features of a-SiC. read less L. M. M. Mendoza, R. Valladares, and A. A. Valladares, “Simulating the structure of amorphous Si0.5C0.5 using Lin–Harris molecular dynamics,” Molecular Simulation. 2008. link Times cited: 3 Abstract: We have amorphised Si0.5C0.5 by ab initio generating random … read more Abstract: We have amorphised Si0.5C0.5 by ab initio generating random networks with the experimental density of 2.75 g/cm3. Two types of crystalline supercells were used at the start: one was a diamond-like periodic supercell of 64 atoms, containing 32 carbons and 32 silicons, chemically ordered, amorphised using Fast Structure®, and the other was an fcc crystalline periodic supercell with 108 atoms, 54 carbons and 54 silicons, chemically ordered, amorphised using DMol3 from the suite in Materials Studio 3.2®. The amorphisation is made by heating the periodic samples to just below the melting point (the undermelt–quench approach), and then cooling them down to 0 K. Then the structures are relaxed by annealing and quenching, and finally a geometry relaxation is carried out. Our simulations show that Cerius2 ® and Materials Studio 3.2 give equivalent results in general: atoms of one kind are almost completely surrounded by the atoms of the other kind. We also find that the two codes lead to total and partial radial distribution functions such that after weighting them with the corresponding experimental structure factors yield curves that are similar and comparable with experiment. Also C–C bonds with an average bond length of 1.35 Å are found. read less V. Ivashchenko, P. Turchi, and V. Shevchenko, “Simulations of indentation-induced phase transformations in crystalline and amorphous silicon,” Physical Review B. 2008. link Times cited: 19 Abstract: The pressure- and indentation-induced phase transformations … read more Abstract: The pressure- and indentation-induced phase transformations in crystalline $(cd)$ and amorphous $(a)$ silicon are studied by using molecular dynamics simulations based on the modified Tersoff potential. The $s{p}^{3}{s}^{\ensuremath{\star}}$ tight-binding scheme is employed to gain insight into the origin of the change in conductivity during nanoindentation. The Gibbs free energy calculations predict the following pressure-induced phase transitions: $cd\text{-Si}\ensuremath{\rightarrow}\ensuremath{\beta}\text{-tin}$ $\text{Si}(\ensuremath{\beta}\text{-Si})$ (11.4 GPa); $cd\text{-Si}\ensuremath{\rightarrow}\text{high}$ density amorphous phase (HDA) (22.5 GPa); $a\text{-Si}\ensuremath{\rightarrow}\ensuremath{\beta}\text{-Si}$ (2.5 GPa); $a\text{-Si}\ensuremath{\rightarrow}\text{HDA}$ (8.4 GPa). Simulations of nanoindentation of crystalline silicon reveal discontinuities in the load-displacement curves. In the loading curves of the $cd\text{-Si}$ (100) substrate, the pop-in is assigned to the appearance of the $\ensuremath{\beta}\text{-tin}$ Si phase. During unloading, the pop-out is due to the formation of a low-density amorphous phase $a\text{-Si}$. The $a\text{-Si}\ensuremath{\rightarrow}\text{HDA}$ transformation takes place during nanoindentation of $a\text{-Si}$ in loading regime. Upon unloading the $a\text{-Si}$ phase is preserved. The structural transformations in $cd\text{-Si}$ and $a\text{-Si}$ during nanoindentation are treated in terms of triaxial and uniaxial compressions of the respective bulk samples. A change in conductivity from semiconducting to metallic during nanoindentation of the $cd\text{-Si}$ (100) and $a\text{-Si}$ slabs is explained in terms of a transformation of the localized electronic states in the band gap region. The results are compared to those of available theoretical models and experiments. read less P. Mélinon, B. Masenelli, F. Tournus, and A. Pérez, “Playing with carbon and silicon at the nanoscale.,” Nature materials. 2007. link Times cited: 253 R. Devanathan, F. Gao, and W. J. Weber, “Atomistic modeling of amorphous silicon carbide using a bond-order potential,” Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms. 2007. link Times cited: 20 A. Moriani and F. Cleri, “Point-defect recombination efficiency at grain boundaries in irradiated SiC,” Physical Review B. 2006. link Times cited: 9 Abstract: We studied the atomic-scale mechanisms of radiation damage r… read more Abstract: We studied the atomic-scale mechanisms of radiation damage recovery, by molecular dynamics simulations of irradiation cascades in a $\ensuremath{\beta}\text{\ensuremath{-}}\mathrm{Si}\mathrm{C}$ model system, containing one general (001) twist grain boundary in the direction approximately perpendicular to the cascade. The (001) grain boundary has a disordered atomic structure, representative of high-angle, high-energy boundaries in cubic silicon carbide. Compared to the perfect crystal model system, we find a relevant effect of grain boundaries on the annealing of cascade defects, both in terms of localization of defects, which are preferentially concentrated around the grain boundary, and of relative defect recovery efficiency. In general, C interstitials are the prevalent type of defect over the whole range of energies explored. A slight grain boundary expansion is observed, accompanied by a broadening of the central atomic planes. read less S. Sorieul, J. Costantini, L. Gosmain, L. Thomé, and J. Grob, “Raman spectroscopy study of heavy-ion-irradiated α-SiC,” Journal of Physics: Condensed Matter. 2006. link Times cited: 166 Abstract: Raman spectroscopy was used to investigate the structure of … read more Abstract: Raman spectroscopy was used to investigate the structure of ion-irradiated α-SiC single crystals at room temperature and 400 °C. Irradiations induce a decrease of the Raman line intensities related to crystalline SiC, the appearance of several new Si–C vibration bands attributed to the breakdown of the Raman selection rules, and the formation of homonuclear bonds Si–Si and C–C within the SiC network. For low doses, the overall sp3 bond structure and the chemical order may be almost completely conserved. By contrast, the amorphous state shows a strong randomization of the Si–Si, Si–C and C–C bonds. The relative Raman intensity decreases exponentially versus increasing dose due to the absorption of the irradiated layer. The total disorder follows a sigmoidal curve, which is well fitted by the direct impact/defect stimulated model. The chemical disorder expressed as the ratio of C–C bonds to Si–C bonds increases exponentially versus the dose. A clear correlation is established between the total disorder and the chemical disorder. The increase of temperature allows the stabilization of a disordered/distorted state and a limitation of damage accumulation owing to the enhancement of the dynamic annealing. read less C. Ciobanu, A. Barbu, and R. Briggs, “Interactions of Carbon Atoms and Dimer Vacancies on the Si(001) Surface,” Journal of Engineering Materials and Technology-transactions of The Asme. 2005. link Times cited: 2 Abstract: We investigate the interactions between substitutional carbo… read more Abstract: We investigate the interactions between substitutional carbon atoms on the defect free, (2×1) reconstructed Si(001) surface, and bring evidence that the interaction energy differs significantly from the inverse-cube distance dependence that is predicted by the theory of force dipoles on an elastic half-space. Bused on Tersoff potentials, we also calculate the interactions between carbon atoms and dimer vacancies. The calculations indicate that dimer vacancies (DVs) are strongly stabilised by fourth-layer C atoms placed directly underneath them. By use of simple model Monte Carlo simulations, we show that the computed interactions between carbon atoms and DVs lead to self-assembled vacancy lines, in qualitative agreement with recent experimental results. read less V. Ivashchenko, P. Turchi, V. Shevchenko, L. A. Ivashchenko, and O. Shramko, “Simulations of pressure-induced phase transitions in amorphousSixC1−xalloys,” Physical Review B. 2005. link Times cited: 6 V. Ivashchenko, V. Shevchenko, L. A. Ivashchenko, and O. Porada, “The atomic pattern and electron structure of amorphous and microcrystalline sic,” Powder Metallurgy and Metal Ceramics. 2004. link Times cited: 2 J. Rino et al., “Short- and intermediate-range structural correlations in amorphous silicon carbide: a molecular dynamics study,” Physical Review B. 2004. link Times cited: 67 Abstract: Short- and intermediate-range structural correlations in amo… read more Abstract: Short- and intermediate-range structural correlations in amorphous silicon carbide $(\mathrm{a}\text{\ensuremath{-}}\mathrm{SiC})$ are studied in terms of partial pair distributions, bond angle distribution functions, and shortest-path ring statistics. A well relaxed sample is prepared following a slow annealing schedule of the simulation at the experimental density of the amorphous phase. The short-range correlation functions indicate a locally ordered amorphous structure with heteronuclear bonds, $\mathrm{Si}--\mathrm{C}$, with no phase separation, and no graphitic or diamond structures present. The bond distances and coordination numbers are similar to those in the crystalline phase. The rings statistics indicate an intermediate-range topology formed by the rearrangement of tetrahedra with the occurrence of corner and edge sharing units connecting two- ($\ensuremath{\sim}5%$ of total), three-, four-, and five-fold rings. The presence of large size rings indicates the existence of nano-voids in the structure, which explains the low density compared with the crystal phase while keeping the same coordination number and bond distance. These simulation results agree well with experimental results. read less M. Gastreich, J. Gale, and C. Marian, “Charged-particle potential for boron nitrides, silicon nitrides, and borosilazane ceramics: Derivation of parameters and probing of capabilities,” Physical Review B. 2003. link Times cited: 14 Abstract: A classical pair potential, augmented by three-body interact… read more Abstract: A classical pair potential, augmented by three-body interactions, for the modeling of borosilazane ceramics has been derived on the basis of both experimental and ah initio data. The primary goals were a good description of structural parameters and applicability in molecular dynamics. Furthermore, major challenges were to enable bond breaking and to avoid Coulomb collapse during simulations. This has been achieved by long-range, exponentially damped, analytical forms and the inclusion of short-range Coulomb tapering functions. We report on the fitting procedure, discuss the analytical forms employed, and demonstrate the abilities of the potential by comparing to ah initio calculations and experiments. read less A. C. Sparavigna, “Lattice thermal conductivity in cubic silicon carbide,” Physical Review B. 2002. link Times cited: 31 Abstract: The lattice thermal conductivity of cubic silicon carbide is… read more Abstract: The lattice thermal conductivity of cubic silicon carbide is evaluated by means of a microscopic model. considering the discrete nature of the lattice and its Brillouin zone for phonon dispersions and scattering mechanisms. The phonon Boltzmann equation is solved iteratively, with the three-phonon normal and umklapp collisions rigorously treated, avoiding relaxation-time approximations. Good agreement with the experimental data is obtained. Moreover, the role of point defects, such as antisites, on the lattice thermal conductivity is discussed. read less F. Finocchi, “Theoretical investigations of Si/C/N- based alloys.” 2002. link Times cited: 0 K. Albe, K. Nordlund, J. Nord, and A. Kuronen, “Modeling of compound semiconductors: Analytical bond-order potential for Ga, As, and GaAs,” Physical Review B. 2002. link Times cited: 151 Abstract: An analytical bond-order potential for GaAs is presented, th… read more Abstract: An analytical bond-order potential for GaAs is presented, that allows one to model a wide range of properties of GaAs compound structures, as well as the pure phases of gallium and arsenide, including nonequilibrium configurations. The functional form is based on the bond-order scheme as devised by Abell-Tersoff and Brenner, while a systematic fitting scheme starting from the Pauling relation is used for determining all adjustable parameters. Reference data were taken from experiments if available, or computed by self-consistent total-energy calculations within the local density-functional theory otherwise. For fitting the parameters, only structural data of the metallic phases of gallium and arsenide as well as those of different GaAs phases were used. A number of tests on point defect properties, surface properties, and melting behavior have been performed afterward in order to validate the accuracy and transferability of the potential model, but were not part of the fitting procedure. While point defect properties and surfaces with low As content are found to be in good agreement with literature data, the description of As-rich surface reconstructions is not satisfactory. In the case of molten GaAs we find support for a structural model based on experiment that indicates a polymerized arsenic phase in the melt. read less X. Yuan and L. Hobbs, “Modeling chemical and topological disorder in irradiation-amorphized silicon carbide,” Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms. 2002. link Times cited: 69 F. Gao and W. J. Weber, “Empirical potential approach for defect properties in 3C-SiC,” Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms. 2002. link Times cited: 92 N. Marks, “Modelling diamond-like carbon with the environment-dependent interaction potential,” Journal of Physics: Condensed Matter. 2002. link Times cited: 97 Abstract: The environment-dependent interaction potential is a transfe… read more Abstract: The environment-dependent interaction potential is a transferable empirical potential for carbon which is well suited for studying disordered systems. Ab initio data are used to motivate and parametrize the functional form, which includes environment-dependence in the pair and triple terms, and a generalized aspherical coordination describing dihedral rotation and non-bonded π-repulsion. Simulations of liquid carbon compare very favourably with Car-Parrinello calculations, while amorphous networks generated by liquid quench have properties superior to Tersoff, Brenner and orthogonal tight-binding calculations. The efficiency of the method enables the first simulations of tetrahedral amorphous carbon by deposition, and a new model for the formation of diamond-like bonding is presented. read less V. Ivashchenko, G. V. Rusakov, V. Shevchenko, A. Klymenko, L. A. Ivashchenko, and V. M. Popov, “Plausible interpretation of optical absorption spectra of a-SiC:H thin films,” Applied Surface Science. 2001. link Times cited: 3 V. Ivashchenko and V. Shevchenko, “Effects of short-range disorder upon electronic properties of a-SiC alloys,” Applied Surface Science. 2001. link Times cited: 13 C. Marian and M. Gastreich, “A systematic theoretical study of molecular Si/N, B/N, and Si/B/N(H) compounds and parameterisation of a force-field for molecules and solids,” Journal of Molecular Structure-theochem. 2000. link Times cited: 10 S. Knief and W. Niessen, “The electronic structure of amorphous silicon–carbon alloys,” Journal of Non-crystalline Solids. 1999. link Times cited: 8 M.-sook Lee and S. Bent, “Spectroscopic and thermal studies of a-SiC:H film growth: Comparison of mono-, tri-, and tetramethylsilane,” Journal of Vacuum Science and Technology. 1998. link Times cited: 28 Abstract: Thin a-SiC:H films were grown by hot-wire chemical vapor dep… read more Abstract: Thin a-SiC:H films were grown by hot-wire chemical vapor deposition at 200 K on Si(100) using mono-, tri-, and tetramethylsilane as single source precursors. The film structure and thermal reactivity were compared using in situ multiple internal reflection Fourier transform infrared spectroscopy and temperature programmed reaction/desorption. The results indicate that both mono- and trimethylsilane precursors yield films containing mixed silicon hydrides, SiHx (x=1–3), and mostly intact methyl groups. Tetramethylsilane did not lead to substantial film growth. These results are consistent with a mechanism for film growth involving Si–H bond cleavage. All the films are stable to above 550 K. By 600 K, silane and methylsilanes evolve, following the loss of terminal SiH3 and Si(CH3)xH3−x groups in the films. At higher temperatures, hydrogen desorption and hydrocarbon evolution are observed. For films grown with monomethylsilane, methane is the main hydrocarbon evolved, but films grown with trimethylsilane yie... read less P. Kelires and P. Denteneer, “Total-energy and entropy considerations as a probe of chemical order in amorphous silicon carbide,” Journal of Non-crystalline Solids. 1998. link Times cited: 13 R. Devanathan, T. D. Rubia, and W. J. Weber, “Displacement threshold energies in β-SiC,” Journal of Nuclear Materials. 1998. link Times cited: 141 G. Compagnini and G. Foti, “1430 cm−1 Raman line in ion implanted carbon rich amorphous silicon carbide,” Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms. 1997. link Times cited: 13 J. R. Bottin, P. Mccurdy, and E. R. Fisher, “A versatile substrate heater for thermal and plasma-enhanced chemical-vapor deposition,” Review of Scientific Instruments. 1997. link Times cited: 7 Abstract: A simple and inexpensive substrate heater that can be used i… read more Abstract: A simple and inexpensive substrate heater that can be used in both thermal- and plasma-enhanced chemical-vapor deposition (PECVD) systems has been constructed. This heater design can be used to achieve and sustain substrate temperatures as high as 650 °C with a minimal amount of outgassing under both CVD and PECVD conditions. Substrates are heated very quickly with all but the highest temperatures achieved within 30 min. The heater is also very robust, with a lifetime of more than 30 h of continuous use under vacuum with several heating and cooling cycles. We have used this heater design to thermally deposit TiS2 from 1-methyl-1-propanethiol and TiCl4 in the temperature range of 200–500 °C. In addition, amorphous hydrogenated silicon carbide (a-Si1−xCx:H) was deposited in the temperature range of 30–570 °C using a 13.56 MHz rf plasma reactor and a modified version of the same heater.A simple and inexpensive substrate heater that can be used in both thermal- and plasma-enhanced chemical-vapor deposition (PECVD) systems has been constructed. This heater design can be used to achieve and sustain substrate temperatures as high as 650 °C with a minimal amount of outgassing under both CVD and PECVD conditions. Substrates are heated very quickly with all but the highest temperatures achieved within 30 min. The heater is also very robust, with a lifetime of more than 30 h of continuous use under vacuum with several heating and cooling cycles. We have used this heater design to thermally deposit TiS2 from 1-methyl-1-propanethiol and TiCl4 in the temperature range of 200–500 °C. In addition, amorphous hydrogenated silicon carbide (a-Si1−xCx:H) was deposited in the temperature range of 30–570 °C using a 13.56 MHz rf plasma reactor and a modified version of the same heater. read less G. Ackland and G. Bonny, “Interatomic Potential Development,” Comprehensive Nuclear Materials. 2020. link Times cited: 4 H. N. Pishkenari and P. G. Ghanbari, “Vibrational analysis of the fullerene family using Tersoff potential,” Current Applied Physics. 2017. link Times cited: 11 R. Jones, C. Weinberger, S. Coleman, and G. Tucker, “Introduction to Atomistic Simulation Methods.” 2016. link Times cited: 1 G. Ackland, “1.10 – Interatomic Potential Development.” 2012. link Times cited: 10 H. Lan, Y. Wang, and C. Liu, “Simulations of structures of amorphous SixC1−x films,” Applied Surface Science. 2012. link Times cited: 0 R. Devanathan, F. Gao, and W. J. Weber, “Computer Simulation of Displacement Damage in Silicon Carbide,” MRS Proceedings. 2004. link Times cited: 2 V. Ivashchenko, P. Turchi, and V. Shevchenko, “A Tight-Binding Molecular-Dynamics Approach to Structural and Electronic Properties of a-SiC.” 2003. link Times cited: 0 X. Yuan and L. Hobbs, “Influence of Interatomic Potentials in MD Investigation of Ordering in a -SiC,” MRS Proceedings. 2000. link Times cited: 4 Abstract: Molecular dynamics (MD) simulations of a -SiC using several … read more Abstract: Molecular dynamics (MD) simulations of a -SiC using several Tersoff potentials have been performed and their influences on structure ordering were studied. It was found that using different potential cutoffs leads to remarkably different structures. An abrupt cutoff at 2.5 A greatly increases the chemical ordering of a -SiC by disfavoring the formation of Si-Si bonds. In addition, annealing of SiC cascades embedded in β-SiC was simulated, and the final structures were compared. Again, much stronger topological and chemical ordering was observed in the structure modeled with the 2.5 A potential cutoff. read less G. Compagnini and G. Foti, “The Effect of Bonding Disorder on the Vibrational Features of Amorphous Carbon Based Binary Alloys,” MRS Proceedings. 1997. link Times cited: 0 Y. Xie, J. Vandermause, S. Ramakers, N. Protik, A. Johansson, and B. Kozinsky, “Uncertainty-aware molecular dynamics from Bayesian active learning for phase transformations and thermal transport in SiC,” npj Computational Materials. 2022. link Times cited: 14 J. M. Ortiz-Roldán, F. Montero-Chacón, E. Garcia-Perez, S. Calero, A. R. Ruiz-Salvador, and S. Hamad, “Thermostructural Characterization of Silicon Carbide Nanocomposite Materials via Molecular Dynamics Simulations,” Advanced Composite Materials. 2021. link Times cited: 1 Abstract: In this paper, we investigate the thermostructural propertie… read more Abstract: In this paper, we investigate the thermostructural properties of a type of silicon-based nanomaterials, which we refer to as SiC@Si nanocomposites, formed by SiC crystalline nanoparticles (with the cubic phase), embedded within an amorphous Si matrix. We have followed an in silico approach to characterize the mechanical and thermal behaviour of these materials, by calculating the elastic constants, uniaxial stress-strain curves, coefficients of thermal expansion, and specific heats, at different temperatures, using interatomic potential calculations. The results obtained from our simulations suggest that this type of material presents enhanced thermal resistance features, making it suitable to be used in devices subjected to big temperature changes, such as heat sinks in micro and nanoelectronics, solar energy harvesters at high temperatures, power electronics, or in other applications in which good thermomechanical properties are required. read less N.-T. Do, V. Dinh, L. Lich, H.-H. Dang-Thi, and T. G. Nguyen, “Effects of Substrate Bias Voltage on Structure of Diamond-Like Carbon Films on AISI 316L Stainless Steel: A Molecular Dynamics Simulation Study,” Materials. 2021. link Times cited: 4 Abstract: With the recent significant advances in micro- and nanoscale… read more Abstract: With the recent significant advances in micro- and nanoscale fabrication techniques, deposition of diamond-like carbon films on stainless steel substrates has been experimentally achieved. However, the underlying mechanism for the formation of film microstructures has remained elusive. In this study, the growth processes of diamond-like carbon films on AISI 316L substrate are studied via the molecular dynamics method. Effects of substrate bias voltage on the structure properties and sp3 hybridization ratio are investigated. A diamond-like carbon film with a compact structure and smooth surface is obtained at 120 V bias voltage. Looser structures with high surface roughness are observed in films deposited under bias voltages of 0 V or 300 V. In addition, sp3 fraction increases with increasing substrate bias voltage from 0 V to 120 V, while an opposite trend is obtained when the bias voltage is further increased from 120 V to 300 V. The highest magnitude of sp3 fraction was about 48.5% at 120 V bias voltage. The dependence of sp3 fraction in carbon films on the substrate bias voltage achieves a high consistency within the experiment results. The mechanism for the dependence of diamond-like carbon structures on the substrate bias voltage is discussed as well. read less A. Kubo and Y. Umeno, “Machine-Learning-Based Atomistic Model Analysis on High-Temperature Compressive Creep Properties of Amorphous Silicon Carbide,” Materials. 2021. link Times cited: 5 Abstract: Ceramic matrix composites (CMCs) based on silicon carbide (S… read more Abstract: Ceramic matrix composites (CMCs) based on silicon carbide (SiC) are used for high-temperature applications such as the hot section in turbines. For such applications, the mechanical properties at a high temperature are essential for lifetime prediction and reliability design of SiC-based CMC components. We developed an interatomic potential function based on the artificial neural network (ANN) model for silicon-carbon systems aiming at investigation of high-temperature mechanical properties of SiC materials. We confirmed that the developed ANN potential function reproduces typical material properties of the single crystals of SiC, Si, and C consistent with first-principles calculations. We also validated applicability of the developed ANN potential to a simulation of an amorphous SiC through the analysis of the radial distribution function. The developed ANN potential was applied to a series of creep test for an amorphous SiC model, focusing on the amorphous phase, which is expected to be formed in the SiC-based composites. As a result, we observed two types of creep behavior due to different atomistic mechanisms depending on the strain rate. The evaluated activation energies are lower than the experimental values in literature. This result indicates that an amorphous region can play an important role in the creep process in SiC composites. read less A. Galashev, O. Rakhmanova, K. Katin, M. Maslov, and Y. Zaikov, “Effect of an Electric Field on a Lithium Ion in a Channel of the Doped Silicene–Graphite System,” Russian Journal of Physical Chemistry B. 2020. link Times cited: 0 B. Sun, W. Ouyang, J. Gu, C. Wang, J. Wang, and L. Mi, “Formation of Moiré superstructure of epitaxial graphene on Pt(111): A molecular dynamic simulation investigation,” Materials Chemistry and Physics. 2020. link Times cited: 5 A. Galashev and O. Rakhmanova, “Stability of a Two-Layer Silicene on a Nickel Substrate upon Intercalation of Graphite,” Glass Physics and Chemistry. 2020. link Times cited: 1 A. Galashev, O. Rakhmanova, and A. Isakov, “Molecular Dynamic Behavior of Lithium Atoms in a Flat Silicene Pore on a Copper Substrate,” Russian Journal of Physical Chemistry B. 2020. link Times cited: 3 A. Sarikov, A. Marzegalli, L. Barbisan, E. Scalise, F. Montalenti, and L. Miglio, “Molecular dynamics simulations of extended defects and their evolution in 3C–SiC by different potentials,” Modelling and Simulation in Materials Science and Engineering. 2019. link Times cited: 11 Abstract: An important issue in the technology of cubic SiC (3C–SiC) m… read more Abstract: An important issue in the technology of cubic SiC (3C–SiC) material for electronic device applications is to understand the behavior of extended defects such as partial dislocation complexes and stacking faults (SFs). Atomistic simulations using molecular dynamics (MD) are an efficient tool to tackle this issue for large systems at comparatively low computation cost. At this, proper choice of MD potential is imperative to ensure the reliability of the simulation predictions. In this work, we compare the evolution of extended defects in 3C–SiC obtained by MD simulations with Tersoff, analytical bond order, and Vashishta potentials. Key aspects of this evolution are considered including the dissociation of 60° perfect dislocations in pairs of 30° and 90° partials as well as the dependence of the partial dislocation velocity on the Burgers vector and the atomic composition of core. Tersoff potential has been found to be less appropriate in describing the dislocation behavior in 3C–SiC as compared to two other potentials, which in their turn provide qualitatively equivalent predictions. The Vashishta potential predicts much faster defect dynamics than the analytical bond order potential (ABOP). It can be applied therefore to describe the large-scale evolution of the dislocation systems and SFs. On the other hand, ABOP is more precise in predicting local atom arrangements and reconstructions of the dislocation core structures. In this respect, synergetic use of ABOP and Vashishta potential is suggested for the MD simulation study of the properties and evolution of extended defects in the 3C–SiC. read less H. Wang, J. Guilleminot, and C. Soize, “Modeling uncertainties in molecular dynamics simulations using a stochastic reduced-order basis,” Computer Methods in Applied Mechanics and Engineering. 2019. link Times cited: 14 J. Luo, A. Alateeqi, L. Liu, and T. Sinno, “Carbon solubility in liquid silicon: A computational analysis across empirical potentials.,” The Journal of chemical physics. 2019. link Times cited: 4 Abstract: The nucleation and growth of SiC precipitates in liquid sili… read more Abstract: The nucleation and growth of SiC precipitates in liquid silicon is important in the crystallization of silicon used for the photovoltaic industry. These processes depend strongly on the carbon concentration as well as the equilibrium solubility relative to the precipitate phase. Here, using a suite of statistical thermodynamic techniques, we calculate the solubility of carbon atoms in liquid silicon relative to the β-SiC phase. We employ several available empirical potentials to assess whether these potentials may reasonably be used to computationally analyze SiC precipitation. We find that some of the Tersoff-type potentials provide an excellent picture for carbon solubility in liquid silicon but, because of their severe silicon melting point overestimation, are limited to high temperatures where the carbon solubility is several percent, a value that is irrelevant for typical solidification conditions. Based on chemical potential calculations for pure silicon, we suggest that this well-known issue is confined to the description of the liquid phase and demonstrate that some recent potential models for silicon might address this weakness while preserving the excellent description of the carbon-silicon interaction found in the existing models. read less Y. Y. Zhang, M. Tang, Y. Cai, J. E, and S. Luo, “Deducing density and strength of nanocrystalline Ta and diamond under extreme conditions from X-ray diffraction.,” Journal of synchrotron radiation. 2019. link Times cited: 3 Abstract: In situ X-ray diffraction with advanced X-ray sources offers… read more Abstract: In situ X-ray diffraction with advanced X-ray sources offers unique opportunities for investigating materials properties under extreme conditions such as shock-wave loading. Here, Singh's theory for deducing high-pressure density and strength from two-dimensional (2D) diffraction patterns is rigorously examined with large-scale molecular dynamics simulations of isothermal compression and shock-wave compression. Two representative solids are explored: nanocrystalline Ta and diamond. Analysis of simulated 2D X-ray diffraction patterns is compared against direct molecular dynamics simulation results. Singh's method is highly accurate for density measurement (within 1%) and reasonable for strength measurement (within 10%), and can be used for such measurements on nanocrystalline and polycrystalline solids under extreme conditions (e.g. in the megabar regime). read less A. Leide, L. Hobbs, Z. Wang, D. Chen, L. Shao, and J. Li, “The role of chemical disorder and structural freedom in radiation-induced amorphization of silicon carbide deduced from electron spectroscopy and ab initio simulations,” Journal of Nuclear Materials. 2019. link Times cited: 12 D. Prasad and N. Mitra, “An atomistic study of phase transition in cubic diamond Si single crystal subjected to static compression,” Computational Materials Science. 2019. link Times cited: 7 B. Szpunar, L. Malakkal, J. Rahman, and J. Szpunar, “Atomistic modeling of thermo‐mechanical properties of cubic SiC,” Journal of the American Ceramic Society. 2018. link Times cited: 10 L. N. Abdulkadir, K. Abou-El-Hossein, A. I. Jumare, M. Liman, T. A. Olaniyan, and P. B. Odedeyi, “Review of molecular dynamics/experimental study of diamond-silicon behavior in nanoscale machining,” The International Journal of Advanced Manufacturing Technology. 2018. link Times cited: 38 L. N. Abdulkadir, K. Abou-El-Hossein, A. I. Jumare, M. Liman, T. A. Olaniyan, and P. B. Odedeyi, “Review of molecular dynamics/experimental study of diamond-silicon behavior in nanoscale machining,” The International Journal of Advanced Manufacturing Technology. 2018. link Times cited: 0 Y. Liu, Y. Liu, T. Ma, and J. Luo, “Atomic Scale Simulation on the Anti-Pressure and Friction Reduction Mechanisms of MoS2 Monolayer,” Materials. 2018. link Times cited: 9 Abstract: MoS2 nanosheets can be used as solid lubricants or additives… read more Abstract: MoS2 nanosheets can be used as solid lubricants or additives of lubricating oils to reduce friction and resist wear. However, the atomic scale mechanism still needs to be illustrated. Herein, molecular simulations on the indentation and scratching process of MoS2 monolayer supported by Pt(111) surface were conducted to study the anti-pressure and friction reduction mechanisms of the MoS2 monolayer. Three deformation stages of Pt-supported MoS2 monolayer were found during the indentation process: elastic deformation, plastic deformation and finally, complete rupture. The MoS2 monolayer showed an excellent friction reduction effect at the first two stages, as a result of enhanced load bearing capacity and reduced deformation degree of the substrate. Unlike graphene, rupture of the Pt-supported MoS2 monolayer was related primarily to out-of-plane compression of the monolayer. These results provide a new insight into the relationship between the mechanical properties and lubrication properties of 2D materials. read less Y. Liu, B. Li, and L. Kong, “Atomistic insights on the nanoscale single grain scratching mechanism of silicon carbide ceramic based on molecular dynamics simulation,” AIP Advances. 2018. link Times cited: 15 Abstract: The precision and crack-free surface of brittle silicon carb… read more Abstract: The precision and crack-free surface of brittle silicon carbide (SiC) ceramic was achieved in the nanoscale ductile grinding. However, the nanoscale scratching mechanism and the root causes of SiC ductile response, especially in the atomistic aspects, have not been fully understood yet. In this study, the SiC atomistic scale scratching mechanism was investigated by single diamond grain scratching simulation based on molecular dynamics. The results indicated that the ductile scratching process of SiC could be achieved in the nanoscale depth of cut through the phase transition to an amorphous structure with few hexagonal diamond structure. Furthermore, the silicon atoms in SiC could penetrate into diamond grain which may cause wear of diamond grain. It was further found out that the chip material in the front of grain flowed along the grain side surface to form the groove protrusion as the scratching speed increases. The higher scratching speed promoted more atoms to transfer into the amorphous structure an... read less S. Takamoto et al., “Atomistic mechanism of graphene growth on a SiC substrate: Large-scale molecular dynamics simulations based on a new charge-transfer bond-order type potential,” Physical Review B. 2018. link Times cited: 9 Abstract: Thermal decomposition of silicon carbide is a promising appr… read more Abstract: Thermal decomposition of silicon carbide is a promising approach for the fabrication of graphene. However, the atomistic growth mechanism of graphene remains unclear. This paper describes the development of a new charge-transfer interatomic potential. Carbon bonds with a wide variety of characteristics can be reproduced by the proposed vectorized bond-order term. Large-scale thermal decomposition simulation enables us to observe the continuous growth process of the multi-ring carbon structure. The annealing simulation reveals the atomistic process by which the multi-ring carbon structure is transformed to flat graphene involving only 6-membered rings. Also, it is found that the surface atoms of the silicon carbide substrate enhance the homogeneous graphene formation. read less W. Li, X. Yao, and X. Zhang, “Planar impacts on nanocrystalline SiC: a comparison of different potentials,” Journal of Materials Science. 2018. link Times cited: 14 J. Luo, A. Alateeqi, L. Liu, and T. Sinno, “Atomistic simulations of carbon diffusion and segregation in liquid silicon,” Journal of Applied Physics. 2017. link Times cited: 9 Abstract: The diffusivity of carbon atoms in liquid silicon and their … read more Abstract: The diffusivity of carbon atoms in liquid silicon and their equilibrium distribution between the silicon melt and crystal phases are key, but unfortunately not precisely known parameters for the global models of silicon solidification processes. In this study, we apply a suite of molecular simulation tools, driven by multiple empirical potential models, to compute diffusion and segregation coefficients of carbon at the silicon melting temperature. We generally find good consistency across the potential model predictions, although some exceptions are identified and discussed. We also find good agreement with the range of available experimental measurements of segregation coefficients. However, the carbon diffusion coefficients we compute are significantly lower than the values typically assumed in continuum models of impurity distribution. Overall, we show that currently available empirical potential models may be useful, at least semi-quantitatively, for studying carbon (and possibly other impurity) trans... read less F. Gayk, J. Ehrens, T. Heitmann, P. Vorndamme, A. Mrugalla, and J. Schnack, “Young’s moduli of carbon materials investigated by various classical molecular dynamics schemes,” Physica E-low-dimensional Systems & Nanostructures. 2017. link Times cited: 16 A. Galashev, K. Ivanichkina, A. Vorob’ev, and O. Rakhmanova, “Structure and stability of defective silicene on Ag(001) and Ag(111) substrates: A computer experiment,” Physics of the Solid State. 2017. link Times cited: 30 H. Ko, A. Kaczmarowski, I. Szlufarska, and D. Morgan, “Data for: Optimization of self-interstitial clusters in 3C-SiC with Genetic Algorithm.” 2017. link Times cited: 9 L. M. Mej’ia-Mendoza, M. Vald’ez-Gonz’alez, J. Muñiz, U. Santiago, A. K. Cuentas-Gallegos, and M. Robles, “A theoretical approach to the nanoporous phase diagram of carbon,” Carbon. 2017. link Times cited: 20 C. Deng, X. Yu, X. Huang, and N. Yang, “ENHANCEMENT OF INTERFACIAL THERMAL CONDUCTANCE OF SIC BY OVERLAPPED CARBON NANOTUBES AND INTERTUBE ATOMS.” 2016. link Times cited: 8 Abstract: We proposed a new way, adding intertube atoms, to enhance in… read more Abstract: We proposed a new way, adding intertube atoms, to enhance interfacial thermal conductance (ITC) between SiC-carbon nanotube (CNT) array structure. Non-equilibrium molecular dynamics method was used to study the ITC. The results show that the intertube atoms can significantly enhance the ITC. The dependence of ITC on both the temperature and the number of intertube atoms are shown. The mechanism is analyzed by calculating probability distributions of atomic forces and vibrational density of states. Our study may provide some guidance on enhancing the ITC of CNT-based composites. read less S. Chavoshi and X. Luo, “Molecular dynamics simulation study of deformation mechanisms in 3C-SiC during nanometric cutting at elevated temperatures,” Materials Science and Engineering A-structural Materials Properties Microstructure and Processing. 2016. link Times cited: 102 S. Bringuier, V. Manga, K. Runge, P. Deymier, and K. Muralidharan, “Grain boundary dynamics of SiC bicrystals under shear deformation,” Materials Science and Engineering A-structural Materials Properties Microstructure and Processing. 2015. link Times cited: 10 S. Goel, “The current understanding on the diamond machining of silicon carbide,” Journal of Physics D: Applied Physics. 2014. link Times cited: 139 Abstract: The Glenn Research Centre of NASA, USA (www.grc.nasa.gov/WWW… read more Abstract: The Glenn Research Centre of NASA, USA (www.grc.nasa.gov/WWW/SiC/, silicon carbide electronics) is in pursuit of realizing bulk manufacturing of silicon carbide (SiC), specifically by mechanical means. Single point diamond turning (SPDT) technology which employs diamond (the hardest naturally-occurring material realized to date) as a cutting tool to cut a workpiece is a highly productive manufacturing process. However, machining SiC using SPDT is a complex process and, while several experimental and analytical studies presented to date aid in the understanding of several critical processes of machining SiC, the current knowledge on the ductile behaviour of SiC is still sparse. This is due to a number of simultaneously occurring physical phenomena that may take place on multiple length and time scales. For example, nucleation of dislocation can take place at small inclusions that are of a few atoms in size and once nucleated, the interaction of these nucleations can manifest stresses on the micrometre length scales. The understanding of how these stresses manifest during fracture in the brittle range, or dislocations/phase transformations in the ductile range, is crucial to understanding the brittle–ductile transition in SiC. Furthermore, there is a need to incorporate an appropriate simulation-based approach in the manufacturing research on SiC, owing primarily to the number of uncertainties in the current experimental research that includes wear of the cutting tool, poor controllability of the nano-regime machining scale (effective thickness of cut), and coolant effects (interfacial phenomena between the tool, workpiece/chip and coolant), etc. In this review, these two problems are combined together to posit an improved understanding on the current theoretical knowledge on the SPDT of SiC obtained from molecular dynamics simulation. read less P. Mélinon, “SiC Cage Like Based Materials.” 2011. link Times cited: 4 Abstract: SiC is a compound of silicon and carbon with a chemical form… read more Abstract: SiC is a compound of silicon and carbon with a chemical formula SiC. Silicon carbide(SiC) as a material is the most promising for applications in which high-temperature, high-power, and high-frequency devices, catalyst support, high irradiation environments are needed. Naturally occurring SiC is found only in poor quantities that explains the considerable effort made in the industrial SiC engineering. At a first glad, silicon and carbide are close but a careful inspection reveals different properties leading to brothers at odds behavior. In well ordered stoichiometric compounds SiC adopts a tetrahedral bonding like observed in common semiconductors (zincblende and wurtzite are the most populars). The difference of electronegativities induces a ionicity which is not enough to promote NaCl or CsCl structures but enough to induce multipolar effects. These multipolar effects are responsible to the huge number of polytypes. This polytypism has numerous applications including quantum confinement effects and graphene engineering. In this chapter, special emphasis has been placed on the non stoichiometric compounds. Silicon architectures are based from sp3 or more dense packing while carbon architectures cover a large spread of hybridization from sp to sp3, the sp2 graphite-like being the stable structure in standard conditions. Whenwe gather silicon and carbon together one of the basic issue is: what is the winner? When silicon and carbon have the same concentration (called stoichiometric compound), the answer is trivial: "the sp3" lattice since both the elements share this hybridization in bulk phase. In rich silicon phases, the sp3 hybridization is also a natural way. However, a mystery remains when rich carbon compounds are synthesized. Silicon sp2 lattice is definitively unstable while carbon adopts this structure. One of the solution is the cage-like structure (the fullerenes belongs to this family) where the hybridization is intermediate between sp2 and sp3. Other exotic structures like buckydiamonds are also possible. Special architectures can be built from the elemental SiC cage-like bricks, most of them are not yet synthesized, few are experimentally reported in low quantity. However, these structures are promising as long the electronic structure is quite different from standard phase and offer new areas of research in fuel cells (catalysis and gas storage), superconductivity, thermoelectric, optical and electronic devices. . .Moreover, the cage like structure permits endohedrally doping opening the way of heavily doped semiconductors strain free. Assembling elemental bricks lead to zeolite-like structures. We review the properties of some of these structures and their potential applications. 2 read less K. Xue, L. Niu, and H.-ji Shi, “Mechanical Properties of Amorphous Silicon Carbide.” 2011. link Times cited: 8 Abstract: Excellent physical and chemical properties make silicon carb… read more Abstract: Excellent physical and chemical properties make silicon carbide (SiC) a prominent candidate for a variety of applications, including high-temperature, high-power, and high-frequency and optoelectronic devices, structural component in fusion reactors, cladding material for gas-cooled fission reactors, and an inert matrix for the transmutation of Pu(Katoh, Y. et al., 2007; Snead, L. L. et al., 2007). Different poly-types of SiC such as 3C, 6H of which 6H have been researched the most. There has been a considerable interest in fabricating 3C-SiC/6HSiC hetero p-n junction devices in recent years. Ion implantation is a critical technique to selectively introduce dopants for production of Si-based devices, since conventional methods, such as thermal diffusion of dopants, require extremely high temperatures for application to SiC. There is, however, a great challenge with ion implantation because it inevitably produces defects and lattice disorder, which not only deteriorate the transport properties of electrons and holes, but also inhibit electrical activation of the implanted dopants(Benyagoub, A., 2008; Bolse, W., 1999; Jiang, W. et al., 2009; Katoh, Y. et al., 2006). Meanwhile the swelling and mechanical properties of SiC subjected to desplacive neutron irradiation are of importance in nuclear applications. In such irradiations the most dramatic material and microstructural changes occur during irradiation at low temperatures. Specifically, at temperatures under 100 C volumetric swelling due to point defect induced strain has been seen to reach 3% for neutron irradiation doses of ~0.1-0.5. At these low temperatures, amorphization of the SiC is also possible, which would lead to a substantial volumetric expansion of ~15%, along with decreases in mechanical properties such as hardness and modulus(Snead, L. L. et al., 1992; Snead, L. L. et al., 1998; Snead, L. L., 2004; Weber, W. J. et al., 1998). Intensive experimental and theoretical efforts have been devoted to the dose and temperature dependence of the properties of irradiation-amorphized SiC (a-SiC)(Weber, W. J. et al., 1997). Heera et al. (Heera, V. et al., 1997) found that the amorphization of SiC induced by 2 MeV Si+ implantation is accompanied by a dramatic and homogeneous volume swelling until a critical dose level dependent on the temperature. Afterwards the volume tends to saturate and the density of a-SiC is about 12% less than that of the crystalline read less M. Daw, J. Lawson, and C. Bauschlicher, “Interatomic potentials for Zirconium Diboride and Hafnium Diboride,” Computational Materials Science. 2011. link Times cited: 19 A. A. Valladares et al., “New Approaches to the Computer Simulation of Amorphous Alloys: A Review,” Materials. 2011. link Times cited: 17 Abstract: In this work we review our new methods to computer generate … read more Abstract: In this work we review our new methods to computer generate amorphous atomic topologies of several binary alloys: SiH, SiN, CN; binary systems based on group IV elements like SiC; the GeSe2 chalcogenide; aluminum-based systems: AlN and AlSi, and the CuZr amorphous alloy. We use an ab initio approach based on density functionals and computationally thermally-randomized periodically-continued cells with at least 108 atoms. The computational thermal process to generate the amorphous alloys is the undermelt-quench approach, or one of its variants, that consists in linearly heating the samples to just below their melting (or liquidus) temperatures, and then linearly cooling them afterwards. These processes are carried out from initial crystalline conditions using short and long time steps. We find that a step four-times the default time step is adequate for most of the simulations. Radial distribution functions (partial and total) are calculated and compared whenever possible with experimental results, and the agreement is very good. For some materials we report studies of the effect of the topological disorder on their electronic and vibrational densities of states and on their optical properties. read less C. Qin, W. Hengan, W. Yu, and W. Xiu-xi, “Orientation and Rate Dependence of Wave Propagation in Shocked Beta-SiC from Atomistic Simulations,” Chinese Physics Letters. 2009. link Times cited: 1 Abstract: The orientation dependence of planar wave propagation in bet… read more Abstract: The orientation dependence of planar wave propagation in beta-SiC is studied via the molecular dynamics (MD) method. Simulations are implemented under impact loadings in four main crystal directions, i.e., (100), (110), (111), and (112). The dispersion of stress states in different directions increases with rising impact velocity, which implies the anisotropic characteristic of shock wave propagation for beta-SiC materials. We also obtain the Hugoniot relations between the shock wave velocity and the impact velocity, and find that the shock velocity falls into a plateau above a threshold of impact velocity. The shock velocity of the plateaux is dependent on the shock directions, while (111) and (112) can be regarded as equivalent directions as they almost reach the same plateau. A comparison between the atomic stress from MD and the stress from Rankine–Hugoniot jump conditions is also made, and it is found that they agree with each other very well. read less J. Kioseoglou, P. Komninou, and T. Karakostas, “Interatomic potential calculations of III(Al, In)–N planar defects with a III‐species environment approach,” physica status solidi (b). 2008. link Times cited: 22 Abstract: III–N compound semiconductors are nowadays widely used in el… read more Abstract: III–N compound semiconductors are nowadays widely used in electronic device technology. Due to the complexity of their structures planar and linear defects may have various atomic configurations. Since in the wurtzite structure of AlN and InN the second‐neighbor distance is very close to the stable “metallic” Al–Al and In–In distances respectively, a III‐species environment approach based on a Tersoff empirical bond order interatomic potential is developed in which the cut‐off distance for Al–Al and In–In interactions is tuned. In particular, the work is focused on two issues: the development of an approach for the calculation of defected structures in III‐nitrides and the application of this method on a series of planar defects in wurtzite structure. Various structural and energy‐related conclusions are drawn that are attributed to the complexity of the III–III metal type and N–N interactions in connection with the difference of the lattice parameters and the elastic constants. Molecular dynamic simulations are led to the conclusion that structural transformations may also occur. The Austerman–Gehman and Holt models for the inversion domain boundary (IDB) on the (10$ \bar 1 $0) plane are higher in energy than the IDB model of Northrup, Neugebauer, and Romano. The model of Blank et al. for the translation domain boundary (TDB) on the {1$ \bar 2 $10} plane is unstable with respect to Drum's model. The Austerman model for the IDB on the {1$ \bar 2 $10} plane is unstable with respect to the IDB* model appropriate for this plane. The Austerman {10$ \bar 1 $0} IDB model is recognized as a strong candidate, among the IDB atomic configurations. Moreover, models for IDBs on {10$ \bar 1 $0} planes in which the boundary plane intersects two bonds (type‐2 models) are less stable than models in which the boundary plane intersects one bond (type‐1 models), in all cases considered. It is confirmed that the III‐species environment approach describes the “wrong”‐bonded defect local configuration structures more realistically with respect to the standard approach. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim) read less T. Takeshita, “Analysis and location of antisite defects in polycrystalline SiC,” Journal of Applied Physics. 2008. link Times cited: 0 Abstract: Molecular dynamics simulations based on the empirical Tersof… read more Abstract: Molecular dynamics simulations based on the empirical Tersoff potential were performed to examine the structure of the polycrystalline SiC containing antisite defects. To locate the defects, two types of crystallites were used as a model of the grain in polycrystalline SiC: the model structure I contains the defects located randomly in the crystallite; the structure II contains the defects located only on the surface of the crystallite. As a result of calculating the lattice parameters, the strain in structure I is one to two orders larger than that in structure II. The comparison between the simulation results with experimental observations indicates that the carbon antisite defects are easily incorporated into the crystallites in C-rich polycrystalline SiC, whereas the silicon antisites are difficult to locate in the crystallites in Si-rich polycrystalline SiC. read less I. Szlufarska, R. Kalia, A. Nakano, and P. Vashishta, “A molecular dynamics study of nanoindentation of amorphous silicon carbide,” Journal of Applied Physics. 2007. link Times cited: 35 Abstract: Through molecular dynamics simulation of nanoindentation of … read more Abstract: Through molecular dynamics simulation of nanoindentation of amorphous a‐SiC, we have found a correlation between its atomic structure and the load-displacement (P‐h) curve. We show that a density profile of a‐SiC exhibits oscillations normal to the surface, analogous to liquid metal surfaces. Short-range P‐h response of a‐SiC is similar to that of crystalline 3C‐SiC, e.g., it shows a series of load drops associated with local rearrangements of atoms. However, the load drops are less pronounced than in 3C‐SiC due to lower critical stress required for rearrangement of local clusters of atoms. The nanoindentation damage is less localized than in 3C‐SiC. The maximum pressure under the indenter is 60% lower than in 3C‐SiC with the same system geometry. The onset of plastic deformation occurs at the depth of 0.5A, which is ∼25% of the corresponding value in 3C‐SiC. a‐SiC exhibits lower damping as compared to 3C‐SiC, which is reflected in the longer relaxation time of transient forces after each discrete indenta... read less J. Li, “Spectral Method for Thermal Conductivity Calculations,” Journal of Computer-Aided Materials Design. 2006. link Times cited: 6 P. Erhart and K. Albe, “Analytical potential for atomistic simulations of silicon, carbon, and silicon carbide,” Physical Review B. 2005. link Times cited: 462 Abstract: We present an analytical bond-order potential for silicon, c… read more Abstract: We present an analytical bond-order potential for silicon, carbon, and silicon carbide that has been optimized by a systematic fitting scheme. The functional form is adopted from a preceding work {\}Phys. Rev. B 65, 195124 (2002) and is built on three independently fitted potentials for Si-Si, C-C, and Si-C interaction. For elemental silicon and carbon, the potential perfectly reproduces elastic properties and agrees very well with first-principles results for high-pressure phases. The formation enthalpies of point defects are reasonably reproduced. In the case of silicon stuctural features of the melt agree nicely with data taken from literature. For silicon carbide the dimer as well as the solid phases B1, B2, and B3 were considered. Again, elastic properties are very well reproduced including internal relaxations under shear. Comparison with first-principles data on point defect formation enthalpies shows fair agreement. The successful validation of the potentials for configurations ranging from the molecular to the bulk regime indicates the transferability of the potential model and makes it a good choice for atomistic simulations that sample a large configuration space. read less J. Li, D. Liao, S. Yip, R. Najafabadi, and L. Ecker, “Force-based many-body interatomic potential for ZrC,” Journal of Applied Physics. 2003. link Times cited: 48 Abstract: A classical potential for ZrC is developed in the form of a … read more Abstract: A classical potential for ZrC is developed in the form of a modified second-moment approximation with emphasis on the strong directional dependence of the C–Zr interactions. The model has a minimal set of parameters, 4 for the pure metal and 6 for the cross interactions, which are fitted to the database of cohesive energies of B1–, B2–, and B3–ZrC, the heat of formation, and most importantly, the atomic force constants of B1–ZrC from first-principles calculations. The potential is then extensively tested against various physical properties, none of which were considered in the fitting. Finite temperature properties such as thermal expansion and melting point are in excellent agreement with experiments. We believe our model should be a good template for metallic ceramics. read less A. C. Sparavigna, “Role of nonpairwise interactions on phonon thermal transport,” Physical Review B. 2003. link Times cited: 15 Abstract: In this paper, the phonon system for a perfect silicon latti… read more Abstract: In this paper, the phonon system for a perfect silicon lattice is obtained by means of a model considering a phenomenological potential that includes both two- and three-body contributions. Phonon dispersions are discussed, and anharmonic contributions to the phonon Hamiltonian are evaluated. The model is compared with a model involving a pairwise potential, previously used by the author in the calculation of silicon thermal conductivity. The equation of motion is solved for both models, obtaining phonon dispersions practically indistinguishable and in good agreement with the experimental data. The role of nonpairwise interactions in phonon-phonon-scattering processes, relevant for the calculation of thermal conductivity, is then discussed. The thermal conductivity obtained with the present model including two- and three-body interactions has a good agreement with the experimental data, better than the one previously achieved with the model involving a central potential. read less V. Ivashchenko, “Atomic and electronic structure of a-SiC,” Semiconductor physics, quantum electronics and optoelectronics. 2002. link Times cited: 2 R. Devanathan, W. J. Weber, and F. Gao, “Atomic scale simulation of defect production in irradiated 3C-SiC,” Journal of Applied Physics. 2001. link Times cited: 207 Abstract: Molecular dynamics simulations using a modified Tersoff pote… read more Abstract: Molecular dynamics simulations using a modified Tersoff potential have been used to study the primary damage state and statistics of defect production in displacement cascades in 3C-SiC. Recoils with energies from 0.25 to 50 keV have been simulated at 300 K. The results indicate that: (1) the displacement threshold energy surface is highly anisotropic; (2) the dominant surviving defects are C interstitials and vacancies; (3) the defect production efficiency decreases with increasing recoil energy; (4) defect clusters are much smaller and more sparse compared to those reported in metals; and (5) a small fraction of the surviving defects are antisite defects. read less K. Moriguchi et al., “Nano-tube-like surface structure in graphite particles and its formation mechanism: A role in anodes of lithium-ion secondary batteries,” Journal of Applied Physics. 2000. link Times cited: 37 Abstract: Nano-structures on the surface of graphite based carbon part… read more Abstract: Nano-structures on the surface of graphite based carbon particles have been investigated by means of high resolution transmission electron microscopy. The surfaces consist of “closed-edge” structures in a similar manner as carbon nano-tube. That is, they are composed of coaxial carbon tubes consisting of adequate coupling of graphite layer edges. These graphite particles are chemically stable and, therefore, applicable for lithium-ion secondary battery anodes. Molecular dynamics simulations based on the Tersoff potential reveal that the vibrations of the graphite layers at the free edges play an important role in the formation of the closed-edge structures. In lithium-ion secondary batteries, Li ions can intrude into bulk carbon anodes through these closed-edge structures. In order to clarify this intrusion mechanism, we have studied the barrier potentials of Li intrusion through these closed edges using the first-principles cluster calculations. From electrochemical measurements, the carbon anodes compos... read less X. Hu, K. Albe, and R. Averback, “Molecular-dynamics simulations of energetic C60 impacts on (2×1)-(100) silicon,” Journal of Applied Physics. 2000. link Times cited: 10 Abstract: Single impacts of energetic C60 clusters on (2×1)-(100) sili… read more Abstract: Single impacts of energetic C60 clusters on (2×1)-(100) silicon substrates are studied by molecular-dynamics simulations. The role of impact energies and internal cluster energy are investigated in detail. Six different energy regimes can be identified at the end of the ballistic phase: At thermal energies below 20 eV the fullerene cages undergo elastic deformation, while impinging on the surface, and are mostly chemisorpted on top of the (2×1)-dimer rows. Between 20 and 100 eV the cage structure is preserved after the collision, but the cluster comes to rest within a few monolayers of the silicon surface. At energies of 100–500 eV the cluster partially decomposes and small coherent carbon caps are embedded in the surface. At higher energies up to 1.5 keV complete decomposition of the fullerene cluster occurs and an amorphous zone is formed in the subsurface area. At energies greater than approximately 1.5 keV craters form and above 6 keV sputtering becomes significant. In all cases the substrate temperat... read less V. Ivashchenko, V. Shevchenko, L. A. Ivashchenko, and G. V. Rusakov, “Deep gap states of a single vacancy in cubic SiC,” Journal of Physics: Condensed Matter. 1999. link Times cited: 4 Abstract: The character of relaxation of atoms around a vacancy in cub… read more Abstract: The character of relaxation of atoms around a vacancy in cubic silicon carbide is determined with the help of the empirical potential of Tersoff. The recursion method of Haydock and Nex is applied to calculate the density of states derived from atoms situated around the defect. The outward relaxation of the lattice surrounding a empty site is established. The lattice relaxation results in the shift of gap states toward the conduction band. Vacancy levels of carbon at 0.5 eV and silicon at 0.45 and 1.98 eV are revealed in the band gap. The obtained results are compared with the experimental ones and with the data of other calculations. The work shows the importance of taking into account the lattice relaxation in examining vacancy states in semiconducting compounds. read less K. Yasuda, J. Costantini, and G. Baldinozzi, “Radiation-Induced Effects on Material Properties of Ceramics: Mechanical and Dimensional Properties,” Comprehensive Nuclear Materials. 2020. link Times cited: 2 R. Alsayegh, “Vision-augmented molecular dynamics simulation of nanoindentation,” Journal of Nanomaterials. 2015. link Times cited: 7 Abstract: We present a user-friendly vision-augmented technique to car… read more Abstract: We present a user-friendly vision-augmented technique to carry out atomic simulation using hand gestures. The system is novel in its concept as it enables the user to directly manipulate the atomic structures on the screen, in 3D space using hand gestures, allowing the exploration and visualisation of molecular interactions at different relative conformations. The hand gestures are used to pick and place atoms on the screen allowing thereby the ease of carrying out molecular dynamics simulation in a more efficient way. The end result is that users with limited expertise in developing molecular structures can now do so easily and intuitively by the use of body gestures to interact with the simulator to study the system in question. The proposed system was tested by simulating the crystal anisotropy of crystalline silicon during nanoindentation. A long-range (Screened bond order) Tersoff potential energy function was used during the simulation which revealed the value of hardness and elastic modulus being similar to what has been found previously from the experiments. We anticipate that our proposed system will open up new horizons to the current methods on how an MD simulation is designed and executed. read less C. Jiang, D. Morgan, and I. Szlufarska, “Structures and stabilities of small carbon interstitial clusters in cubic silicon carbide,” Acta Materialia. 2014. link Times cited: 19
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_794973922560_000
Extended KIM ID The long form of the KIM ID including a human readable prefix (100 characters max), two underscores, and the Short KIM ID. Extended KIM IDs can only contain alpha-numeric characters (letters and digits) and underscores and must begin with a letter.	Tersoff_LAMMPS_Tersoff_1994_SiC__MO_794973922560_000
DOI	10.25950/2ecced5d https://doi.org/10.25950/2ecced5d https://commons.datacite.org/doi.org/10.25950/2ecced5d
KIM Item Type Specifies whether this is a Portable Model (software implementation of an interatomic model); Portable Model with parameter file (parameter file to be read in by a Model Driver); Model Driver (software implementation of an interatomic model that reads in parameters).	Portable Model using Model Driver Tersoff_LAMMPS__MD_077075034781_005
Driver	Tersoff_LAMMPS__MD_077075034781_005
KIM API Version	2.2
Potential Type	tersoff

Verification Check Dashboard

(Click here to learn more about Verification Checks)

Grade	Name	Category	Brief Description	Full Results	Aux File(s)
P All elements claimed by model are supported in at least one of the tested configurations.	vc-species-supported-as-stated	mandatory	The model supports all species it claims to support; see full description.	Results	Files
P Periodic boundary conditions were correctly supported for all configurations that the model was able to compute.	vc-periodicity-support	mandatory	Periodic boundary conditions are handled correctly; see full description.	Results	Files
P Model energy has permutation symmetry for all configurations the model was able to compute.	vc-permutation-symmetry	mandatory	Total energy and forces are unchanged when swapping atoms of the same species; see full description.	Results	Files
A The letter grade A was assigned because the normalized error in the computation was 3.74903e-10 compared with a machine precision of 2.22045e-16. The letter grade was based on 'score=log10(error/eps)', with ranges A=[0, 7.5], B=(7.5, 10.0], C=(10.0, 12.5], D=(12.5, 15.0), F>15.0. 'A' is the best grade, and 'F' indicates failure.	vc-forces-numerical-derivative	consistency	Forces computed by the model agree with numerical derivatives of the energy; see full description.	Results	Files
P The model is C^1 continuous. This means that the model has continuous energy and continuous first derivative.	vc-dimer-continuity-c1	informational	The energy versus separation relation of a pair of atoms is C1 continuous (i.e. the function and its first derivative are continuous); see full description.	Results	Files
P Model energy and forces are invariant with respect to rigid-body motion (translation and rotation) for all configurations the model was able to compute.	vc-objectivity	informational	Total energy is unchanged and forces transform correctly under rigid-body translation and rotation; see full description.	Results	Files
P Model energy has inversion symmetry for all configurations the model was able to compute.	vc-inversion-symmetry	informational	Total energy is unchanged and forces change sign when inverting a configuration through the origin; see full description.	Results	Files
P No memory leak detected.	vc-memory-leak	informational	The model code does not have memory leaks (i.e. it releases all allocated memory at the end); see full description.	Results	Files
P All threads give identical results for tested case. Model appears to be thread-safe.	vc-thread-safe	mandatory	The model returns the same energy and forces when computed in serial and when using parallel threads for a set of configurations. Note that this is not a guarantee of thread safety; see full description.	Results	Files
N/A Unable to perform verification check due to an error.	vc-unit-conversion	mandatory	The model is able to correctly convert its energy and/or forces to different unit sets; see full description.	Results	Files

This bar chart plot shows the mono-atomic body-centered cubic (bcc) lattice constant predicted by the current model (shown in the unique color) compared with the predictions for all other models in the OpenKIM Repository that support the species. The vertical bars show the average and standard deviation (one sigma) bounds for all model predictions. Graphs are generated for each species supported by the model.

Species: Si

Species: C

Cohesive Energy Graph

This graph shows the cohesive energy versus volume-per-atom for the current mode for four mono-atomic cubic phases (body-centered cubic (bcc), face-centered cubic (fcc), simple cubic (sc), and diamond). The curve with the lowest minimum is the ground state of the crystal if stable. (The crystal structure is enforced in these calculations, so the phase may not be stable.) Graphs are generated for each species supported by the model.

Species: Si

Species: C

Diamond Lattice Constant

This bar chart plot shows the mono-atomic face-centered diamond lattice constant predicted by the current model (shown in the unique color) compared with the predictions for all other models in the OpenKIM Repository that support the species. The vertical bars show the average and standard deviation (one sigma) bounds for all model predictions. Graphs are generated for each species supported by the model.

Species: Si

Species: C

Dislocation Core Energies

This graph shows the dislocation core energy of a cubic crystal at zero temperature and pressure for a specific set of dislocation core cutoff radii. After obtaining the total energy of the system from conjugate gradient minimizations, non-singular, isotropic and anisotropic elasticity are applied to obtain the dislocation core energy for each of these supercells with different dipole distances. Graphs are generated for each species supported by the model.

(No matching species)

FCC Elastic Constants

This bar chart plot shows the mono-atomic face-centered cubic (fcc) elastic constants predicted by the current model (shown in blue) compared with the predictions for all other models in the OpenKIM Repository that support the species. The vertical bars show the average and standard deviation (one sigma) bounds for all model predictions. Graphs are generated for each species supported by the model.

Species: Si

Species: C

FCC Lattice Constant

This bar chart plot shows the mono-atomic face-centered cubic (fcc) lattice constant predicted by the current model (shown in red) compared with the predictions for all other models in the OpenKIM Repository that support the species. The vertical bars show the average and standard deviation (one sigma) bounds for all model predictions. Graphs are generated for each species supported by the model.

Species: C

Species: Si

FCC Stacking Fault Energies

This bar chart plot shows the intrinsic and extrinsic stacking fault energies as well as the unstable stacking and unstable twinning energies for face-centered cubic (fcc) predicted by the current model (shown in blue) compared with the predictions for all other models in the OpenKIM Repository that support the species. The vertical bars show the average and standard deviation (one sigma) bounds for all model predictions. Graphs are generated for each species supported by the model.

(No matching species)

FCC Surface Energies

This bar chart plot shows the mono-atomic face-centered cubic (fcc) relaxed surface energies predicted by the current model (shown in blue) compared with the predictions for all other models in the OpenKIM Repository that support the species. The vertical bars show the average and standard deviation (one sigma) bounds for all model predictions. Graphs are generated for each species supported by the model.

(No matching species)

SC Lattice Constant

This bar chart plot shows the mono-atomic simple cubic (sc) lattice constant predicted by the current model (shown in the unique color) compared with the predictions for all other models in the OpenKIM Repository that support the species. The vertical bars show the average and standard deviation (one sigma) bounds for all model predictions. Graphs are generated for each species supported by the model.

Species: C

Species: Si

Cubic Crystal Basic Properties Table

Species: C

Species: Si

Tests

ClusterEnergyAndForces__TD_000043093022_003

Conjugate gradient relaxation of atomic cluster v003

Creators: Daniel S. Karls
Contributor: karls
Publication Year: 2019
DOI: https://doi.org/10.25950/b47dd4c4

Given an xyz file corresponding to a finite cluster of atoms, this Test Driver computes the total potential energy and atomic forces on the configuration. The positions are then relaxed using conjugate gradient minimization and the final positions and forces are recorded. These results are primarily of interest for training machine-learning algorithms.

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2013
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3789
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1528
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3760
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1491
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3809
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1826
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3591
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3720
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3770
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3849
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3998
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3968
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1491
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4048
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3779
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1528
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3959
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1826
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3720
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3750
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3799
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1826
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3809
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3968
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2775
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2745
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2795
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2646
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2795
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2013
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2944
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3949
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3849
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3043
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3760
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3899
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3949
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3899
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3998
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1826
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3760
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3770
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3770
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3799
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3660
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3770
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1528
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1975
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2765
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3988
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3829
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3909
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1826
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4008
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3392
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1975
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3929
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3392
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1342
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3849
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3660
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3591
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3779
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3799
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3919
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3581
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1379
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1379
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3750
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4048
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4048
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4078
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2087
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3998
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3829
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4048
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3740
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3730
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3839
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3839
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2087
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3521
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4177
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3988
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3899
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3779
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1975
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3770
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2013
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3630
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2735
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2984
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3929
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3620
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4028
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2534
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4048
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3740
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3988
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3660
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3819
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3750
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2125
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3799
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4008
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3909
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4297
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3740
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2125
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3770
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3939
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3133
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1416
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2984
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3869
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3968
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3998
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1938
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2576
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1826
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3809
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4058
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3779
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3620
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3909
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3034
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3760
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3750
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3740
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3600
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3809
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4068
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3571
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1454
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2199
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3968
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2013
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1528
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4287
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3929
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4048
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3819
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4167
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1491
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3929
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3710
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2087
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3700
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2805
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3103
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3839
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3043
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3541
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3630
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3869
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2087
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2274
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2013
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3760
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3889
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3581
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1975
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2125
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4197
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3849
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3770
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3720
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1938
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3760
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4118
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3889
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3879
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3919
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1528
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3819
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3978
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3949
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3899
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3909
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3591
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4038
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4177
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2013
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3521
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3471
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3779
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4008
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2162
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1454
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3879
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3809
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3959
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3770
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2125
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2236
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4207
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3521
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3581
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2087
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4048
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3799
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3561
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3779
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3978
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3879
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1491
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4058
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3262
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3998
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1454
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3829
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3680
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4028
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3750
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4058
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1975
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2675
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3770
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1826
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1938
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3929
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3909
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3929
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2236
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3043
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1938
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3879
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3949
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1826
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3889
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4078
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3700
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3879
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3779
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4187
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4048
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2013
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3819
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3929
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3899
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3173
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3521
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4088
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3909
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2934
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3959
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3899
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3650
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1938
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4058
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3690
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3899
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3740
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4257
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3998
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1826
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1938
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4028
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2236
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4207
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3929
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3322
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3968
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4038
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3978
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2087
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2311
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1528
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2013
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1454
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3949
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4028
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2825
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3809
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3879
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2013
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3978
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4138
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3581
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2087
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1826
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3720
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3899
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4098
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3849
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3899
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3909
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2199
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4078
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3879
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1975
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4376
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3978
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3939
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3620
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3551
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3939
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4038
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1826
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4028
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3859
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3919
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3819
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4068
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1491
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3879
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3779
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3968
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1826
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3879
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4098
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3869
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3680
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1938
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3760
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3859
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3819
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1938
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1826
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2964
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3968
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3839
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1938
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3809
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3799
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4187
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3014
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3750
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3949
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3829
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4128
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4207
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3939
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3859
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3839
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3849
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3342
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2236
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3491
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2087
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3690
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3770
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3849
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3700
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3750
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3919
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2125
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4078
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3879
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1826
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3869
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3690
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3710
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3650
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4058
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3978
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1491
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3600
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2385
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3988
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2013
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1528
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2914
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2904
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1975
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1975
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3879
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3899
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3968
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3650
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1603
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3929
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4118
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1528
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1454
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4048
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3730
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1677
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3770
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1528
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3690
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1826
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1454
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2460
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3829
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3312
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3710
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4048
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1975
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4108
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3949
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3630
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3710
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3889
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3819
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1528
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3650
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3939
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3978
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3869
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3949
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4068
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3919
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3541
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3959
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3789
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3750
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3610
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1901

CohesiveEnergyVsLatticeConstant__TD_554653289799_003

Cohesive energy versus lattice constant curve for monoatomic cubic lattices v003

Creators:
Contributor: karls
Publication Year: 2019
DOI: https://doi.org/10.25950/64cb38c5

This Test Driver uses LAMMPS to compute the cohesive energy of a given monoatomic cubic lattice (fcc, bcc, sc, or diamond) at a variety of lattice spacings. The lattice spacings range from a_min (=a_min_frac*a_0) to a_max (=a_max_frac*a_0) where a_0, a_min_frac, and a_max_frac are read from stdin (a_0 is typically approximately equal to the equilibrium lattice constant). The precise scaling and number of lattice spacings sampled between a_min and a_0 (a_0 and a_max) is specified by two additional parameters passed from stdin: N_lower and samplespacing_lower (N_upper and samplespacing_upper). Please see README.txt for further details.

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Cohesive energy versus lattice constant curve for bcc C v004	view	2636
Cohesive energy versus lattice constant curve for bcc Si v004	view	2477
Cohesive energy versus lattice constant curve for diamond C v004	view	2825
Cohesive energy versus lattice constant curve for diamond Si v004	view	2429
Cohesive energy versus lattice constant curve for fcc C v004	view	3092
Cohesive energy versus lattice constant curve for fcc Si v004	view	2397
Cohesive energy versus lattice constant curve for sc C v004	view	2775
Cohesive energy versus lattice constant curve for sc Si v004	view	2417

ElasticConstantsCrystal__TD_034002468289_000

Elastic constants for arbitrary crystals at zero temperature and pressure v000

Creators:
Contributor: ilia
Publication Year: 2024
DOI: https://doi.org/10.25950/888f9943

Computes the elastic constants for an arbitrary crystal. A robust computational protocol is used, attempting multiple methods and step sizes to achieve an acceptably low error in numerical differentiation and deviation from material symmetry. The crystal structure is specified using the AFLOW prototype designation as part of the Crystal Genome testing framework. In addition, the distance from the obtained elasticity tensor to the nearest isotropic tensor is computed.

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Elastic constants for CSi in AFLOW crystal prototype A2B_cP12_205_c_a at zero temperature and pressure v000		view	100860

ElasticConstantsCubic__TD_011862047401_006

Elastic constants for cubic crystals at zero temperature and pressure v006

Creators: Junhao Li and Ellad Tadmor
Contributor: tadmor
Publication Year: 2019
DOI: https://doi.org/10.25950/5853fb8f

Computes the cubic elastic constants for some common crystal types (fcc, bcc, sc, diamond) by calculating the hessian of the energy density with respect to strain. An estimate of the error associated with the numerical differentiation performed is reported.

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Elastic constants for bcc C at zero temperature v006	view	20015
Elastic constants for bcc Si at zero temperature v006	view	21066
Elastic constants for diamond C at zero temperature v001	view	36787
Elastic constants for diamond Si at zero temperature v001	view	15317
Elastic constants for fcc C at zero temperature v006	view	39173
Elastic constants for fcc Si at zero temperature v006	view	11508
Elastic constants for sc C at zero temperature v006	view	11229
Elastic constants for sc Si at zero temperature v006	view	3988

EquilibriumCrystalStructure__TD_457028483760_002

Equilibrium structure and energy for a crystal structure at zero temperature and pressure v002

Creators:
Contributor: ilia
Publication Year: 2024
DOI: https://doi.org/10.25950/2f2c4ad3

Computes the equilibrium crystal structure and energy for an arbitrary crystal at zero temperature and applied stress by performing symmetry-constrained relaxation. The crystal structure is specified using the AFLOW prototype designation. Multiple sets of free parameters corresponding to the crystal prototype may be specified as initial guesses for structure optimization. No guarantee is made regarding the stability of computed equilibria, nor that any are the ground state.

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype A2B_cP12_205_c_a v002	view	101523
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype A2B_tP6_131_i_e v002	view	59633
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cF136_227_aeg v002	view	2082798
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_cF16_227_c v002	view	213720
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_cF240_202_h2i v002	view	1375667
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cF4_225_a v002	view	91142
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_cF8_227_a v002	view	121547
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cF8_227_a v002	view	140910
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cI12_229_d v002	view	245230
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_cI16_206_c v002	view	82013
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cI16_206_c v002	view	57540
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_cI16_229_f v002	view	76740
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cI82_217_acgh v002	view	408125
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_cI8_214_a v002	view	106014
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_cP1_221_a v002	view	68909
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_cP20_221_gj v002	view	104394
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cP46_223_cik v002	view	205551
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP12_194_bc2f v002	view	79216
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP12_194_e2f v002	view	76271
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP16_194_e3f v002	view	69130
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP1_191_a v002	view	45448
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP2_191_c v002	view	118014
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP2_194_c v002	view	66479
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP40_191_hjmno v002	view	124713
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP4_194_bc v002	view	40345
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP4_194_f v002	view	62136
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP4_194_f v002	view	43929
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP58_164_2d3i3j v002	view	95332
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP68_194_ef2h2kl v002	view	118968
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP8_194_ef v002	view	42775
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hR10_166_5c v002	view	105351
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hR14_166_7c v002	view	77081
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hR2_166_c v002	view	51313
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hR4_166_2c v002	view	42410
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hR60_166_2h4i v002	view	455932
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hR8_148_cf v002	view	51221
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_mC164_15_e20f v002	view	450596
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_mC16_12_4i v002	view	52436
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_mC16_12_4i v002	view	81203
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_oC16_65_mn v002	view	269288
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_oC16_65_pq v002	view	109400
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_oC8_65_gh v002	view	56689
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_oC92_63_ce2f2g3h v002	view	315979
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_oF16_69_gh v002	view	142088
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_oI120_71_lmn6o v002	view	603688
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_oP16_62_4c v002	view	54380
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_tI4_141_a v002	view	60884
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_tI8_139_h v002	view	45570
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_tI8_139_h v002	view	43504
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_tP106_137_a5g4h v002	view	145642
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_cF8_216_a_c v002	view	78380
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_cF8_225_a_b v002	view	84516
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP10_156_2a2bc_2a2bc v002	view	73841
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP12_186_a2b_a2b v002	view	50005
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP16_186_a3b_a3b v002	view	78111
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP20_156_4a3b3c_4a3b3c v002	view	71211
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP28_156_5a5b4c_5a5b4c v002	view	113135
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP32_186_3a5b_3a5b v002	view	70725
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP36_156_8a5b5c_8a5b5c v002	view	126406
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP38_156_7a6b6c_7a6b6c v002	view	202824
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP42_156_7a7b7c_7a7b7c v002	view	124376
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP4_186_b_b v002	view	53651
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP54_156_9a9b9c_9a9b9c v002	view	133915
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP8_186_ab_ab v002	view	46603
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hR10_160_5a_5a v002	view	156149
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hR14_160_7a_7a v002	view	76193
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hR16_160_8a_8a v002	view	102774
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hR18_160_9a_9a v002	view	83423
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hR22_160_11a_11a v002	view	265476

LatticeConstant2DHexagonalEnergy__TD_034540307932_002

Cohesive energy and equilibrium lattice constant of hexagonal 2D crystalline layers v002

Creators: Ilia Nikiforov
Contributor: ilia
Publication Year: 2019
DOI: https://doi.org/10.25950/dd36239b

Given atomic species and structure type (graphene-like, 2H, or 1T) of a 2D hexagonal monolayer crystal, as well as an initial guess at the lattice spacing, this Test Driver calculates the equilibrium lattice spacing and cohesive energy using Polak-Ribiere conjugate gradient minimization in LAMMPS

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Cohesive energy and equilibrium lattice constant of graphene v002		view	932

LatticeConstantCubicEnergy__TD_475411767977_007

Equilibrium lattice constant and cohesive energy of a cubic lattice at zero temperature and pressure v007

Creators: Daniel S. Karls and Junhao Li
Contributor: karls
Publication Year: 2019
DOI: https://doi.org/10.25950/2765e3bf

Equilibrium lattice constant and cohesive energy of a cubic lattice at zero temperature and pressure.

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Equilibrium zero-temperature lattice constant for bcc C v007	view	10045
Equilibrium zero-temperature lattice constant for bcc Si v007	view	9399
Equilibrium zero-temperature lattice constant for diamond C v007	view	4324
Equilibrium zero-temperature lattice constant for diamond Si v007	view	9707
Equilibrium zero-temperature lattice constant for fcc C v007	view	3951
Equilibrium zero-temperature lattice constant for fcc Si v007	view	8842
Equilibrium zero-temperature lattice constant for sc C v007	view	5293
Equilibrium zero-temperature lattice constant for sc Si v007	view	8981

LinearThermalExpansionCoeffCubic__TD_522633393614_002

Linear thermal expansion coefficient of cubic crystal structures v002

Creators:
Contributor: mjwen
Publication Year: 2024
DOI: https://doi.org/10.25950/9d9822ec

This Test Driver uses LAMMPS to compute the linear thermal expansion coefficient at a finite temperature under a given pressure for a cubic lattice (fcc, bcc, sc, diamond) of a single given species.

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Linear thermal expansion coefficient of diamond C at 293.15 K under a pressure of 0 MPa v002		view	4549526
Linear thermal expansion coefficient of diamond Si at 293.15 K under a pressure of 0 MPa v002		view	1475649

TriclinicPBCEnergyAndForces__TD_892847239811_003

Potential energy and atomic forces of periodic, non-orthogonal cell of atoms v003

Creators: Daniel S. Karls
Contributor: karls
Publication Year: 2019
DOI: https://doi.org/10.25950/c3dca28e

Given an extended xyz file corresponding to a non-orthogonal periodic box of atoms, use LAMMPS to compute the total potential energy and atomic forces.

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1565
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1938
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2596
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1789
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2954
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1565
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3889
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1715
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1938
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1640
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1491
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1379
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	4108
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3899
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3541
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1715
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1640
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3998
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2013
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3949
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1603
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1416
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1975
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3113
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2125
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3770
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1752
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1565
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1603
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1789
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1715
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3710
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1640
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1603
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	4048
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1491
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1565
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1491
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3690
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1826
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1901
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2536
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2725
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3909
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1826
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3720
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2423
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3014
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1752
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1603
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1491
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2125
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1938
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3919
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1565
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1715
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1715
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1864
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1528
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1640
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	4118
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1752
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1603
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2013
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1640
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1715
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1826
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1864
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3630
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1789
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3352
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3909
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3839
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3043
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3859
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3968
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3819
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1826
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3859
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3978
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1603
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	4068
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3551
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	4118
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1491
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3789
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3740
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3879
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1826
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1826
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1901
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1752
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1789
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3899
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1454
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	2125
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3700
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1789
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3869
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3680
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1491
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	2745
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	2278
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	2387
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3551
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1752
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3859
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	2125
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1826
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1901
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3819
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1826
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3561
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1715
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1677
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3660
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1826
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1715
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3879
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3491
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1826
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1640
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1752
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3879
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1752
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1789
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	4307
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	2884
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1603
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1789
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	2914
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1864
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	4038
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3511
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1901
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1603
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1379
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1603
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3034
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3680
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1565
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1640
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1715
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3789
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3978
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1975
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1901
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	2050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1752
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3978
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1715
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3561
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	4297
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	4028
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	2685
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3302
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1938
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3819
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1640
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3789
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1864
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3829
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3869
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3919
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1826
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1305
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3919
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	4048
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	4048
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3720
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1901
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	2236
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1715
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3024
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	4088
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	2199
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	3829
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	3988
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1901
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	3720
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	3789
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	2311
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1677
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1901
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1677
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1901
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1565
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	2984
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1826
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1603
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	3809
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	3779
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	3949
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	3620
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1901
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	3799
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1752
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1789
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1454
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1603
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1640
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1826
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1826
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1975
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	3998
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	3909
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	3819
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	2775
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1752
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	3859
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	4008
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	2274
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	4028
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1491

VacancyFormationEnergyRelaxationVolume__TD_647413317626_001

Monovacancy formation energy and relaxation volume for cubic and hcp monoatomic crystals v001

Creators:
Contributor: efuem
Publication Year: 2023
DOI: https://doi.org/10.25950/fca89cea

Computes the monovacancy formation energy and relaxation volume for cubic and hcp monoatomic crystals.

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Monovacancy formation energy and relaxation volume for diamond Si		view	183978

VacancyFormationMigration__TD_554849987965_001

Vacancy formation and migration energies for cubic and hcp monoatomic crystals v001

Creators:
Contributor: efuem
Publication Year: 2023
DOI: https://doi.org/10.25950/c27ba3cd

Computes the monovacancy formation and migration energies for cubic and hcp monoatomic crystals.

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Vacancy formation and migration energy for diamond Si		view	3996636

Errors

EquilibriumCrystalStructure__TD_457028483760_000

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP12_194_bc2f v000	other	view
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP16_194_e3f v000	other	view
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP2_191_c v000	other	view
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP4_194_f v000	other	view
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hR2_166_c v000	other	view
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hR4_166_2c v000	other	view
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hR8_148_cf v000	other	view
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_oC16_65_mn v000	other	view
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_oC8_65_gh v000	other	view
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_oF16_69_gh v000	other	view
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_tP106_137_a5g4h v000	other	view

EquilibriumCrystalStructure__TD_457028483760_002

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_oC8_67_m v002	other	view

LatticeConstantHexagonalEnergy__TD_942334626465_005

Test	Error Categories	Link to Error page
Equilibrium lattice constants for hcp C v005	other	view
Equilibrium lattice constants for hcp Si v005	other	view

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1994_SiC.settings
1994_SiC.tersoff
CMakeLists.txt
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kimprovenance.edn
kimspec.edn

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Tersoff_LAMMPS_Tersoff_1994_SiC__MO_794973922560_000

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BCC Lattice Constant

Cohesive Energy Graph

Diamond Lattice Constant

Dislocation Core Energies

FCC Elastic Constants

FCC Lattice Constant

FCC Stacking Fault Energies

FCC Surface Energies

SC Lattice Constant

Cubic Crystal Basic Properties Table

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