Tersoff-style three-body potential for SiC developed by Tersoff (1990) v000

Jerry Tersoff

doi:10.25950/653e6833

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Tersoff_LAMMPS_Tersoff_1990_SiC__MO_444207127575_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 (1990) 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 parameterization of the Tersoff three-body potential for SiC focused on studying C interstitials in bulk Si. It has a sharp cutoff not suited for unconstrained simulations.
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/1990--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. Carbon defects and defect reactions in silicon. Phys Rev Lett [Internet]. 1990Apr;64(15):1757–60. Available from: https://link.aps.org/doi/10.1103/PhysRevLett.64.1757 doi:10.1103/PhysRevLett.64.1757 — (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 (1990) v000. OpenKIM; 2022. doi:10.25950/653e6833 [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. 134 Citations (26 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 . X. Dong and Y. Shin, “Multiscale Modeling for Predicting the Mechanical Properties of Silicon Carbide Ceramics,” Journal of the American Ceramic Society. 2016. link Times cited: 7 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 K. Yin, L. Shi, X.-N. Ma, Y. Zhong, M. Li, and X. He, “Thermal Conductivity of 3C/4H-SiC Nanowires by Molecular Dynamics Simulation,” Nanomaterials. 2023. link Times cited: 0 Abstract: Silicon carbide (SiC) is a promising material for thermoelec… read more Abstract: Silicon carbide (SiC) is a promising material for thermoelectric power generation. The characterization of thermal transport properties is essential to understanding their applications in thermoelectric devices. The existence of stacking faults, which originate from the “wrong” stacking sequences of Si–C bilayers, is a general feature of SiC. However, the effects of stacking faults on the thermal properties of SiC are not well understood. In this study, we evaluated the accuracy of Tersoff, MEAM, and GW potentials in describing the thermal transport of SiC. Additionally, the thermal conductivity of 3C/4H-SiC nanowires was investigated using non-equilibrium molecular dynamics simulations (NEMD). Our results show that thermal conductivity exhibits an increase and then saturation as the total lengths of the 3C/4H-SiC nanowires vary from 23.9 nm to 95.6 nm, showing the size effect of molecular dynamics simulations of the thermal conductivity. There is a minimum thermal conductivity, as a function of uniform period length, of the 3C/4H-SiC nanowires. However, the thermal conductivities of nanowires weakly depend on the gradient period lengths and the ratio of 3C/4H. Additionally, the thermal conductivity of 3C/4H-SiC nanowires decreases continuously from compressive strain to tensile strain. The reduction in thermal conductivity suggests that 3C/4H-SiC nanowires have potential applications in advanced thermoelectric devices. Our study provides insights into the thermal transport properties of SiC nanowires and can guide the development of SiC-based thermoelectric materials. read less Y. Chen, H. Liu, T. Gao, and H. Wei, “Simulation of the Irradiation Cascade Effect of 6H-SiC Based on Molecular Dynamics Principles,” Micromachines. 2023. link Times cited: 1 Abstract: When semiconductor materials are exposed to radiation fields… read more Abstract: When semiconductor materials are exposed to radiation fields, cascade collision effects may form between the radiation particles in the radiation field and the lattice atoms in the target material, creating irradiation defects that can lead to degradation or failure of the performance of the device. In fact, 6H-SiC is one of the typical materials for third-generation broadband semiconductors and has been widely used in many areas of intense radiation, such as deep space exploration. In this paper, the irradiation cascade effect between irradiated particles of different energies in the radiation and lattice atoms in 6H-SiC target materials is simulated based on the molecular dynamics analysis method, and images of the microscopic trajectory evolution of PKA and SKA are obtained. The recombination rates of the Frenkel pairs were calculated at PKA energies of 1 keV, 2 keV, 5 keV, and 10 keV. The relationship between the number of defects, the spatial distribution pattern of defects, and the clustering of defects in the irradiation cascade effect of 6H-SiC materials with time and the energy of PKA are investigated. The results show that the clusters are dominated by vacant clusters and are mainly distributed near the trajectories of the SKA. The number and size of vacant clusters, the number of Frenkel pairs, and the intensity of cascade collisions of SKAs are positively correlated with the magnitude of the energy of the PKA. The recombination rate of Frenkel pairs is negatively correlated with the magnitude of the energy of PKA. read less M. Tahani, E. Postek, L. Motevalizadeh, and T. Sadowski, “Effect of Vacancy Defect Content on the Interdiffusion of Cubic and Hexagonal SiC/Al Interfaces: A Molecular Dynamics Study,” Molecules. 2023. link Times cited: 5 Abstract: The mechanical properties of ceramic–metal nanocomposites ar… read more Abstract: The mechanical properties of ceramic–metal nanocomposites are greatly affected by the equivalent properties of the interface of materials. In this study, the effect of vacancy in SiC on the interdiffusion of SiC/Al interfaces is investigated using the molecular dynamics method. The SiC reinforcements exist in the whisker and particulate forms. To this end, cubic and hexagonal SiC lattice polytypes with the Si- and C-terminated interfaces with Al are considered as two samples of metal matrix nanocomposites. The average main and cross-interdiffusion coefficients are determined using a single diffusion couple for each system. The interdiffusion coefficients of the defective SiC/Al are compared with the defect-free SiC/Al system. The effects of temperature, annealing time, and vacancy on the self- and interdiffusion coefficients are investigated. It is found that the interdiffusion of Al in SiC increases with the increase in temperature, annealing time, and vacancy. read less M. Tahani, E. Postek, and T. Sadowski, “Molecular Dynamics Study of Interdiffusion for Cubic and Hexagonal SiC/Al Interfaces,” Crystals. 2022. link Times cited: 5 Abstract: The mechanical properties of the SiC/Al interface are crucia… read more Abstract: The mechanical properties of the SiC/Al interface are crucial in estimating the overall strength of this ceramic-metal composite. The present work investigates the interdiffusion at the SiC/Al interface using molecular dynamics simulations. One cubic and one hexagonal SiC with a higher probability of orientations in contact with Al are examined as two samples of metal-matrix nanocomposites with whisker and particulate reinforcements. These reinforcements with the Si- and C-terminated surfaces of the SiC/Al interfaces are also studied. The average main and cross-interdiffusion coefficients are evaluated using a single diffusion couple for each system. The effect of temperature and annealing time are analysed on the self- and interdiffusion coefficients. It is found that the diffusion of Al in SiC is similar in cubic and hexagonal SiC and as expected, the interdiffusion coefficient increases as the temperature and annealing time increase. The model after diffusion can be used to evaluate the overall mechanical properties of the interface region in future studies. read less Y. Yan, S. Zhou, and S. Liu, “Atomistic simulation on mechanical behaviors of Al/SiC nanocomposites,” 2017 18th International Conference on Electronic Packaging Technology (ICEPT). 2017. link Times cited: 4 Abstract: Molecular dynamics (MD) simulations were carried out to stud… read more Abstract: Molecular dynamics (MD) simulations were carried out to study the mechanical properties of co-continuous Al/SiC nanocomposites under tensile loading. Three cases of different models were implemented to investigate the influence of volume fraction (Vf) of SiC, thickness of SiC skeletons and shape of Al nanowire on the mechanical properties of the nanocomposites. It is found that the ultimate strength and Young's modulus of nanocomposites increase nonlinearly with the Vf of SiC, whereas the limit strains decrease with the increasing Vf of SiC. The Young's modulus obtained by MD simulations are in good agreement with the prediction by micromechanics methods and experimental results. In addition, the thickness of SiC skeletons and the shape of Al nanowire have a significant impact on the mechanical behaviors of co-continuous Al-SiC nanocomposites. This study on the mechanical properties of co-continuous Al-SiC nanocomposites will be helpful to further understanding the mechanical behaviors of the metal/ceramics co-continuous composites. read less 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 M. Backman et al., “Molecular dynamics simulations of swift heavy ion induced defect recovery in SiC,” Computational Materials Science. 2013. link Times cited: 77 V. Tomar, M. Gan, and H.-sung Kim, “Atomistic analyses of the effect of temperature and morphology on mechanical strength of Si–C–N and Si–C–O nanocomposites,” Journal of The European Ceramic Society. 2010. link Times cited: 31 V. Tomar, “Atomistic and Continuum Understanding of the Particle Clustering and Particle Size Effect on the Room and High Temperature Strength of SiC-Si 3 N 4 Nanocomposites.” 2010. link Times cited: 1 Abstract: Silicon carbide (SiC)-silicon nitride (Si3N4) nanocomposites… read more Abstract: Silicon carbide (SiC)-silicon nitride (Si3N4) nanocomposites are one of the most important high temperature materials. Factors that affect the strength of the SiC-Si3N4 nanocomposites can include the second phase SiC particle placement and clustering along Si3N4 GBs, the SiC particle size, Si3N4 grain size, and Si3N4 matrix morphology. This work presents recent work by our group in analyzing the effect of morphological variations in second phase SiC particle placement and GB strength on the room temperature fracture strength of SiC-Si3N4 nanocomposites using continuum analyses based on a mesoscale (~50 nm) cohesive finite element method (CFEM) and using molecular dynamics (MD) based analyses at nanoscale (~15 nm). The analyses have revealed that high strength and relatively small sized SiC particles act as stress concentration sites in Si3N4 matrix leading to inter-granular Si3N4 matrix cracking as a dominant nanocomposite failure mode under dynamic loading. At high SiC volume fractions that peak at approximately 30%, the CFEM analyses have revealed that due to a significant number of nano-sized SiC particles being present in micro-sized Si3N4 matrix, the SiC particles invariantly fall in the wake regions of microcracks leading to significant increase in fracture resistance. This finding was mechanistically confirmed in the room temperature MD analyses that revealed that particle clustering along the GBs was more effective than particles being placed on GBs in increasing the nanocomposite mechanical strength. The temperature dependent deformation mechanism is found to be a trade-off between the stress concentration caused by SiC particles and Si3N4-Si3N4 GB sliding. The temperature increase tends to work in favor of GB sliding leading to softening of structures. However, microstructural strength increases with increase in temperature when GBs are absent. read less 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 V. Tomar, “Multiscale Simulation of Dynamic Fracture in Polycrystalline SiC-Si 3N4 Using a Molecularly Motivated Cohesive Finite Element Method.” 2007. link Times cited: 0 Abstract: An advanced nanocomposite microstructure such as that of pol… read more Abstract: An advanced nanocomposite microstructure such as that of polycrystalline Silicon Carbide (SiC)-Silicon Nitride (Si3N4) nanocomposites contains multiple lengthscales with grain boundary (GB) thickness of the order of 50 nm, SiC particle sizes of the order of 200300 nm and Si3N4 grain sizes of the order of 0.8 to 1.5 μm. Recent developments in failure analyses of such materials focus on continuum calculations with an account of the corresponding atomistic deformation mechanisms. In the presented research one such analysis approach is applied to analyze continuum level deformation in polycrystalline SiCSi3N4 nanocomposites. The continuum bilinear cohesive law is motivated from the atomistic SiC-Si3N4 interfacial separation analyses. The cohesive finite element method (CFEM) based analyses of dynamic fracture at a loading rate of 2 m/sec in bi-modal SiC-Si3N4 nanocomposites with an explicit account of the multiple length scales associated with GBs, second phase (SiC particles), and the primary phase (Si3N4 matrix) are performed. For CFEM analyses bimodal polycrystalline SiC-Si3N4 nanocomposite structures are generated with grain sizes of Si3N4 in the range of 0.8 to 1.5 μm and SiC particle size varying between 200 nm and 300 nm. The volume fraction of the SiC phase is fixed at 30%. In order to analyze the effect of GBs each sample of SiC-Si3N4 nanocomposite has two corresponding meshes: one with finite element (FE) mesh resolving GBs and the other with FE mesh neglecting GBs. Since, a given unique set of phase morphology defining parameters (such as location of SiC particles, SiC or GB distribution etc.) corresponds to a multiple sets of morphologies, three different random sets of morphologies are used to characterize the material behavior corresponding to one unique set of phase morphology parameters. Analyses clearly show that the GBs have a strong effect on dynamic fracture in the nanocomposites. 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 S. Park et al., “Carbon incorporation pathways and lattice sites in Si1−yCy alloys grown on Si(001) by molecular-beam epitaxy,” Journal of Applied Physics. 2002. link Times cited: 11 Abstract: We use a combination of in situ and postdeposition experimen… read more Abstract: We use a combination of in situ and postdeposition experimental probes together with ab initio calculations of strain coefficients and formation energies associated with specific C configurations in the Si lattice to determine C incorporation pathways and lattice site distributions in fully coherent Si1−yCy alloy layers grown by molecular-beam epitaxy on Si(001) as a function of deposition temperature Ts (380 °C–680 °C) and C fraction y (0–0.026). Lattice strain and Raman spectroscopy measurements demonstrate that all C, irrespective of y, is incorporated into substitutional lattice sites in Si1−yCy(001) layers grown at Ts⩽480 °C. Increasing Ts⩾580 °C leads to strong C surface segregation, as shown by in situ angle-resolved x-ray photoelectron spectroscopy, yielding additional pathways for C incorporation. Photoluminescence measurements indicate that an increasing fraction of the incorporated C in the higher-temperature layers resides in dicarbon complexes. Reflection high-energy electron diffraction and ... read less S. Park, J. D’Arcy-Gall, D. Gall, young-Seok Kim, P. Desjardins, and J. Greene, “C lattice site distributions in metastable Ge1−yCy alloys grown on Ge(001) by molecular-beam epitaxy,” Journal of Applied Physics. 2002. link Times cited: 13 Abstract: Epitaxial metastable Ge1−yCy alloy layers with y⩽0.045 were … read more Abstract: Epitaxial metastable Ge1−yCy alloy layers with y⩽0.045 were grown on Ge(001) by solid-source molecular-beam epitaxy (MBE) at temperatures Ts=200–400 °C. Using calculated strain coefficients and measured layer strains obtained from high-resolution reciprocal lattice maps (HR-RLMs), we determine C lattice site distributions as a function of Ts and total C concentration y. HR-RLMs show that all as-deposited alloys are fully coherent with their substrates. Ge1−yCy(001) layers grown at Ts⩽350 °C are in a state of in-plane tension and contain C in substitutional sites, giving rise to tensile strain, as well as in nanocluster sites which induce negligible lattice strain. Ts=400 °C layers are strain neutral with negligible substitutional C incorporation. Increasing y and/or Ts leads to a decrease in substitutional C concentration, consistent with Raman spectroscopy results, with a corresponding increase in the C fraction incorporated in nanocluster sites. The latter suggests that nanocluster formation is kinetica... read less J. D’Arcy-Gall, D. Gall, I. Petrov, P. Desjardins, and J. Greene, “Quantitative C lattice site distributions in epitaxial Ge1−yCy/Ge(001) layers,” Journal of Applied Physics. 2001. link Times cited: 11 Abstract: Epitaxial metastable Ge1−yCy alloy layers with y⩽0.035 were … read more Abstract: Epitaxial metastable Ge1−yCy alloy layers with y⩽0.035 were grown on Ge(001) from hyperthermal Ge and C atomic beams at deposition temperatures Ts of 250 and 300 °C. The use of hyperthermal beams allows us to controllably vary the concentration of C incorporated as Ge–C split interstitials. Ge1−yCy layers grown with incident Ge-atom energy distributions corresponding to ⩽0.14 lattice displacement per incident atom (dpa) are in a state of in-plane tension and contain significant concentrations of C atoms incorporated in substitutional sites. Increasing the dpa to 0.24 yields layers in compression with C incorporated primarily as Ge–C split interstitials. Ab initio density functional calculations of the formation energies and strain coefficients associated with C atomic arrangements in Ge show that configurations containing multiple C atoms, referred to collectively as C nanoclusters, are energetically more favorable than substitutional C and Ge–C split interstitials and yield a nearly zero average strain. ... 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 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 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 P. Kelires, “Simulations of Carbon Containing Semiconductor Alloys:. Bonding, Strain Compensation, and Surface Structure,” International Journal of Modern Physics C. 1998. link Times cited: 19 Abstract: This paper reviews recent Monte Carlo simulations within the… read more Abstract: This paper reviews recent Monte Carlo simulations within the empirical potential approach, which give insights into fundamental aspects of the bulk and surface structure of group-IV semiconductor alloys containing carbon. We focus on the binary Si1-xCx and ternary Si1-x-yGexCy alloys strained on silicon substrates. The statistical treatment of these highly strained alloys is made possible by using the semigrand canonical ensemble. We describe here improvements in the algorithm which considerably speed up the method. We show that the identity switches, which are the basic ingredients in this statistical ensemble, must be accompanied by appropriate relaxations of nearest neighbors in order to reach "quasiequilibrium" in metastable systems with large size mismatch between the constituent atoms. This effectively lowers the high formation energies and large barriers for diffusion which make molecular dynamics methods impractical for this problem. The most important findings of our studies are: (a) The prediction of a repulsive Ge–C interaction and of a preferential C–C interaction in the lattice. (b) The prediction for significant deviations of the structural parameters and of the elastic constants from linearly interpolated values (Vegard's law). As a result, for a given amount of carbon, strain compensation is shown to be more drastic than previously thought. (c) Investigation of the surface problem shows that the competition between the reconstruction strain field and the preferential arrangement of carbon atoms leads to new complicated structural patterns. read less L. Porter, J. Li, and S. Yip, “Atomistic modeling of finite-temperature properties of β-SiC. I. Lattice vibrations, heat capacity, and thermal expansion,” Journal of Nuclear Materials. 1997. link Times cited: 84 S. Jain, H. Osten, B. Dietrich, and H. Rücker, “Growth and properties of strained Si1-x-yGexCy layers,” Semiconductor Science and Technology. 1995. link Times cited: 73 Abstract: Advances made in the growth and properties of CSi and CSiGe … read more Abstract: Advances made in the growth and properties of CSi and CSiGe pseudomorphic strained layers are reviewed. The solubility of C in Si is small (3.51017 atoms/cm3 near the melting point). However, high-quality strained layers of the alloys with considerably larger C concentrations have been grown using MBE, CVD and solid-phase epitaxy methods. A careful control of the growth rate and temperature is necessary to avoid formation of silicon carbide. In high-quality layers, most of the C atoms occupy lattice positions of the Si or SiGe host crystals and a substitutional alloy is formed although the equilibrium volume of C atoms is only 30% of that of Si. The formation and stability of alloys of atoms with large differences in size is a topic of fundamental interest. Experimental and theoretical investigations have focused on the microscopic structure of substitutional Si1-x-yGexCy alloys. C compensates the compressive strain produced by Ge in the pseudomorphic layers grown on a Si substrate. From Raman studies of the microscopic strain in substitutional Si1-x-yGexCy alloys it has been concluded that Si-Si bonds experience a considerable local deformation even in strain-compensated alloys. The pair interaction of substitutional C atoms in an Si lattice and the possibility of forming ordered alloys have been studied theoretically. It has been found that the interaction of pairs of substitutional C atoms is attractive for special atomic configurations. Information available on electronic properties is rather meagre. Recent theoretical work shows that the bandgap of the alloy should decrease with C concentration. Experiments to confirm this have not yet been performed. Using strain-compensated alloys it is possible to grow symmetrically strained superlattices without the need of growing buffer layers. Si1-x-yGexCy strained layers are likely to be very useful for passive applications such as buffer layers. Considerably more work is required to determine their utility for active device applications. read less H. Osten, “Carbon-containing heteroepitaxial silicon and silicon/germanium thin films on Si(001).” 2002. link Times cited: 1 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 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 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 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 A. Rohskopf, S. Wyant, K. Gordiz, H. R. Seyf, M. G. Muraleedharan, and A. Henry, “Fast & accurate interatomic potentials for describing thermal vibrations,” Computational Materials Science. 2020. link Times cited: 7 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 A. Platonenko, F. Gentile, F. Pascale, P. D’arco, and R. Dovesi, “Interstitial carbon defects in silicon. A quantum mechanical characterization through the infrared and Raman spectra,” Journal of Computational Chemistry. 2020. link Times cited: 1 Abstract: The Infrared (IR) and Raman spectra of various interstitial … read more Abstract: The Infrared (IR) and Raman spectra of various interstitial carbon defects in silicon are computed at the quantum mechanical level by using an all electron Gaussian type basis set, the hybrid B3LYP functional and the supercell approach, as implemented in the CRYSTAL code (Dovesi et al. J. Chem. Phys. 2020, 152, 204111). The list includes two 〈100〉 split interstitial IXY defects, namely ICC and ICSi, a couple of related defects that we indicate as IXIY, the so called CiCs0 in its A and B form, as well as SiCiSi and CsCiCs, in which the interstitial carbon atom is twofold coordinated. The second undergoes a large relaxation, and the final configuration is close to ICCCs. Geometries, relative stabilities, electronic, and vibrational properties are analysed. All these defects show characteristic features in their IR spectrum (above 730 cm−1), whereas the Raman spectrum is dominated, in most of the cases, by the pristine silicon peak at 530 cm−1, that hides the defect peaks. read less H. Wu, Q. Chen, N. Huang, X. Lian, and K. Li, “Evolution of hyperbranched polyglycerols as single-dopant carriers,” Colloids and Surfaces A: Physicochemical and Engineering Aspects. 2020. link Times cited: 3 X. Dong and Y. Shin, “Predictions of thermal conductivity and degradation of irradiated SiC/SiC composites by materials-genome-based multiscale modeling,” Journal of Nuclear Materials. 2018. link Times cited: 16 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 W. Lowe and J. Eapen, “Using Space-Time Correlations to Identify Transient Defects,” MRS Advances. 2018. link Times cited: 0 Abstract: Atomistic simulations are employed to investigate the dynami… read more Abstract: Atomistic simulations are employed to investigate the dynamical behavior of atoms in cubic silicon carbide (SiC) following a 5 keV radiation knock. Specifically, we have computed the time-resolved van Hove self-correlation function, G_s(r,t), separately for the silicon and carbon sub-lattices. Our goal is to probe the early radiation damage mechanisms using a dynamical methodology. The simulation results show that the carbon atoms engage in a dynamic hopping mechanism as the system recovers from the radiation knock. The silicon atoms, however, exhibit a strikingly different behaviour: the time variation of 4πr^2G_s(r,t) indicates a dynamic tension between the crystalline and disordered regions of the Si sub-lattice. The power-law tail of the 4πr^2G_s(r,t) correlation for silicon atoms suggests a scale-free self-organized critical (SOC) state – a possible precursor to the collapse of the Si sub-lattice. read less X. Dong and Y. Shin, “Multi-scale modeling of thermal conductivity of SiC-reinforced aluminum metal matrix composite,” Journal of Composite Materials. 2017. link Times cited: 9 Abstract: High thermal conductivity is one important factor in the sel… read more Abstract: High thermal conductivity is one important factor in the selection or development of ceramics or composite materials. Predicting the thermal conductivity would be useful to the design and application of such materials. In this paper, a multi-scale model is developed to predict the effective thermal conductivity in SiC particle-reinforced aluminum metal matrix composite. A coupled two-temperature molecular dynamics model is used to calculate the thermal conductivity of the Al/SiC interface. The electronic effects on the interfacial thermal conductivity are studied. A homogenized finite element model with embedded thin interfacial elements is used to predict the properties of bulk materials, considering the microstructure. The effects of temperatures, SiC particle sizes, and volume fractions on the thermal conductivity are also studied. A good agreement is found between prediction results and experimental measurements. The successful prediction of thermal conductivity could help a better understanding and an improvement of thermal transport within composites and ceramics. read less 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 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 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 D. Simeone, J. Costantini, L. Lunéville, L. Desgranges, P. Trocellier, and P. Garcia, “Characterization of radiation damage in ceramics: Old challenge new issues?,” Journal of Materials Research. 2015. link Times cited: 19 Abstract: This work is an overview of the physical approaches required… read more Abstract: This work is an overview of the physical approaches required for characterizing and understanding the long-term evolution of ceramics under irradiation. Because this subject is complex and has many ramifications, we have chosen to address the problem by looking at the behavior of a number of key ceramics. In the first part of this work, we present the physical mechanisms responsible for the production of primary defects, pointing out the main differences between metals, semiconductors, and insulators. In part two, we attempt to show how devoted experimental techniques can combine with transmission electron microscopy and x-ray techniques to provide a clearer picture of the long-term evolution of the microstructure of ceramics under irradiation. The last part of this work is devoted to discussing different approaches to explain and describe the long-term behavior of irradiated ceramics. read less C. A. Londos, E. Sgourou, D. J. Hall, A. Chroneos, and A. Chroneos, “Vacancy-oxygen defects in silicon: the impact of isovalent doping,” Journal of Materials Science: Materials in Electronics. 2014. link Times cited: 22 W. J. Lee et al., “The effect of structural and chemical bonding changes on the optical properties of Si/Si1−xCx core/shell nanowires,” Journal of Materials Chemistry C. 2013. link Times cited: 2 Abstract: Si/Si1−xCx core/shell nanowires (CS NWs) were synthesized. F… read more Abstract: Si/Si1−xCx core/shell nanowires (CS NWs) were synthesized. First, a Si NW was grown via a Vapor–Liquid–Solid (VLS) procedure using Au as a catalyst. Next, a Si1−xCx shell was deposited by a chemical vapor deposition (CVD) method after the removal of the Au tip at the top of the Si NW. We investigated the physical, chemical, and optical properties of the Si/Si1−xCx CS NWs as a function of annealing temperature. The Si1−xCx shell was initially deposited on the Si core with small clusters of an amorphous state, which were remarkably transformed into larger clusters by recrystallization after annealing under vacuum. To relieve the strain induced by the huge difference between the atomic sizes of Si and C, substitutionally incorporated C atoms can combine with another C atom at the third-nearest-neighbor distance in the Si1−xCx shell with increasing annealing temperature. Furthermore, the THz pulse emitted from the Si/Si1−xCx CS NWs was observed and analyzed. In the case of annealing treatment at 600 °C, the THz pulse intensity was substantially increased, which is not ascribed to Drude absorption but to mid-IR absorption. Moreover, based on the simulation results, we suggest that the existence of substitutional C atoms and control of the shell thickness is a viable method to enhance the THz pulse amplitude. read less A. Gheribi and P. Chartrand, “Application of the CALPHAD method to predict the thermal conductivity in dielectric and semiconductor crystals,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2012. link Times cited: 41 J.-Y. Li, C. Huang, and J. Sturm, “The effect of hydrogen on the surface segregation of phosphorus in epitaxially grown relaxed Si0.7Ge0.3 films by rapid thermal chemical vapor deposition,” Applied Physics Letters. 2012. link Times cited: 7 Abstract: The surface segregation of phosphorus in relaxed Si0.7Ge0.3 … read more Abstract: The surface segregation of phosphorus in relaxed Si0.7Ge0.3 epitaxial films grown on Si (100) substrates by rapid thermal chemical vapor deposition was investigated in this letter. The effect of the growth temperature on phosphorus segregation was studied experimentally and examined using a two-state model. As the growth temperature is reduced, phosphorus segregation is greatly suppressed, and we report an extremely sharp phosphorus turn-off slope of 6 nm/dec at 500 °C. The sharper slopes at low temperatures are explained by a modified two-state model which includes the effect of increased surface coverage of hydrogen at low temperatures. read less L. Briquet et al., “Reactive force field potential for carbon deposition on silicon surfaces,” Journal of Physics: Condensed Matter. 2012. link Times cited: 16 Abstract: In this paper a new interatomic potential based on the Kieff… read more Abstract: In this paper a new interatomic potential based on the Kieffer force field and designed to perform molecular dynamics (MD) simulations of carbon deposition on silicon surfaces is implemented. This potential is a third-order reactive force field that includes a dynamic charge transfer and allows for the formation and breaking of bonds. The parameters for Si–C and C–C interactions are optimized using a genetic algorithm. The quality of the potential is tested on its ability to model silicon carbide and diamond physical properties as well as the formation energies of point defects. Furthermore, MD simulations of carbon deposition on reconstructed (100) silicon surfaces are carried out and compared to similar simulations using a Tersoff-like bond order potential. Simulations with both potentials produce similar results showing the ability to extend the use of the Kieffer potential to deposition studies. The investigation reveals the presence of a channelling effect when depositing the carbon at 45° incidence angle. This effect is due to channels running in directions symmetrically equivalent to the (110) direction. The channelling is observed to a lesser extent for carbon atoms with 30° and 60° incidence angles relative to the surface normal. On a pristine silicon surface, sticking coefficients were found to vary between 100 and 73%, depending on deposition conditions. read less A. Doçaj and S. Estreicher, “Three carbon pairs in Si,” Physica B-condensed Matter. 2012. link Times cited: 13 V. Tomar and M. Gan, “Temperature dependent nanomechanics of Si–C–N nanocomposites with an account of particle clustering and grain boundaries,” International Journal of Hydrogen Energy. 2011. link Times cited: 11 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 A. Chroneos, B. Uberuaga, and R. Grimes, “Carbon, dopant, and vacancy interactions in germanium,” Journal of Applied Physics. 2007. link Times cited: 73 Abstract: Electronic structure calculations have been used to study th… read more Abstract: Electronic structure calculations have been used to study the interaction of carbon with isolated substitutional dopants (boron, phosphorus, or arsenic), vacancies, and dopant-vacancy pairs in germanium. For comparison, equivalent defects were examined in silicon. The calculations employed a plane-wave basis set and pseudopotentials within the generalized gradient approximation of density functional theory. The results predict a range of different association preferences, with carbon being strongly bound in some cases and unbound in others. For example, in germanium, the carbon-vacancy cluster is weakly bound whereas in silicon it is more strongly bound. Conversely, dopant-carbon pairs are not stable in either germanium or silicon compared to their isolated components. If, however, they are formed during implantation, they will act as strong vacancy traps. Details of clusters comprised of a dopant, carbon, and vacancy are also discussed with respect to their formation by the association of a vacancy or cl... read less A. Chroneos, “Isovalent impurity‐vacancy complexes in germanium,” physica status solidi (b). 2007. link Times cited: 53 Abstract: Electronic structure simulations are used to predict the str… read more Abstract: Electronic structure simulations are used to predict the structures and relative energies of clusters formed between isovalent impurities and lattice vacancies in germanium and for comparison in silicon. The structures and relative energies of a series of different carbon‐vacancy complexes in germanium are considered. The technique is also used to predict the effect of carbon atoms on the binding of tin‐vacancy pairs in germanium. For germanium and silicon different configurations containing carbon, tin and vacancies are stable. The calculations highlight important differences in the stability of clusters in germanium compared to silicon. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim) 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 Q. Lu and B. Bhattacharya, “The role of atomistic simulations in probing the small-scale aspects of fracture—a case study on a single-walled carbon nanotube,” Engineering Fracture Mechanics. 2005. link Times cited: 71 S. Kapur, M. Prasad, and T. Sinno, “Carbon-Mediated Aggregation of Self-Interstitials in Silicon.” 2004. link Times cited: 12 Abstract: The carbon-mediated aggregation of silicon self-interstitial… read more Abstract: The carbon-mediated aggregation of silicon self-interstitials is investigated with large-scale parallel molecular dynamics. The presence of carbon in the silicon matrix is shown to lead to concentration-dependent self-interstitial cluster pinning, dramatically reducing cluster coalescence and thereby inhibiting the nucleation process. The extent of cluster pinning increases with cluster size for the range of cluster sizes observed in the simulation. The direct effect of carbon on single self-interstitials is shown to be of secondary importance, and the concentration of single self-interstitials as a function of time is essentially unchanged in the presence of carbon. A quasi-single-component mean-field interpretation of the atomistic simulation results is proposed and further confirms these conclusions. Based on these results, it is suggested that the experimentally observed effect of carbon on transient-enhanced diffusion of boron could be due to the direct interaction between carbon atoms and self-interstitial clusters. read less C. A. Londos, M. Potsidi, and E. Stakakis, “Carbon-related complexes in neutron-irradiated silicon,” Physica B-condensed Matter. 2003. link Times cited: 29 D. J. Lockwood, H. Xu, and J. Baribeau, “Lattice vibrations of Si1-xCx epilayers on Si(100),” Physical Review B. 2003. link Times cited: 12 Abstract: Raman spectroscopy has been used to investigate the lattice … read more Abstract: Raman spectroscopy has been used to investigate the lattice vibrations of Si 1 - x C x (0read less A. Mattoni, F. Bernardini, and L. Colombo, “Self-interstitial trapping by carbon complexes in crystalline silicon,” Physical Review B. 2002. link Times cited: 42 Abstract: By combining model-potential molecular-dynamics simulations … read more Abstract: By combining model-potential molecular-dynamics simulations and ab initio calculations we investigate the microscopic mechanism of silicon trapping by carbon substitutional defects (C S ). We find that, upon silicon trapping, carbon is converted into an interstitial mobile complex (C l by an efficient exothermic reaction. Interstitial carbon C I may further interact either with another C S , forming the well-known C I C S dicarbon complex, or with extra silicon and carbon interstitials. In particular, we identify and characterize two structures, namely, C I I and C I C I . They are found energetically stable so that they could play a crucial role in the process of carbon aggregation. According to our calculations C I C I may be formed by the interaction of one I with a C I C S , proving that the latter is not a deactivated trap for interstitials. Our results further suggest that C I I and C I C I are seeds for further carbon aggregation. 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 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 A. Serra, “Atomic computer simulation: Large scale calculations of defect properties by empirical potentials,” Physica Status Solidi B-basic Solid State Physics. 2001. link Times cited: 2 Abstract: This paper is aimed at introducing computer simulation of ex… read more Abstract: This paper is aimed at introducing computer simulation of extended defects in crystalline materials by means of empirical potentials. In this context we understand by large scale calculations those related to a number of atoms from 10 3 to 10 6 and/or a time scale of few nanoseconds (10 2 -10 4 ps) for the evolution of the processes studied. read less X. Zhu, S. Lee, J. Y. Kim, Y. H. Lee, D. Chung, and T. Frauenheim, “Structural and vibrational properties of carbon impurities in crystalline silicon,” Semiconductor Science and Technology. 2001. link Times cited: 7 Abstract: Si1-xCx alloys have been studied using self-consistent-charg… read more Abstract: Si1-xCx alloys have been studied using self-consistent-charge density-functional-based tight-binding calculations. The origin of experimentally observed carbon-induced vibrational peaks near 475, 607 and 810 cm-1 are analysed, based on the theoretical calculations. The stability, vibrational frequencies, lattice relaxations, and energy gap variances of substitutional, interstitial single-carbon and dicarbon complexes in crystalline silicon are calculated. All the impurities induce severe lattice relaxations of adjacent Si atoms. The peak near 475 cm-1 originates from the lattice relaxations of Si atoms up to second-nearest neighbours from carbon impurities in all cases. The peak near 605 cm-1 originates mainly from the midbond interstitial carbon (which is at odds with general belief) whereas the high-energy peaks near 810 cm-1 result from the formation of the carbon complexes. read less M. Albrecht et al., “Carbon Containing Platelets in Silicon and Oriented Diamond Growth,” Crystal Research and Technology. 2000. link Times cited: 2 Abstract: We analyse be means of transmision electron microscopy techn… read more Abstract: We analyse be means of transmision electron microscopy techniques the processes during the initial stages of diamond growth by magnetron sputtering. We show that a comparatively high density of C is found as deep as 100 nm in the Si substrate. The carbon arranges in planar defects in {111} and in {001} lattice planes. Our analysis shows that these defects can best be described by coherently strained inclusions that resemble hexagonal SiC platelets. These can act as seeds for orientated growth of diamond on Si. read less J. D’Arcy-Gall et al., “Epitaxial metastable Ge1−yCy (y⩽0.02) alloys grown on Ge(001) from hyperthermal beams: C incorporation and lattice sites,” Journal of Applied Physics. 2000. link Times cited: 8 Abstract: Epitaxial metastable Ge1−yCy alloy layers with y⩽0.02 were g… read more Abstract: Epitaxial metastable Ge1−yCy alloy layers with y⩽0.02 were grown on Ge(001) at temperatures Ts=200–550 °C using hyperthermal Ge and C beams with average energies of 16 and 24 eV, respectively, in order to investigate C incorporation pathways in the Ge lattice. High-resolution reciprocal lattice maps show that all as-deposited alloy layers are fully coherent with the substrate. Layers grown at Ts⩽350 °C are in compression due to higher C concentrations in interstitial than in substitutional sites. The compressive strain decreases (i.e., the substitutional C concentration increases) with increasing Ts within this temperature range. At higher growth temperatures, as-deposited alloys are nearly strain free since the majority of the incorporated C is trapped at extended defects. Annealing the Ge1−yCy layers at Ta=450 and 550 °C leads to a significant increase, proportional to the strain in the as-deposited films, in compressive strain. Further annealing at Ta=650 °C results in the formation of dislocation loop... read less K. Koivusaari, T. Rantala, and S. Leppävuori, “Calculated electronic density of states and structural properties of tetrahedral amorphous carbon,” Diamond and Related Materials. 2000. link Times cited: 14 R. Devanathan and W. J. Weber, “Displacement energy surface in 3C and 6H SiC,” Journal of Nuclear Materials. 2000. link Times cited: 190 H. Nörenberg and G. Briggs, “Influence of carbon on the formation of the Si(001) c(4×4) surface reconstruction,” Surface Science. 1999. link Times cited: 9 H. Nörenberg and G. Briggs, “The Si(001) c(4×4) surface reconstruction: a comprehensive experimental study,” Surface Science. 1999. link Times cited: 40 C. Guedj, M. Dashiell, L. Kulik, J. Kolodzey, and A. Hairie, “Precipitation of β-SiC in Si1−yCy alloys,” Journal of Applied Physics. 1998. link Times cited: 20 Abstract: The infrared modes of annealed Si1−yCy alloys were studied e… read more Abstract: The infrared modes of annealed Si1−yCy alloys were studied experimentally and theoretically. The alloys were grown on Si(100) substrates by solid-source molecular beam epitaxy and were characterized by Fourier transform infrared spectroscopy. At annealing temperatures above 850 °C, the localized vibrational mode of substitutional C around 605 cm−1 diminished in intensity while another mode due to incoherent silicon carbide precipitates appeared at 810 cm−1. For lower processing temperatures, a peak around 725 cm−1 has been tentatively attributed to a C-rich phase, which is a precursor to SiC precipitation. Theoretical calculations based on the anharmonic Keating model predict that small (1 nm) 3C–SiC coherent precipitates may actually produce a mode at 725 cm−1. This mode occurs if the bonds gradually vary in length between the C-rich region and the host lattice. On the other hand, if the bonds are abruptly distorted at the edges of the precipitate, it becomes elastically isolated from the host lattice, a... read less R. Butz and H. Lüth, “The surface morphology of Si (100) after carbon deposition,” Surface Science. 1998. link Times cited: 36 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 H. Osten, G. Lippert, P. Gaworzewski, and R. Sorge, “Impact of low carbon concentrations on the electrical properties of highly boron doped SiGe layers,” Applied Physics Letters. 1997. link Times cited: 35 Abstract: We present results on the effect of carbon coevaporation by … read more Abstract: We present results on the effect of carbon coevaporation by molecular beam epitaxy on electrical properties of highly boron doped SiGe:C layers for C concentration of around 1020 cm−3. Such C concentrations are needed for substantial suppression of boron outdiffusion. The concentration of electrically active boron and the hole mobility are not affected by the addition of carbon. Carbon-related defects, typically observed for C concentrations below the bulk solid solubility limit (<1018 cm−3), do not significantly reduce the concentration of electrically active B in SiGe:C. However, carbon coevaporation affects carrier lifetimes. The generation lifetime is reduced by more than one order of magnitude in SiGe:C compared with analogous SiGe layers. read less K. Beardmore and R. Smith, “Empirical potentials for C-Si-H systems with application to C60 interactions with Si crystal surfaces,” Philosophical Magazine. 1996. link Times cited: 52 Abstract: A semiempirical potential is developed for modelling both th… read more Abstract: A semiempirical potential is developed for modelling both the chemistry and the bulk properties of C[sbnd]Si[sbnd]H systems based on the Tersoff formulation. The potentials are compared with the known energetics of small Si[sbnd]H[sbnd]C clusters with good results. The potential is used to investigate the interaction of Ca with hydrogenated crystal surfaces in the energy range 100-250 eV. The simulations show that a wide variety of interactions is possible. The molecule can stick on the surface either directly or by bouncing across the surface. Reflection from the surface is also possible. read less H. Osten et al., “Strain relaxation in tensile-strained layers on Si(001),” Semiconductor Science and Technology. 1996. link Times cited: 40 Abstract: We investigated in detail the strain relaxation behaviour of… read more Abstract: We investigated in detail the strain relaxation behaviour of metastable tensile-strained epilayers on Si(001) by comparing the layers before and after an annealing step using a variety of different diagnostic methods. The dominant strain-relieving mechanism is the formation of carbon-containing interstitial complexes and/or silicon carbide nanoparticles, similar to the behaviour of carbon in silicon under thermodynamical equilibrium conditions (concentrations below the solid bulk solubility limit). We did not observe any carbon out-diffusion. To grow material suitable for device applications, all carbon atoms should be incorporated substitutionally. There is only a very narrow temperature window for perfect epitaxial growth of such layers, limited on one side by the possible formation of interstitial carbon complexes and on the other side by the deterioration of epitaxial growth at low temperatures. The carbon concentration should not exceed a few per cent to avoid strain-driven precipitation. read less M. Heggie, G. Jungnickel, and C. D. Latham, “The theory of CVD diamond growth,” Diamond and Related Materials. 1996. link Times cited: 10 H.-C. Huang, N. Ghoniem, J. Wong, and M. Baskes, “Molecular dynamics determination of defect energetics in beta -SiC using three representative empirical potentials,” Modelling and Simulation in Materials Science and Engineering. 1995. link Times cited: 102 Abstract: The determination of formation and migration energies of poi… read more Abstract: The determination of formation and migration energies of point and clustered defects in SiC is of critical importance to a proper understanding of atomic phenomena in a wide range of applications. We present here calculations of formation and migration energies of a number of point and clustered defect configurations. A newly developed set of parameters for the modified embedded-atom method (MEAM) is presented. Detailed molecular dynamics calculations of defect energetics using three representative potentials, namely the Pearson potential, the Tersoff potential and the MEAM, have been performed. Results of the calculations are compared to first-principles calculations and to available experimental data. The results are analysed in terms of developing a consistent empirical interatomic potential and are used to discuss various atomic migration processes. read less W. Pollard, “Electronic structure of phosphorus in doped amorphous hydrogenated silicon,” Journal of Non-crystalline Solids. 1994. link Times cited: 3 T. Halicioǧlu, “Binding energies for carbon atoms and clusters deposited on the Si(100) surface,” Thin Solid Films. 1994. link Times cited: 2 T. Halicioǧlu, “Carbon atoms on the (2 × 1) reconstructed Si(100) surface,” Surface Science. 1993. link Times cited: 4 S. Kajihara, A. Antonelli, and J. Bernholc, “Impurity incorporation and doping of diamond,” Physica B-condensed Matter. 1993. link Times cited: 35 J. Bernholc, S. Kajihara, C. Wang, A. Antonelli, and R. Davis, “Theory of native defects, doping and diffusion in diamond and silicon carbide,” Materials Science and Engineering B-advanced Functional Solid-state Materials. 1992. link Times cited: 40 C. Morgan-Pond, “Present status and future of theoretical work on point defects and diffusion in semiconductors,” Journal of Electronic Materials. 1991. link Times cited: 4 Y. Xuan, D. Zhang, and L. Nastac, “An Experimental and Modeling Investigation of Al-based Nanocomposites Manufactured via Ultrasonic Cavitation and Solidification Processing,” Materials Today: Proceedings. 2018. link Times cited: 2 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 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 V. Venkatesh, “Computer simulation studies of carbon nanotube and its interactions with water.” 2014. link Times cited: 1 Abstract: ii addition to defect concentration, the location of defects… read more Abstract: ii addition to defect concentration, the location of defects in SWCNT will also affect the mechanical properties of water submerged SWCNT. For the case of capped SWCNTs, it was found that the concentration of water molecule encapsulated inside the SWCNT strongly affects the elastic properties of the SWCNT. Another study involved the transport characteristics of water molecules in CNTs using MD simulation. The transport properties of water molecules in a nano-scale channel such as CNTs is critical for its key role in designing the next generation CNT based nanofluidic devices. The effect of channel diameter, defects and the inter-layer spacing on the transport of water molecules is studied by subjecting the flow of water molecules through CNTs under pressure. The findings show that the efficiency of water transport can be improved by deploying bigger SWCNTs that have wide channel diameter. It was however found that defects in the nano-fluidic system will reduce the transport efficiency of water molecules. The results also show that the inter-layer spacing in a double-walled CNTs (DWCNTs) has a significant influence on the transport efficiency of water molecules. The investigations and conclusions obtained from this thesis is expected to further compliment the potential applications of CNTs in nano-fluidics and NEMS devices. read less V. Tomar, “Multiscale modeling of the structure and properties of ceramic nanocomposites.” 2013. link Times cited: 0 Abstract: Abstract: One of the most recent developments in ceramics ha… read more Abstract: Abstract: One of the most recent developments in ceramics has been the distribution of multiple phases in a ceramic composite at the nanoscopic length scale. An advanced nanocomposite microstructure such as that of polycrystalline silicon carbide (SiC)–silicon nitride (Si3N4) nanocomposites contains multiple length scales with grain boundary thickness of the order of 50 nm, SiC particle sizes of the order of 200–300 nm and Si3N4 grain sizes of the order of 0.8–1.5 μm. Designing the microstructure of such a composite for a targeted set of material properties is, therefore, a daunting task. Since the microstructure involves multiple length scales, multiscale analyses based material design is an appropriate approach for such a task. With this view, this chapter presents an overview of the current state of the art and work performed in this area. read less V. Tomar, V. Samvedi, and H.-sung Kim, “Atomistic Understanding of the Particle Clustering and Particle Size Effect on the Room Temperature Strength of SiC-Si3N4 Nanocomposites,” International Journal for Multiscale Computational Engineering. 2010. link Times cited: 7 V. Samvedi and V. Tomar, “Atomistic Simulations - Based Understanding of the Mechanism behind the Role of Second-Phase SiC Particles in Fracture Resistance of SiC-Si 3 N 4 Nanocomposites,” International Journal for Multiscale Computational Engineering. 2009. link Times cited: 11 M. Heggie, “Theory and Modelling of Carbon.” 2001. link Times cited: 1 J. Perlado, L. Malerba, A. Sánchez-Rubio, and T. D. Rubia, “Analysis of displacement cascades and threshold displacement energies in β-sic,” Journal of Nuclear Materials. 2000. link Times cited: 48 M. Ali and A. Törn, “Optimization of Carbon and Silicon Cluster Geometry for Tersoff Potential using Differential Evolution.” 2000. link Times cited: 23 H. Osten, “Si 1−x−y Ge x C y alloys: Growth and properties of a new semiconducting material.” 1999. link Times cited: 0 K. Eberl, K. Brunner, and O. Schmidt, “Chapter 8 - Si1–yCy and Si1–x–yGexCy Alloy Layers,” Semiconductors and Semimetals. 1998. link Times cited: 5 C. A. Londos, “Deep level transient spectroscopy investigation of a deep trap in float‐zone Si,” Journal of Applied Physics. 1994. link Times cited: 3 Abstract: Carbon-related defects in silicon have been the subject stag… read more Abstract: Carbon-related defects in silicon have been the subject stage the defect partners attach each other to a more or less of a large number of works. In particular, a level positioned unstable configuration prior to the final arrangement of the at about 0.34 eV [herein to be referred as H(0.34)] above defect when the stable configuration is established. Otherthe top of the valence band in float-zone material has re- wise, one could think of an energy barrier that separates ceived much attention in recent years. However, the results the second and third stage preventing the automatic forof various researchers are in some respects controversial. mation of the defect complex. The probability of penetraAn early assignment has correlated the H( 0.34) state with tion or overcoming such a barrier depends among other the C-C, pair.’ Recently, Song et ~1.~ have raised serious factors on the charge state of the participants and the temdoubts about this correlation. In a p-type material, it was perature. The higher the dynamical barrier the larger the proposed that the Ci-Cs pair is a bistable trap possessing necessary increase in temperature for the final structure to two levels H( 0.05 ) and H( 0.09)) each of them correspond- be achieved. This appears in the spectra as a delay with ing to the two configurations of the defect. It is worth temperature between the first stage [migration of noting that in some experiments, signals from the H( 0.34) Cfs-decay of H(0.28) peak] and the third stage [formadefect were not observed,3 although the level has also been tion of the final defect structure-emergence of the reported in proton4 irradiated Si. H(0.34) peak]. Aluminum-silicon Schottky diodes with boron dopant read less T. Halicioǧlu, “Strain dependence of binding energies for carbon adatoms on the Si(100) surface,” Thin Solid Films. 1994. link Times cited: 0 J. Bernholc, S. Kajihara, and A. Antonelli, “Theory of Doping of Diamond,” MRS Proceedings. 1992. link Times cited: 0 K. Jensen, “III-1 – Thermal Chemical Vapor Deposition.” 1991. link Times cited: 22 J. Tersoff, “Calculated Properties of Carbon Defects in Silicon,” MRS Proceedings. 1990. link Times cited: 0 T. Menold, M. Ametowobla, and J. Werner, “Signatures of self-interstitials in laser-melted and regrown silicon,” AIP Advances. 2021. link Times cited: 2 Abstract: Photoluminescence spectroscopy investigates epitaxially regr… read more Abstract: Photoluminescence spectroscopy investigates epitaxially regrown silicon single crystals after pulsed laser melting for atomic-level lattice defects. The measurements identify a transition from a regime free of defect-related spectral lines to a regime in which spectral lines appear originating from small self-interstitial clusters. This finding of self-interstitial clusters indicates supersaturated concentrations of self-interstitials within the regrown volume. Molecular dynamics simulations confirm that recrystallization velocities vre ≈ 1 m/s after laser melting lead to supersaturation of both self-interstitials and vacancies. Their concentrations ci and cv in the regrown volumes are ci ≈ cv ≈ 1017 cm−3. An analytical model based on time-dependent nucleation theory shows a very strong dependence of self-interstitial aggregation to clusters on the cooling rate after solidification. This model explains the transition identified by photoluminescence spectroscopy. read less 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 H. M. Ayedh, E. Monakhov, and J. Coutinho, “Formation and dissociation reactions of complexes involving interstitial carbon and oxygen defects in silicon,” Physical Review Materials. 2020. link Times cited: 3 Abstract: We present a detailed first-principles study which explores … read more Abstract: We present a detailed first-principles study which explores the configurational space along the relevant reactions and migration paths involving the formation and dissociation of interstitial carbon-oxygen complexes, $\mathrm{C_{i}O_{i}}$ and $\mathrm{C_{i}O_{2i}}$, in silicon. The formation/dissociation mechanisms of $\mathrm{C_{i}O_{i}}$ and $\mathrm{C_{i}O_{2i}}$ are found as occurring via capture/emission of mobile $\mathrm{C_{i}}$ impurities by/from O-complexes anchored to the lattice. The lowest activation energies for dissociation of $\mathrm{C_{i}O_{i}}$ and $\mathrm{C_{i}O_{2i}}$ into smaller moieties are 2.3 eV and 3.1 eV, respectively. The first is compatible with the observed annealing temperature of $\mathrm{C_{i}O_{i}}$ , which occurs at around 400 $^{\circ}$C, and below the threshold for $\mathrm{O_{i}}$ diffusion. The latter exceeds significantly the measured activation energy for the annealing of $\mathrm{C_{i}O_{2i}}$ ($E_{\mathrm{a}}=2.55$ eV). We propose that instead of dissociation, the actual annealing mechanism involves the capture of interstitial oxygen by $\mathrm{C_{i}O_{2i}}$, thus being governed by the migration barrier of $\mathrm{O_{i}}$ ($E_{\mathrm{m}}=2.53$ eV). The study is also accompanied by measurements of hole capture cross sections and capture barriers of $\mathrm{C_{i}O_{i}}$ and $\mathrm{C_{i}O_{2i}}$. In combination with previously reported data, we find thermodynamic donor transitions which are directly comparable to the first-principles results. The two levels exhibit close features, conforming to a model where the electronic character of $\mathrm{C_{i}O_{2i}}$ can be described by that of $\mathrm{C_{i}O_{i}}$ perturbed by a nearby O atom. read less 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 K. Kohno and M. Ishimaru, “Molecular-dynamics simulations of solid phase epitaxy in silicon: Effects of system size, simulation time, and ensemble,” Japanese Journal of Applied Physics. 2018. link Times cited: 3 Abstract: Solid phase epitaxial (SPE) recrystallization of amorphous S… read more Abstract: Solid phase epitaxial (SPE) recrystallization of amorphous Si on a Si(001) substrate was examined by large-scale (6144–129024 Si atoms), long-time (up to 2000 ns) molecular-dynamics (MD) simulations using the empirical Tersoff interatomic potential. We particularly focused on the effects of the MD cell size, simulation time, and ensemble on the SPE growth rate. We found that the simulations under the isothermal–isochoric conditions (NVT ensemble) show a higher crystallization rate than those under the isothermal–isobaric conditions (NPT ensemble). The system size dealt with in the present MD simulation, i.e., >6144 Si atoms, was enough to estimate the SPE growth rate. The Arrhenius plot of the growth rate between 1300 and 1600 K exhibited a single activation energy, ∼2.4 eV, which is in agreement with the experimental value (∼2.7 eV). However, the growth rate at temperatures below 1300 K deviated from the extrapolated ones from 1300 to 1600 K, which is because recrystallization does not reach a steady state: long-time MD simulations are required to estimate the growth rate at low temperature. The structure analysis of amorphous/crystalline interfaces suggested that the braking of atomic bonds parallel to the interface becomes a rate-limiting step of the SPE growth. read less 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 V. S. Proshchenko, P. Dholabhai, and S. Neogi, “Heat and charge transport in bulk semiconductors with interstitial defects,” Physical Review B. 2018. link Times cited: 10 Abstract: Interstitial defects are inevitably present in doped semicon… read more Abstract: Interstitial defects are inevitably present in doped semiconductors that enable modern-day electronic, optoelectronic or thermoelectric technologies. Understanding of stability of interstitials and their bonding mechanisms in the silicon lattice was accomplished only recently with the advent of first-principles modeling techniques, supported by powerful experimental methods. However, much less attention has been paid to the effect of different naturally occurring interstitials on the thermal and electrical properties of silicon. In this work, we present a systematic study of the variability of heat and charge transport properties of bulk silicon, in the presence of randomly distributed interstitial defects (Si, Ge, C and Li). We find through atomistic lattice dynamics and molecular dynamics modeling studies that, interstitial defects scatter heat-carrying phonons to suppress thermal transport-1.56% of randomly distributed Ge and Li interstitials reduce the thermal conductivity of silicon by $\sim$ 30 and 34 times, respectively. Using first principles density functional theory and semi-classical Boltzmann transport theory, we compute electronic transport coefficients of bulk Si with 1.56% Ge, C, Si and Li interstitials, in hexagonal, tetrahedral, split-interstitial and bond-centered sites. We demonstrate that hexagonal-Si and hexagonal-Ge interstitials minimally impact charge transport. To complete the study, we predict the thermoelectric property of an experimentally realizable bulk Si sample that contains Ge interstitials in different symmetry sites. Our research establishes a direct relationship between the variability of structures dictated by fabrication processes and heat and charge transport properties of silicon. The relationship provides guidance to accurately estimate performance of Si-based materials for various technological applications. 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 C. Beaufils et al., “Optical properties of an ensemble of G-centers in silicon,” Physical Review B. 2017. link Times cited: 48 Abstract: We addressed the carrier dynamics in so-called G-centers in … read more Abstract: We addressed the carrier dynamics in so-called G-centers in silicon (consisting of substitutional-interstitial carbon pairs interacting with interstitial silicons) obtained via ion implantation into a silicon-on-insulator wafer. For this point defect in silicon emitting in the telecommunication wavelength range, we unravel the recombination dynamics by time-resolved photoluminescence spectroscopy. More specifically, we performed detailed photoluminescence experiments as a function of excitation energy, incident power, irradiation fluence and temperature in order to study the impact of radiative and non-radiative recombination channels on the spectrum, yield and lifetime of G-centers. The sharp line emitting at 969 meV ($\sim$1280 nm) and the broad asymmetric sideband developing at lower energy share the same recombination dynamics as shown by time-resolved experiments performed selectively on each spectral component. This feature accounts for the common origin of the two emission bands which are unambiguously attributed to the zero-phonon line and to the corresponding phonon sideband. In the framework of the Huang-Rhys theory with non-perturbative calculations, we reach an estimation of 1.6$\pm$0.1 $\angstrom$ for the spatial extension of the electronic wave function in the G-center. The radiative recombination time measured at low temperature lies in the 6 ns-range. The estimation of both radiative and non-radiative recombination rates as a function of temperature further demonstrate a constant radiative lifetime. Finally, although G-centers are shallow levels in silicon, we find a value of the Debye-Waller factor comparable to deep levels in wide-bandgap materials. Our results point out the potential of G-centers as a solid-state light source to be integrated into opto-electronic devices within a common silicon platform. 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 X. Dong and Y. Shin, “Multiscale Genome Modeling for Predicting the Thermal Conductivity of Silicon Carbide Ceramics,” Journal of the American Ceramic Society. 2016. link Times cited: 11 Abstract: Silicon carbide (SiC) ceramics have been widely used in indu… read more Abstract: Silicon carbide (SiC) ceramics have been widely used in industry due to its high thermal conductivity. Understanding the relations between the microstructure and the thermal conductivity of SiC ceramics is critical for improving the efficiency of heat removal in heat sink applications. In this paper, a multiscale model is proposed to predict the thermal conductivity of SiC ceramics by bridging atomistic simulations and continuum model via a materials genome model. Interatomic potentials are developed using ab initio calculations to achieve more accurate molecular dynamics (MD) simulations. Interfacial thermal conductivities with various additive compositions are predicted by nonequilibrium MD simulations. A homogenized materials genome model with the calculated interfacial thermal properties is used in a continuum model to predict the effective thermal conductivity of SiC ceramics. The effects of grain size, additive compositions, and temperature are also studied. The good agreement found between prediction results and experimental measurements validates the capabilities of the proposed multiscale genome model in understanding and improving the thermal transport characteristics of SiC ceramics. 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 D. Zhang and L. Nastac, “Progress on Numerical Modeling of the Dispersion of Ceramic Nanoparticles During Ultrasonic Processing and Solidification of Al-Based Nanocomposites,” JOM. 2016. link Times cited: 4 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 F. Zirkelbach, B. Stritzker, K. Nordlund, J. Lindner, W. Schmidt, and E. Rauls, “Combined ab initio and classical potential simulation study on silicon carbide precipitation in silicon,” Physical Review B. 2011. link Times cited: 22 Abstract: Atomistic simulations on the silicon carbide precipitation i… read more Abstract: Atomistic simulations on the silicon carbide precipitation in bulk silicon employing both, classical potential and first-principles methods are presented. The calculations aim at a comprehensive, microscopic understanding of the precipitation mechanism in the context of controversial discussions in the literature. For the quantum-mechanical treatment, basic processes assumed in the precipitation process are calculated in feasible systems of small size. The migration mechanism of a carbon 〈1 0 0〉 interstitial and silicon 〈11 0〉 self-interstitial in otherwise defect-free silicon are investigated using density functional theory calculations. The influence of a nearby vacancy, another carbon interstitial and a substitutional defect as well as a silicon self-interstitial has been investigated systematically. Interactions of various combinations of defects have been characterized including a couple of selected migration pathways within these configurations. Most of the investigated pairs of defects tend to agglomerate allowing for a reduction in strain. The formation of structures involving strong carbon–carbon bonds turns out to be very unlikely. In contrast, substitutional carbon occurs in all probability. A long range capture radius has been observed for pairs of interstitial carbon as well as interstitial carbon and vacancies. A rather small capture radius is predicted for substitutional carbon and silicon self-interstitials. Initial assumptions regarding the precipitation mechanism of silicon carbide in bulk silicon are established and conformability to experimental findings is discussed. Furthermore, results of the accurate first-principles calculations on defects and carbon diffusion in silicon are compared to results of classical potential simulations revealing significant limitations of the latter method. An approach to work around this problem is proposed. Finally, results of the classical potential molecular dynamics simulations of large systems are examined, which reinforce previous assumptions and give further insight into basic processes involved in the silicon carbide transition. read less C. R. Dandekar and Y. Shin, “Molecular dynamics based cohesive zone law for describing Al–SiC interface mechanics,” Composites Part A-applied Science and Manufacturing. 2011. link Times cited: 178 M. Wojdyr, S. Khalil, Y. Liu, and I. Szlufarska, “Energetics and structure of ⟨0 0 1⟩ tilt grain boundaries in SiC,” Modelling and Simulation in Materials Science and Engineering. 2010. link Times cited: 35 Abstract: We have developed a scheme, based on molecular dynamics, tha… read more Abstract: We have developed a scheme, based on molecular dynamics, that allows finding minimum energy structures of grain boundaries (GBs) with relatively large cell of non-identical displacements. This scheme has been used to study symmetric ⟨0 0 1⟩ tilt GBs in cubic SiC. We analyze atomic configurations of dislocation cores found in low-angle GBs and we report structural units found in high-angle GBs. In contrast to what had been previously assumed we find that the lowest energy structures often do not favor perfect coordination of GB atoms and that most of the analyzed GBs contain 6- and 7-atom rings. We tested the applicability of existing empirical potentials to studies of high-symmetry GB structures in SiC and we found the Tersoff potential to be most appropriate. Knowledge of detailed atomic structures of GBs is essential for future studies of GB-controlled phenomena in SiC, such as diffusion of metallic fission product through this material or GB strengthening. read less F. Zirkelbach, B. Stritzker, K. Nordlund, J. Lindner, W. Schmidt, and E. Rauls, “Defects in carbon implanted silicon calculated by classical potentials and first-principles methods,” Physical Review B. 2010. link Times cited: 7 Abstract: A comparative theoretical investigation of carbon interstiti… read more Abstract: A comparative theoretical investigation of carbon interstitials in silicon is presented. Calculations using classical potentials are compared to first-principles density-functional theory calculations of the geometries, formation, and activation energies of the carbon dumbbell interstitial, showing the importance of a quantummechanical description of this system. In contrast to previous studies, the present first-principles calculations of the interstitial carbon migration path yield an activation energy that excellently matches the experiment. The bond-centered interstitial configuration shows a net magnetization of two electrons, illustrating the need for spin-polarized calculations. 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 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 U. M. E. Christmas, D. Faux, and N. Cowern, “Elastic interaction energy between a silicon interstitial and a carbon substitutional in a silicon crystal,” Physical Review B. 2007. link Times cited: 1 Abstract: The strain interaction energy between a silicon interstitial… read more Abstract: The strain interaction energy between a silicon interstitial and a carbon substitutional in a silicon crystal was modeled by a continuum Green’s function method and by atomistic simulation. The interaction energy is proportional to d−3, where d is separation distance between the defects. The pair interaction energy was found to be less than 0.04 meV for d 6 nm increasing to more than about 0.1 meV for d 3 nm. The energies are unlikely to influence the diffusional behavior of the defects except at distances of one or two unit cells. The potential between the point defects is repulsive if they are oriented along the 100 crystal axis, but attractive if they are positioned along 110 or 111 . read less Z. Huang, Z. Guo, X. Chen, Z. Yu, T. M. Yu, and W. Lee, “Microscopic machining mechanism of polishing based on vibrations of liquid,” Nanotechnology. 2007. link Times cited: 8 Abstract: A molecular dynamics method has been applied to study the me… read more Abstract: A molecular dynamics method has been applied to study the mechanism of polishing based on vibrations of liquid. Movements of polishing particles and formations of impact dents are simulated and discussed. The abrasive effect between particle and machined substrate is evaluated empirically. Polishing qualities, including roughness and fractal character under multiple impacts, are obtained by numerical methods. Results show that the particle will vibrate and roll viscously on the substrate. Press, tear and self-organization effects will be responsible for the formation of impact dents. Simulation results are compared with experimental data to verify the conclusions. 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 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 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 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 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
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_444207127575_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_1990_SiC__MO_444207127575_000
DOI	10.25950/653e6833 https://doi.org/10.25950/653e6833 https://commons.datacite.org/doi.org/10.25950/653e6833
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 6.20840e-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
F The model is C^-1 continuous. This means that the model has discontinuous energy.	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: C

Species: Si

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: 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: Si

Species: C

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.

(No matching species)

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	1677
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	3531
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	2348
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	4048
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	3909
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	2606
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	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	2162
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	1715
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	3272
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1267
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	3710
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	1938
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	1938
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	1230
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	3968
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3441
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	3819
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	4098
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	1267
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	3919
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	3968
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	1677
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	1342
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	3451
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2348
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	4008
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	1826
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	1193
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	3988
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	3799
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	1267
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	2385
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	4108
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	1379
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	3839
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	3899
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	2125
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3063
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	3093
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	3869
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	2236
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	3600
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	1379
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	2162
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	4048
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	3998
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	2013
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	3073
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2864
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1305
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	3959
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3093
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	3988
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	1528
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	3889
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	1752
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1193
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	3869
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	1528
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2526
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	3889
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	2725
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	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	1603
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	3640
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	2274
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	1454
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	4167
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	1715
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	2735
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	1565
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	3441
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	1528
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	3959
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	3988
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	2013
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1305
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	4257
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	3859
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	4128
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	3968
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	3213
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	3789
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	1565
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	3740
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3024
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2586
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	3789
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	2606
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	1826
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	3909
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	3849
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	1677
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	1454
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	2423
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	3879
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	1305
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	1715
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	3760
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	1603
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1230
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	1305
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	3889
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	4098
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	3710
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	4217
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	2199
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	3600
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2348
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	3968
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	2050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1267
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	4147
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	1603
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	1379
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	4008
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	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	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	1230
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	1267
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3193
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	2636
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1305
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1305
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	4078
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	2758
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	1938
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4237
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	1864
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	3889
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	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	3849
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3670
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	3670
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2884
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	1938
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	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	1342
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2835
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	3272
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2423
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	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4157
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	1938
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	3710
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	1938
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	1975
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	1193
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1155
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	1938
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	2050
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	2274
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	1640
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	1342
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	1565
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	1640
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	3779
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	3024
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4396
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	2695
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	3610
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4277
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	1789
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	1938
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	3531
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	1938
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4227
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	3879
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4267
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	1677
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	1901
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	2013
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	3789
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	2013
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	2050
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	3779
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	3849
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4227
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	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	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	3899
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	1752
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	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	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	2311
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	3043
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	3640
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	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4147
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	1379
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	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4267
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	3978
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	3859
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	1975
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3511
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	3919
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	1305
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	3889
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	3919
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	1640
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	1864
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	3411
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	3043
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	1379
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	2013
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3272
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	1565
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	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	4118
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	1715
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1305
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	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	1938
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	2087
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	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	1715
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	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	2311
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	1454
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	1826
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	2934
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	4207
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4575
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	1342
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	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3670
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	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	2050
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	1715
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	1342
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	1491
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	3869
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	1454
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	2274
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	3859
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	2087
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	2236
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	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	1715
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	3889
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	3799
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	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	1864
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	1752
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	4088
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	4078
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	3939
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	1864
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	3909
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	3978
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	3899
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	4028
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3223
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	3959
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	2162
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	4108
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	3919
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	4098
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	4327
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3163
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3153
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1305
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	1715
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	2125
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	2087
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	1938
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	4028
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	1789
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	4058
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	1901
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	3700
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1305
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	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	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	3849
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	1901
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	3909
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	2311
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3019
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	1379
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	4207
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	2236
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	4108
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	1640
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3332
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	4028
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	3869
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	2311
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	1864
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	1752
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	1416
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	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	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	3949
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	4068
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	3561
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	1305
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	1789
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	1789
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	3839
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	3949
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	1901
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	3740
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	3939
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	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	2586
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	1938
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	4147
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4267
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	2348
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	2162
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3670
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	4028
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	2199
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2348
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	3988
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	1901
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	4058
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	4068
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	2162
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	1677
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	1342
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	2013
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	4336
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	3869
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	2348
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	3978
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	3949
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	3789
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	2274
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	3879
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	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	3959
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	1901
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3019
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	1938
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	2162
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	3998
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	1342
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	2609
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	1305
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	4108
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	3760
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	3939
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	2460
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3163
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	3471
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	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	1379
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	1640
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	4078
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	4317
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	3650
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	1826
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	4167
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	1565
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	2785
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	3720
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	3302
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	2609
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	1975
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	2497
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	4147
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1864

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	2437
Cohesive energy versus lattice constant curve for bcc Si v004	view	2447
Cohesive energy versus lattice constant curve for diamond C v004	view	2964
Cohesive energy versus lattice constant curve for diamond Si v004	view	2282
Cohesive energy versus lattice constant curve for fcc C v004	view	2798
Cohesive energy versus lattice constant curve for fcc Si v004	view	2307

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	67504

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	9281
Elastic constants for bcc Si at zero temperature v006	view	11915
Elastic constants for diamond C at zero temperature v001	view	26864
Elastic constants for diamond Si at zero temperature v001	view	6821
Elastic constants for fcc C at zero temperature v006	view	12104

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	101891
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype A2B_tP6_131_i_e v002	view	63903
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cF136_227_aeg v002	view	1760035
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_cF16_227_c v002	view	234923
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_cF240_202_h2i v002	view	335425599
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cF4_225_a v002	view	75608
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_cF8_227_a v002	view	101348
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cF8_227_a v002	view	145548
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cI12_229_d v002	view	240960
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cI16_206_c v002	view	59059
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_cI16_229_f v002	view	1700794
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cI82_217_acgh v002	view	392986
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_cI8_214_a v002	view	74735
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_cP1_221_a v002	view	512511
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_cP20_221_gj v002	view	106512
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cP46_223_cik v002	view	272764
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP12_194_bc2f v002	view	86283
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP12_194_e2f v002	view	47332
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP16_194_e3f v002	view	46603
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP1_191_a v002	view	45266
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP2_191_c v002	view	111461
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP2_194_c v002	view	43504
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP40_191_hjmno v002	view	113074
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP4_194_bc v002	view	54626
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP4_194_f v002	view	57718
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP4_194_f v002	view	61620
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP58_164_2d3i3j v002	view	190677
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP68_194_ef2h2kl v002	view	121520
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hP8_194_ef v002	view	55510
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hR10_166_5c v002	view	55952
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hR14_166_7c v002	view	60456
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hR2_166_c v002	view	35302
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hR4_166_2c v002	view	39798
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_hR60_166_2h4i v002	view	179152174
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_mC164_15_e20f v002	view	460135
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_mC16_12_4i v002	view	108811
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_mC16_12_4i v002	view	58208
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_oC16_65_mn v002	view	374360
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_oC8_65_gh v002	view	858710
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_oC92_63_ce2f2g3h v002	view	355955
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_oF16_69_gh v002	view	118750
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_oI120_71_lmn6o v002	view	7520326
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_oP16_62_4c v002	view	97547
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_tI8_139_h v002	view	45448
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_tI8_139_h v002	view	43626
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_tP106_137_a5g4h v002	view	382090
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_cF8_216_a_c v002	view	116615
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_cF8_225_a_b v002	view	70239
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP10_156_2a2bc_2a2bc v002	view	68393
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP12_186_a2b_a2b v002	view	74504
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP16_186_a3b_a3b v002	view	84369
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP20_156_4a3b3c_4a3b3c v002	view	99020
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP28_156_5a5b4c_5a5b4c v002	view	309869
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP32_186_3a5b_3a5b v002	view	72547
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP36_156_8a5b5c_8a5b5c v002	view	100376
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP38_156_7a6b6c_7a6b6c v002	view	100193
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP42_156_7a7b7c_7a7b7c v002	view	207978
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP4_186_b_b v002	view	69571
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP54_156_9a9b9c_9a9b9c v002	view	277108
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hP8_186_ab_ab v002	view	68982
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hR10_160_5a_5a v002	view	59484
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hR14_160_7a_7a v002	view	63433
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hR16_160_8a_8a v002	view	73823
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hR18_160_9a_9a v002	view	89560
Equilibrium crystal structure and energy for CSi in AFLOW crystal prototype AB_hR22_160_11a_11a v002	view	114350

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	9926
Equilibrium zero-temperature lattice constant for bcc Si v007	view	9687
Equilibrium zero-temperature lattice constant for diamond C v007	view	3131
Equilibrium zero-temperature lattice constant for diamond Si v007	view	9419
Equilibrium zero-temperature lattice constant for fcc C v007	view	3205
Equilibrium zero-temperature lattice constant for fcc Si v007	view	9240

LatticeConstantHexagonalEnergy__TD_942334626465_005

Equilibrium lattice constants for hexagonal bulk structures at zero temperature and pressure v005

Creators: Daniel S. Karls and Junhao Li
Contributor: karls
Publication Year: 2019
DOI: https://doi.org/10.25950/c339ca32

Calculates lattice constant of hexagonal bulk structures at zero temperature and pressure by using simplex minimization to minimize the potential energy.

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)
Equilibrium lattice constants for hcp C v005		view	22922

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 Si at 293.15 K under a pressure of 0 MPa v002		view	1720437

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	3829
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	3939
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3988
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1342
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3929
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3869
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3789
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	1342
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1267
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1305
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2874
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2685
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	1752
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	1826
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	3839
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2311
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	3869
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3959
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3859
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1305
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3959
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1677
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	4108
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1267
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3511
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1677
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	1975
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	3859
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3163
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1677
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	1752
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	4177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	4058
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3799
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	1230
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	3959
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	1342
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	4028
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3779
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2162
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	1677
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2311
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	1305
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1342
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1267
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3620
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2616
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	1975
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	3879
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	2596
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	2087
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3959
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	3968
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	3959
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 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	3750
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	2125
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	1491
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	1789
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	3889
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	3799
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	3760
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	3779
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3332
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	3680
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	1267
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	2087
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3959
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	2162
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3949
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	1715
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	1975
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3809
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	3591
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3939
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	1305
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	3232
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3889
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	3879
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3332
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	3889
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1342
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	3740
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	3869
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3949
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	4088
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	3829
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	3809
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	3959
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	3988
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	3899
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	3083
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	1640
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	3750
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	3302
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	3819
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	1528
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	4108
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	1677
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	2087
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	4078
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	2125
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	2050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	2274
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1416
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	1752
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3998
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3988
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	2274
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	3551
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	4018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3730
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3988
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3849
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	1715
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	3770
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1267
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	2087
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1267
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	3392
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1752
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1640
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	1565
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1715
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	2162
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	3113
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	3839
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	1416
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	2125
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	2423
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	3770
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	1342
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1565
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1305
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1528
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	3879
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	2013
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	1565
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	2050
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	3720
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1305
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	3213
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	3829
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1342
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	2199
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	1379
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	4098

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	199732

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	3953715

Errors

ElasticConstantsCubic__TD_011862047401_006

Test	Error Categories	Link to Error page
Elastic constants for fcc Si at zero temperature v006	other	view

ElasticConstantsHexagonal__TD_612503193866_004

Test	Error Categories	Link to Error page
Elastic constants for hcp C at zero temperature v004	other	view

EquilibriumCrystalStructure__TD_457028483760_000

Test	Error Categories	Link to Error page
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_hP4_194_bc 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_hP8_194_ef 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_mC16_12_4i v000	other	view
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_oI120_71_lmn6o v000	other	view
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_tI8_139_h 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_cI16_206_c v002	other	view
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hR8_148_cf v002	other	view
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_oC16_65_pq v002	other	view
Equilibrium crystal structure and energy for C in AFLOW crystal prototype A_oC8_67_m v002	other	view
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_tI4_141_a v002	other	view

LatticeConstant2DHexagonalEnergy__TD_034540307932_002

Test	Error Categories	Link to Error page
Cohesive energy and equilibrium lattice constant of graphene v002	other	view

LatticeConstantCubicEnergy__TD_475411767977_007

Test	Error Categories	Link to Error page
Equilibrium zero-temperature lattice constant for sc C v007	other	view
Equilibrium zero-temperature lattice constant for sc Si v007	other	view

LatticeConstantHexagonalEnergy__TD_942334626465_005

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

LinearThermalExpansionCoeffCubic__TD_522633393614_001

Test	Error Categories	Link to Error page
Linear thermal expansion coefficient of diamond C at 293.15 K under a pressure of 0 MPa v001	other	view
Linear thermal expansion coefficient of diamond Si at 293.15 K under a pressure of 0 MPa v001	other	view

No Driver

Verification Check	Error Categories	Link to Error page
MemoryLeak__VC_561022993723_004	other	view

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1990_SiC.settings
1990_SiC.tersoff
CMakeLists.txt
LICENSE
kimprovenance.edn
kimspec.edn

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Tersoff_LAMMPS_Tersoff_1990_SiC__MO_444207127575_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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