LAMMPS Buckingham potential for SiO2 developed by Carré et al. (2008) v000

Evangelos Voyiatzis; Antreas Afantitis; Antoine Carré; Juergen Horbach; Simona Ispas; Walter Kob

doi:10.25950/dbac5d53

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Sim_LAMMPS_Buckingham_CarreHorbachIspas_2008_SiO__SM_886641404623_000

Interatomic potential for Oxygen (O), Silicon (Si).
Use this Potential

Title A single sentence description.	LAMMPS Buckingham potential for SiO2 developed by Carré et al. (2008) v000
Description	An interionic potential for silica which is derived by fitting the parameters to data generated by Car-Parrinello molecular-dynamics (CPMD) simulations. It reproduces accurately the liquid structure generated by the CPMD trajectories, the experimental activation energies for the self-diffusion constants and the experimental density of amorphous silica. Also lattice parameters and elastic constants of α-quartz are well reproduced, showing the transferability of this potential.
Species The supported atomic species.	O, Si
Disclaimer A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.	None

Contributor	Evangelos Voyiatzis
Maintainer	Evangelos Voyiatzis
Implementer	Evangelos Voyiatzis Antreas Afantitis
Developer	Antoine Carré Juergen Horbach Simona Ispas Walter Kob
Published on KIM	2021
How to Cite	This Simulator Model originally published in [1] is archived in OpenKIM [2-4]. [1] Carré A, Horbach J, Ispas S, Kob W. New fitting scheme to obtain effective potential from Car-Parrinello molecular-dynamics simulations: Application to silica. Europhysics Letters. 2008 ;82:17001. doi:10.1209/0295-5075/82/17001 — (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] Voyiatzis E, Afantitis A, Carré A, Horbach J, Ispas S, Kob W. LAMMPS Buckingham potential for SiO2 developed by Carré et al. (2008) v000. OpenKIM; 2021. doi:10.25950/dbac5d53 [3] 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 [4] 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. 93 Citations (42 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 . S. Sundararaman, L. Huang, S. Ispas, and W. Kob, “New optimization scheme to obtain interaction potentials for oxide glasses.,” The Journal of chemical physics. 2018. link Times cited: 53 Abstract: We propose a new scheme to parameterize effective potentials… read more Abstract: We propose a new scheme to parameterize effective potentials that can be used to simulate atomic systems such as oxide glasses. As input data for the optimization, we use the radial distribution functions of the liquid and the vibrational density of state of the glass, both obtained from ab initio simulations, as well as experimental data on the pressure dependence of the density of the glass. For the case of silica, we find that this new scheme facilitates finding pair potentials that are significantly more accurate than the previous ones even if the functional form is the same, thus demonstrating that even simple two-body potentials can be superior to more complex three-body potentials. We have tested the new potential by calculating the pressure dependence of the elastic moduli and found a good agreement with the corresponding experimental data. read less R. Renou, L. Soulard, E. Lescoute, C. Dereure, D. Loison, and J. Guin, “Silica Glass Structural Properties under Elastic Shock Compression: Experiments and Molecular Simulations,” Journal of Physical Chemistry C. 2017. link Times cited: 21 Abstract: The behavior of silica glass material under shock compressio… read more Abstract: The behavior of silica glass material under shock compression has been investigated in this work. Laser-driven experiments and molecular dynamics simulations were combined to study the elastic regime of fused silica up to 8 GPa. Two simple pair potentials, BKS and CHIK, were tested and the shocked states of the glassy material were obtained by direct shocks and a new Hugoniostat method. The Hugoniot curves obtained numerically were in a very good agreement with the experimental curves. Despite the simplicity of their mathematical form, the pair potentials tested (BKS and CHIK) were able to give a fair description of the silica glass behavior under shock loading conditions. The structural properties of silica glass were also thoroughly studied. It was found that in the elastic regime, the short-range order (tetrahedra) and the medium-range order (rings) were not impacted by the shock wave propagation inside the material. The structural changes behind the shock front were mainly related to a free volume clo... read less Y. J. Yu et al., “Epitaxially Self‐Assembled Alkane Layers for Graphene Electronics,” Advanced Materials. 2017. link Times cited: 22 Abstract: The epitaxially grown alkane layers on graphene are prepared… read more Abstract: The epitaxially grown alkane layers on graphene are prepared by a simple drop-casting method and greatly reduce the environmentally driven doping and charge impurities in graphene. Multiscale simulation studies show that this enhancement of charge homogeneity in graphene originates from the lifting of graphene from the SiO2 surface toward the well-ordered and rigid alkane self-assembled layers. read less L. Broussous et al., “Contribution of molecular simulation to the characterization of porous low-k materials,” 2015 IEEE International Interconnect Technology Conference and 2015 IEEE Materials for Advanced Metallization Conference (IITC/MAM). 2015. link Times cited: 0 Abstract: This study aims to investigate the modified surface porosity… read more Abstract: This study aims to investigate the modified surface porosity of SiOCH low-k porous thin films using statistical mechanics molecular simulations and ellipso-porosimetry. The thin films are modified by plasma etching and wet cleaning. Numerical simulations of solvent adsorption on surfaces highlighted solvent affinity variations depending on chemical surface compositions. read less M. Lépinay et al., “Predicting Adsorption on Bare and Modified Silica Surfaces,” Journal of Physical Chemistry C. 2015. link Times cited: 16 Abstract: We show that Derjaguin’s theory of adsorption can be used to… read more Abstract: We show that Derjaguin’s theory of adsorption can be used to predict adsorption on bare and modified surfaces using parameters available to simple experiments. Using experiment and molecular simulation of adsorption of various gases on hydroxylated, methylated, and trifluoromethylated silica, this simple parametrization of Derjaguin’s model allows predicting adsorption on any functionalized surface using a minimum set of parameters such as the heat of vaporization of the adsorbate and the Henry constant of the adsorption isotherm. This general yet simple scheme constitutes a powerful tool as it avoids having to carry out tedious and complex adsorption measurements. read less E. Manga et al., “Effect of gas adsorption on acoustic wave propagation in MFI zeolite membrane materials: experiment and molecular simulation.,” Langmuir : the ACS journal of surfaces and colloids. 2014. link Times cited: 6 Abstract: The present study reports on the development of a characteri… read more Abstract: The present study reports on the development of a characterization method of porous membrane materials which consists of considering their acoustic properties upon gas adsorption. Using acoustic microscopy experiments and atomistic molecular simulations for helium adsorbed in a silicalite-1 zeolite membrane layer, we showed that acoustic wave propagation could be used, in principle, for controlling the membranes operando. Molecular simulations, which were found to fit experimental data, showed that the compressional modulus of the composite system consisting of silicalite-1 with adsorbed He increases linearly with the He adsorbed amount while its shear modulus remains constant in a large range of applied pressures. These results suggest that the longitudinal and Rayleigh wave velocities (VL and VR) depend on the He adsorbed amount whereas the transverse wave velocity VT remains constant. read less G. Ori, F. Villemot, L. Viau, A. Vioux, and B. Coasne, “Ionic liquid confined in silica nanopores: molecular dynamics in the isobaric–isothermal ensemble,” Molecular Physics. 2014. link Times cited: 65 Abstract: Molecular dynamics simulations in the isobaric–isothermal en… read more Abstract: Molecular dynamics simulations in the isobaric–isothermal ensemble are used to investigate the structure and dynamics of an ionic liquid confined at ambient temperature and pressure in hydroxylated amorphous silica nanopores. The use of the isobaric–isothermal ensemble allows estimating the effect of confinement and surface chemistry on the density of the confined ionic liquid. The structure of the confined ionic liquid is investigated using density profiles and structural order parameters while its dynamics is assessed by determining the mobility and ionic conductivity of the confined phase. Despite the important screening of the electrostatic interactions (owing to the small Debye length in ionic liquids), the local structure of the confined ionic liquid is found to be mostly driven by electrostatic interactions. We show that both the structure and dynamics of the confined ionic liquid can be described as the sum of a surface contribution arising from the ions in contact with the surface and a bulk-like contribution arising from the ions located in the pore centre; as a result, most properties of the confined ionic liquid are a simple function of the surface-to-volume ratio of the host porous material. In contrast, the ionic conductivity of the confined ionic liquid, which is a collective dynamical property, is found to be similar to the bulk. This study sheds light on the complex behaviour of hybrid materials made up of ionic liquid confined in inorganic porous materials. read less F. Villemot, A. Galarneau, and B. Coasne, “Adsorption and Dynamics in Hierarchical Metal–Organic Frameworks,” Journal of Physical Chemistry C. 2014. link Times cited: 27 Abstract: Adsorption and dynamics in hierarchical metal–organic framew… read more Abstract: Adsorption and dynamics in hierarchical metal–organic frameworks are investigated by means of molecular simulation. The models of hierarchical porous solids are obtained by carving mesopores of different diameters out of a crystal of Cu-BTC (model A) or by inserting a microporous particle of Cu-BTC in an amorphous silica mesopore (model B). We show that the nitrogen adsorption isotherms at 77 K for the solids corresponding to model A can be described as a linear combination of reference adsorption isotherms for pure microporous and mesoporous solids. In contrast, the adsorption isotherms for model B cannot be described accurately as a sum of reference microporous and mesoporous adsorption isotherms. The inserted particle acts as a constriction which helps nucleate the liquid phase within the mesopore so that no capillary condensation hysteresis is observed. The dynamics of nitrogen adsorbed at 77 K inside the porosity of the hierarchical solids is also investigated. The Fickian regime is reached at long t... read less B. W. Ewers and J. Batteas, “Molecular Dynamics Simulations of Alkylsilane Monolayers on Silica Nanoasperities: Impact of Surface Curvature on Monolayer Structure and Pathways for Energy Dissipation in Tribological Contacts,” Journal of Physical Chemistry C. 2012. link Times cited: 31 Abstract: Self-assembled monolayers (SAMs) of alkylsilanes have been c… read more Abstract: Self-assembled monolayers (SAMs) of alkylsilanes have been considered as wear reducing layers in tribological applications, particularly to reduce stiction and wear in microelectromechanical systems (MEMS) devices. Though these films successfully reduce interfacial forces, they are easily damaged during impact and shear. Surface roughness at the nanoscale is believed to play an important role in the failure of these films because it effects both the formation and quality of SAMs, and it focuses interfacial contact forces to very small areas, magnifying the locally applied pressure and shear on the lubricant film. To complement our prior studies employing Fourier transform infrared spectroscopy (FTIR) and atomic force microscopy (AFM) experiments in which silica nanoparticles are used to simulate nanoasperities and to refine our analysis of these films to a molecular level, classical molecular dynamics simulations have been employed to understand the impact of nanoscopic surface curvature on the properties... read less K. Zheng et al., “Electron-beam-assisted superplastic shaping of nanoscale amorphous silica,” Nature Communications. 2010. link Times cited: 292 R. Renou et al., “Investigating ramp wave propagation inside silica glass with laser experiments and molecular simulations.” 2018. link Times cited: 2 Abstract: Under elastic shock compression silica glass exhibits a very… read more Abstract: Under elastic shock compression silica glass exhibits a very specific behaviour. A shock propagating inside a material is usually seen as the propagation of a discontinuity. However in silica glass, shocks are unstable and lead to the propagation of a ramp wave where the shock front becomes gradually larger over time. Ramp waves were already reported in the literature, however their origin remain uncertain. This work presents an original study combining laser shock-induced experiments and molecular dynamics simulation aiming to improve the understanding of the mechanisms involved. Experimental ramp waves were directly observed using shadowgraphy technique allowing for an estimation of the head and tail velocities. Molecular dynamics simulations were carried out in order to reproduce ramp waves and to gain insight into the material properties. Ramp waves were observed for both elastic and plastic shockwaves. In the latter case, the plastic waves were preceded by an elastic ramp precursor. The sound speed, related to the material compressibility, was found to decrease with increasing pressure, as observed experimentally for quasi-static hydrostatic loading, thus providing an explanation for the instabilities that lead to the propagation of ramp waves. read less H. S. Senanayake, P. N. Wimalasiri, S. M. Godahewa, W. Thompson, and J. Greathouse, “Ab Initio-Derived Force Field for Amorphous Silica Interfaces for Use in Molecular Dynamics Simulations,” The Journal of Physical Chemistry C. 2023. link Times cited: 0 A. Mysovsky and A. Paklin, “Molecular Dynamics Modeling of SiO2 Melts and Glass Formation Processes,” Glass Physics and Chemistry. 2023. link Times cited: 0 F. Grigoriev and V. Sulimov, “Atomistic Simulation of Physical Vapor Deposition of Optical Thin Films,” Nanomaterials. 2023. link Times cited: 0 Abstract: A review of the methods and results of atomistic modeling of… read more Abstract: A review of the methods and results of atomistic modeling of the deposition of thin optical films and a calculation of their characteristics is presented. The simulation of various processes in a vacuum chamber, including target sputtering and the formation of film layers, is considered. Methods for calculating the structural, mechanical, optical, and electronic properties of thin optical films and film-forming materials are discussed. The application of these methods to studying the dependences of the characteristics of thin optical films on the main deposition parameters is considered. The simulation results are compared with experimental data. read less S. Jahn, “Molecular Simulations of Oxide and Silicate Melts and Glasses,” Reviews in Mineralogy and Geochemistry. 2022. link Times cited: 6 E. Martin, G. Ori, T.-Q. Duong, M. Boero, and C. Massobrio, “Thermal conductivity of amorphous SiO2 by first-principles molecular dynamics,” Journal of Non-Crystalline Solids. 2022. link Times cited: 6 D. Bowron et al., “Atomic-Spring-like Effect in Glassy Silica-Helium Composites,” The Journal of Physical Chemistry C. 2022. link Times cited: 0 Abstract: .… read more Abstract: . read less P. N. Wimalasiri, N. P. Nguyen, H. S. Senanayake, B. Laird, and W. Thompson, “Amorphous Silica Slab Models with Variable Surface Roughness and Silanol Density for Use in Simulations of Dynamics and Catalysis,” The Journal of Physical Chemistry C. 2021. link Times cited: 9 Y. Cheng, A. Kolesnikov, and A. Ramirez‐Cuesta, “Simulation of Inelastic Neutron Scattering Spectra Directly from Molecular Dynamics Trajectories.,” Journal of chemical theory and computation. 2020. link Times cited: 11 Abstract: Inelastic neutron scattering (INS) is a widely used techniqu… read more Abstract: Inelastic neutron scattering (INS) is a widely used technique to study atomic and molecular vibrations. With the increasing complexity of materials and thus the INS spectra, being able to simulate the spectra from various atomistic models becomes an essential step and also a major bottleneck for INS data analysis. The conventional approach using density functional theory and lattice dynamics often falls short when the materials of interest are complex (e.g., defective, disordered, heterogeneous, amorphous, large-scale), for which molecular dynamics driven by an interatomic force field is a more common approach. In this paper, we demonstrate a method to directly convert molecular dynamics trajectories into simulated INS spectra, including not only fundamental but also higher order excitations. The results are compared with data collected on various representative samples from different neutron spectrometers. This development will open great opportunities by providing the key tool to perform in-depth analysis of INS data and to validate and optimize computer models. read less D. Wang, L. Wang, L. Zhang, C. Cai, N. Li, and M. Yang, “A modified model for estimating excess adsorption of methane in moist nanoporous silica,” Chemical Physics. 2020. link Times cited: 7 P. Maximiano, L. Durães, and P. Simões, “Overview of Multiscale Molecular Modeling and Simulation of Silica Aerogels,” Industrial & Engineering Chemistry Research. 2019. link Times cited: 11 Abstract: Molecular simulation has become an integral and invaluable p… read more Abstract: Molecular simulation has become an integral and invaluable part of Chemical Product Engineering, as it provides fundamental and indispensable insights for a rational product design. Silica aerogels... read less S. Gelin, D. Poinot, S. Châtel, P. Calba, and A. Lemaître, “Microstructural origin of compressive in situ stresses in electron-gun-evaporated silica thin films,” Physical Review Materials. 2019. link Times cited: 1 C. Scherer, F. Schmid, M. Letz, and J. Horbach, “Structure and dynamics of B2O3 melts and glasses: From ab initio to classical molecular dynamics simulations,” Computational Materials Science. 2019. link Times cited: 15 F. Bamer, F. Ebrahem, and B. Markert, “Plasticity in vitreous silica induced by cyclic tension considering rate-dependence: Role of the network topology,” Journal of Non-Crystalline Solids. 2019. link Times cited: 21 F. Ebrahem, F. Bamer, and B. Markert, “The influence of the network topology on the deformation and fracture behaviour of silica glass: A molecular dynamics study,” Computational Materials Science. 2018. link Times cited: 33 A. D. Parmar, S. Sengupta, and S. Sastry, “Power law relationship between diffusion coefficients in multi-component glass forming liquids,” The European Physical Journal E. 2018. link Times cited: 2 C. Scherer, J. Horbach, F. Schmid, and M. Letz, “Negative thermal expansion of quartz glass at low temperatures: An ab initio simulation study,” Journal of Non-crystalline Solids. 2017. link Times cited: 7 A. Carré, S. Ispas, J. Horbach, and W. Kob, “Developing empirical potentials from ab initio simulations: The case of amorphous silica,” Computational Materials Science. 2016. link Times cited: 24 B. Cowen and M. El-Genk, “Probability-based threshold displacement energies for oxygen and silicon atoms in α-quartz silica,” Computational Materials Science. 2016. link Times cited: 17 O. Gedeon, “Molecular dynamics of vitreous silica — Variations in potentials and simulation regimes,” Journal of Non-crystalline Solids. 2015. link Times cited: 6 B. Cowen and M. El-Genk, “On force fields for molecular dynamics simulations of crystalline silica,” Computational Materials Science. 2015. link Times cited: 31 I. Bryukhanov, A. Rybakov, V. Kovalev, and A. Larin, “Influence of carbonate species on elastic properties of NaX and NaKX zeolites,” Microporous and Mesoporous Materials. 2014. link Times cited: 8 A. Jacob, A. A. Gray-Weale, and P. Masset, “Molecular Dynamics Simulation of SiO2 and SiO2‐CaO Mixtures.” 2014. link Times cited: 0 K. Okhotnikov, B. Stevensson, and M. Edén, “New interatomic potential parameters for molecular dynamics simulations of rare-earth (RE = La, Y, Lu, Sc) aluminosilicate glass structures: exploration of RE3+ field-strength effects.,” Physical chemistry chemical physics : PCCP. 2013. link Times cited: 39 Abstract: Sets of self-consistent oxygen-rare earth (RE = La, Y, Lu, S… read more Abstract: Sets of self-consistent oxygen-rare earth (RE = La, Y, Lu, Sc) interatomic potential parameters are derived using a force-matching procedure and utilized in molecular dynamics (MD) simulations for exploring the structures of RE2O3-Al2O3-SiO2 glasses that feature a fixed molar ratio n(Al)/n(Si) = 1 but variable RE contents. The structures of RE aluminosilicate (AS) glasses depend markedly on the RE(3+) cation field strength (CFS) over both short and intermediate length-scales. We explore these dependencies for glasses incorporating the cations La(3+), Y(3+), Lu(3+) and Sc(3+), whose CFSs increase due to the concomitant shrinkage of the ionic radii: R(La) > R(Y) > R(Lu) > R(Sc). This trend is mirrored in decreasing average RE(3+) coordination numbers (Z(RE)) from Z(La) = 6.4 to Z(Sc) = 5.4 in the MD-derived data. However, overall the effects from RE(3+) CFS elevations on the local glass structures are most pronounced in the O and {Al([4]), Al([5]), Al([6])} speciations. The former display minor but growing populations of O([0]) ("free oxygen ion") and O([3]) ("oxygen tricluster") moieties. The abundance of AlO5 polyhedra increases significantly from ≈10% in La-based glasses to ≈30% in their Sc counterparts at the expense of the overall dominating AlO4 tetrahedra, whereas the amounts of AlO6 groups remain <5% throughout. We also discuss the Si([4])/Al([p]) (p = 4, 5, 6) intermixing and the nature of their oxygen bridges, where the degree of edge-sharing increases together with the RE(3+) CFS. read less E. Paek and G. Hwang, “A computational analysis of graphene adhesion on amorphous silica,” Journal of Applied Physics. 2013. link Times cited: 19 Abstract: We present a computational analysis of the morphology and ad… read more Abstract: We present a computational analysis of the morphology and adhesion energy of graphene on the surface of amorphous silica (a-SiO2). The a-SiO2 model surfaces obtained from the continuous random network model-based Metropolis Monte Carlo approach show Gaussian-like height distributions with an average standard deviation of 2.91 ± 0.56 A, in good agreement with existing experimental measurements (1.68–3.7 A). Our calculations clearly demonstrate that the optimal adhesion between graphene and a-SiO2 occurs when the graphene sheet is slightly less corrugated than the underlying a-SiO2 surface. From morphology analysis based on fast Fourier transform, we find that graphene may not conform well to the relatively small jagged features of the a-SiO2 surface with wave lengths of smaller than 2 nm, although it generally exhibits high-fidelity conformation to a-SiO2 topographic features. For 18 independent samples, on average the van der Waals interaction at the graphene/a-SiO2 interface is predicted to vary from Evd... read less F. Yuan and L. Huang, “Molecular dynamics simulation of amorphous silica under uniaxial tension: From bulk to nanowire,” Journal of Non-crystalline Solids. 2012. link Times cited: 62 M. Kim, K. Khoo, and J. Chelikowsky, “Simulating liquid and amorphous silicon dioxide using real-space pseudopotentials,” Physical Review B. 2012. link Times cited: 15 F. Angeli, O. Villain, S. Schuller, S. Ispas, and T. Charpentier, “Insight into sodium silicate glass structural organization by multinuclear NMR combined with first-principles calculations,” Geochimica et Cosmochimica Acta. 2011. link Times cited: 110 T. Soules, G. Gilmer, M. Matthews, J. Stolken, and M. Feit, “Silica Molecular Dynamic Force Fields- A Practical Assessment,” Journal of Non-crystalline Solids. 2010. link Times cited: 55 B. Cowen and M. El-Genk, “Bond-order reactive force fields for molecular dynamics simulations of crystalline silica,” Computational Materials Science. 2016. link Times cited: 15 G. Ori, C. Massobrio, A. Bouzid, and B. Coasne, “Molecular Modeling of Glassy Surfaces.” 2015. link Times cited: 1 E. R. Cope, “Dynamic properties of materials : phonons from neutron scattering.” 2010. link Times cited: 2 Abstract: Related article - "FORTRAN routines for the new SQW and… read more Abstract: Related article - "FORTRAN routines for the new SQW and PDF modules of GULP and TOBYFIT" at http://www.dspace.cam.ac.uk/handle/1810/225173 in the Data sets - Mineral Science Collection read less J. Singh and S. Singh, “A review on Machine learning aspect in physics and mechanics of glasses,” Materials Science and Engineering: B. 2022. link Times cited: 10 H. Liu et al., “Challenges and opportunities in atomistic simulations of glasses: a review,” Comptes Rendus. Géoscience. 2022. link Times cited: 8 Abstract: . Atomistic modeling and simulations have been pivotal in ou… read more Abstract: . Atomistic modeling and simulations have been pivotal in our understanding of the glassy state. Indeed, atomistic modeling o ff ers direct access to the structure and dynamics of atoms in glasses—which is typically hidden from conventional experiments. Simulations also o ff er a more economical, faster alternative to systematic experiments to decode composition-property relationships and accelerate the discovery of new glasses with desirable properties and functionalities. However, the atomistic modeling of glasses remains plagued by a series of challenges, e read less I. A. Balyakin, S. Rempel, R. Ryltsev, and A. Rempel, “Deep machine learning interatomic potential for liquid silica.,” Physical review. E. 2020. link Times cited: 16 Abstract: The use of machine learning to develop neural network potent… read more Abstract: The use of machine learning to develop neural network potentials (NNP) representing the interatomic potential energy surface allows us to achieve an optimal balance between accuracy and efficiency in computer simulation of materials. A key point in developing such potentials is the preparation of a training dataset of ab initio trajectories. Here we apply a deep potential molecular dynamics (DeePMD) approach to develop NNP for silica, which is the representative glassformer widely used as a model system for simulating network-forming liquids and glasses. We show that the use of a relatively small training dataset of high-temperature ab initio configurations is enough to fabricate NNP, which describes well both structural and dynamical properties of liquid silica. In particular, we calculate the pair correlation functions, angular distribution function, velocity autocorrelation functions, vibrational density of states, and mean-square displacement and reveal a close agreement with ab initio data. We show that NNP allows us to expand significantly the time-space scales achievable in simulations and thus calculating dynamical and transport properties with more accuracy than that for ab initio methods. We find that developed NNP allows us to describe the structure of the glassy silica with satisfactory accuracy even though no low-temperature configurations were included in the training procedure. The results obtained open up prospects for simulating structural and dynamical properties of liquids and glasses via NNP. read less B. Deng, Y. Shi, and F. Yuan, “Investigation on the structural origin of low thermal expansion coefficient of fused silica,” Materialia. 2020. link Times cited: 9 H. Liu, Z. Fu, K. Yang, X. Xu, and M. Bauchy, “Machine learning for glass science and engineering: A review,” Journal of Non-Crystalline Solids. 2019. link Times cited: 79 H. Liu, Z. Fu, Y. Li, N. F. A. Sabri, and M. Bauchy, “Balance between accuracy and simplicity in empirical forcefields for glass modeling: Insights from machine learning,” Journal of Non-Crystalline Solids. 2019. link Times cited: 19 H. Liu, Z. Fu, Y. Li, N. F. A. Sabri, and M. Bauchy, “Parameterization of empirical forcefields for glassy silica using machine learning,” MRS Communications. 2019. link Times cited: 16 Abstract: The development of reliable, yet computationally efficient i… read more Abstract: The development of reliable, yet computationally efficient interatomic forcefields is key to facilitate the modeling of glasses. However, the parameterization of novel forcefields is challenging as the high number of parameters renders traditional optimization methods inefficient or subject to bias. Here, we present a new parameterization method based on machine learning, which combines ab initio molecular dynamics simulations and Bayesian optimization. By taking the example of glassy silica, we show that our method yields a new interatomic forcefield that offers an unprecedented agreement with ab initio simulations. This method offers a new route to efficiently parameterize new interatomic forcefields for disordered solids in a non-biased fashion. read less B. Coasne et al., “Poroelastic theory applied to the adsorption-induced deformation of vitreous silica.,” The journal of physical chemistry. B. 2014. link Times cited: 25 Abstract: When vitreous silica is submitted to high pressures under a … read more Abstract: When vitreous silica is submitted to high pressures under a helium atmosphere, the change in volume observed is much smaller than expected from its elastic properties. It results from helium penetration into the interstitial free volume of the glass network. We present here the results of concurrent spectroscopic experiments using either helium or neon and molecular simulations relating the amount of gas adsorbed to the strain of the network. We show that a generalized poromechanical approach, describing the elastic properties of microporous materials upon adsorption, can be applied successfully to silica glass in which the free volume exists only at the subnanometer scale. In that picture, the adsorption-induced deformation accounts for the small apparent compressibility of silica observed in experiments. read less B. Coasne et al., “Enhanced mechanical strength of zeolites by adsorption of guest molecules.,” Physical chemistry chemical physics : PCCP. 2011. link Times cited: 65 Abstract: We report a molecular simulation study of the mechanical pro… read more Abstract: We report a molecular simulation study of the mechanical properties of microporous zeolites filled with guest molecules. We show that the adsorption of molecules in the micropores of the material increases its bulk modulus. These results provide a microscopic picture of the deactivation of pressure-induced amorphization by incorporation of molecules. read less L. Huang and J. Kieffer, “Challenges in modeling mixed ionic-covalent glass formers.” 2015. link Times cited: 11 A. Koneru et al., “Multi-reward reinforcement learning based development of inter-atomic potential models for silica,” npj Computational Materials. 2023. link Times cited: 0 J.-C. Griesser, L. Frérot, J. A. Oldenstaedt, M. Müser, and L. Pastewka, “Analytic elastic coefficients in molecular calculations: Finite strain, nonaffine displacements, and many-body interatomic potentials,” Physical Review Materials. 2023. link Times cited: 1 Abstract: Elastic constants are among the most fundamental and importa… read more Abstract: Elastic constants are among the most fundamental and important properties of solid materials, which is why they are routinely characterized in both experiments and simulations. While conceptually simple, the treatment of elastic constants is complicated by two factors not yet having been concurrently discussed: finite-strain and non-affine, internal displacements. Here, we revisit the theory behind zero-temperature, finite-strain elastic constants and extend it to explicitly consider non-affine displacements. We further present analytical expressions for second-order derivatives of the potential energy for two-body and generic many-body interatomic potentials, such as cluster and empirical bond-order potentials. Specifically, we revisit the elastic constants of silicon, silicon carbide and silicon dioxide under hydrostatic compression and dilatation. Based on existing and new results, we outline the effect of multiaxial stress states as opposed to volumetric deformation on the limits of stability of their crystalline lattices. read less F. Bamer, F. Ebrahem, B. Markert, and B. Stamm, “Molecular Mechanics of Disordered Solids,” Archives of Computational Methods in Engineering. 2023. link Times cited: 5 A. Pedone, M. Bertani, L. Brugnoli, and A. Pallini, “Interatomic potentials for oxide glasses: Past, present, and future,” Journal of Non-Crystalline Solids: X. 2022. link Times cited: 2 A. Tirelli and K. Nakano, “Topological Data Analysis for Revealing the Structural Origin of Density Anomalies in Silica Glass.,” The journal of physical chemistry. B. 2022. link Times cited: 1 Abstract: Topological data analysis (TDA) is a newly emerging and powe… read more Abstract: Topological data analysis (TDA) is a newly emerging and powerful tool for understanding the medium-range structure ordering of multiscale data. This study investigates the density anomalies observed during the cooling of liquid silica from a topological point of view using TDA. The density of liquid silica does not monotonically increase during cooling; it instead shows a maximum and minimum. Despite tremendous efforts, the structural origin of these density anomalies is not clearly understood. Our approach reveals that the one-dimensional topology of the -Si-Si- network changes at the temperatures at which the maximum and minimum densities are observed in our MD simulations, while those of the -O-O- and -Si-O- networks change at lower temperatures. Our ring analysis motivated by the TDA outcomes reveals that quantitative changes in -Si-Si- rings occur at the temperatures where the density is maximized and minimized, while those of the -O-O- and -Si-O- rings occur at lower temperatures; such findings are perfectly consistent with our TDA results. Our work demonstrates the value of new topological techniques in understanding the transitions in glassy materials and sheds light on the characterization of glass-liquid transitions. read less L. C. Erhard, J. Rohrer, K. Albe, and V. L. Deringer, “A machine-learned interatomic potential for silica and its relation to empirical models,” npj Computational Materials. 2022. link Times cited: 32 M. Santoro et al., “Insertion of Oxygen and Nitrogen in the Siliceous Zeolite TON at High Pressure,” The Journal of Physical Chemistry C. 2021. link Times cited: 0 H. Liu, Y. Li, Z. Fu, K. Li, and M. Bauchy, “Exploring the landscape of Buckingham potentials for silica by machine learning: Soft vs hard interatomic forcefields.,” The Journal of chemical physics. 2020. link Times cited: 9 Abstract: Interatomic forcefields for silicate glasses often rely on p… read more Abstract: Interatomic forcefields for silicate glasses often rely on partial (rather than formal) charges to describe the Coulombic interactions between ions. Such forcefields can be classified as "soft" or "hard" based on the value of the partial charge attributed to Si atoms, wherein softer forcefields rely on smaller partial charges. Here, we use machine learning to efficiently explore the "landscape" of Buckingham forcefields for silica, that is, the evolution of the overall forcefield accuracy as a function of the forcefield parameters. Interestingly, we find that soft and hard forcefields correspond to two distinct, yet competitive local minima in this landscape. By analyzing the structure of the silica configurations predicted by soft and hard forcefields, we show that although soft and hard potentials offer competitive accuracy in describing the short-range order structure, soft potentials feature a higher ability to describe the medium-range order. read less A. Baroni et al., “Many-body effects at the origin of structural transitions in B2O3.,” The Journal of chemical physics. 2019. link Times cited: 2 Abstract: The structural properties of glassy diboron trioxide, g-B2O3… read more Abstract: The structural properties of glassy diboron trioxide, g-B2O3, are investigated from ambient to high pressure conditions using two types of atomic force-field models that account for many-body effects. These models are parameterized by a dipole- and force-fitting procedure of reference datasets created via first-principles calculations on a series of configurations. The predictions of the models are tested against experimental data, where particular attention is paid to the structural transitions in g-B2O3 that involve changes to both the short- and medium-range order. The models outperform those previously devised, where improvement originates from the incorporation of two key physical ingredients, namely, (i) the polarizability of the oxide ion and (ii) the ability of an oxide ion to change both size and shape in response to its coordination environment. The results highlight the importance of many-body effects for accurately modeling this challenging system. read less M. Bouhadja and N. Jakse, “Structural and dynamic properties of aluminosilicate melts: a molecular dynamics study,” Journal of Physics: Condensed Matter. 2019. link Times cited: 10 Abstract: In the present work, the structural and dynamic properties o… read more Abstract: In the present work, the structural and dynamic properties of aluminosilicates (Al2O3)x-(SiO2)1−x (AS) as a function of the Al2O3 concentration x are studied by means of molecular dynamics simulations. Firstly, the parametrization of the Born–Mayer–Huggins type potential developed recently for the more general CaO-Al2O3-SiO2 ternary system is assessed. Comparison of local structural properties, such as the x-ray structure factor, partial pair-correlation functions, distributions of coordination numbers and bond angles, as well as the dynamics through the viscosity and self-diffusion coefficients to experimental data and other molecular dynamics simulations found in the literature, shows that this potential is transferable to AS melts for all compositions and is more reliable than other empirical potentials used so far. The evolution of viscosity with temperature in stable liquid and undercooled regions is studied in the whole composition range and results show a progressive increase of the fragility with increasing Al2O3 content correlated to that of local structural entities like the triply bonded oxygen (TBO), AlO5 and AlO6. read less B. Cui and E. Terentjev, “Comparison of the Helmholtz, Gibbs, and collective-modes methods to obtain nonaffine elastic constants,” Journal of the Mechanics and Physics of Solids. 2019. link Times cited: 4 B. Cui, A. Zaccone, and D. Rodney, “Nonaffine lattice dynamics with the Ewald method reveals strongly nonaffine elasticity of α-quartz.,” The Journal of chemical physics. 2019. link Times cited: 14 Abstract: A lattice dynamical formalism based on nonaffine response th… read more Abstract: A lattice dynamical formalism based on nonaffine response theory is derived for noncentrosymmetric crystals, accounting for long-range interatomic interactions using the Ewald method. The framework takes equilibrated static configurations as input to compute the elastic constants in excellent agreement with both experimental data and calculations under strain. Besides this methodological improvement, which enables faster evaluation of elastic constants without the need of explicitly simulating the deformation process, the framework provides insights into the nonaffine contribution to the elastic constants of α-quartz. It turns out that, due to the noncentrosymmetric lattice structure, the nonaffine (softening) correction to the elastic constants is very large, such that the overall elastic constants are at least 3-4 times smaller than the affine Born-Huang estimate. read less D. Melgar, M. Lauricella, G. O’Brien, and N. J. English, “Amplitude effects on seismic velocities: How low can we go?,” The Journal of chemical physics. 2019. link Times cited: 1 Abstract: α-quartz is one of the most important SiO2 polymorphs becaus… read more Abstract: α-quartz is one of the most important SiO2 polymorphs because it is the basis of very common minerals, especially for seabed materials with geoscientific importance. The elastic characterization of these materials is particularly relevant when the properties governing phonon and sound propagation are involved. These studies are especially interesting for oil exploration purposes. Recently, we published a new method that constitutes to the best of our knowledge the first attempt to recreate longitudinal and transversal perturbations in a simulation box to observe their propagation through the crystal by means of a set of descriptors [D. Melgar et al., J. Phys. Chem. C 122, 3006-3013 (2018)]. The agreement with the experimental S- and P-wave velocities was rather excellent. Thus, an effort has been undertaken to deepen the particularities of this new methodology. Here, bearing in mind this encouraging initial methodology-development progress, we deepen our knowledge of the particularities of this new methodology in presenting a systematic investigation of the implementation of the perturbation source. This includes new ways of creating the perturbation, as well as analyzing the possible effects the perturbation amplitude could have on the resultant velocities. In addition, different force fields were tested to describe the interatomic interactions. The lack of dependence of the seismic velocities on the way the perturbation is created and the perturbation amplitude, and the good agreement with the experimental results are the main reasons that allow the definition of this new methodology as robust and reliable. These qualities are consolidated by the physical behavior of the calculated velocities in the presence of vacancies and under stress. The development of this method opens up a new line of research of calculating seismic velocities for geophysically relevant materials in a systematic way, with full control not only on the sample features (composition, porosity, vacancies, stress, etc.) but also on the particularities of perturbation itself, as well as determining optimal system-response metrics. read less S. Sundararaman, L. Huang, S. Ispas, and W. Kob, “New interaction potentials for alkali and alkaline-earth aluminosilicate glasses.,” The Journal of chemical physics. 2018. link Times cited: 36 Abstract: We apply a recently developed optimization scheme to obtain … read more Abstract: We apply a recently developed optimization scheme to obtain effective potentials for alkali and alkaline-earth aluminosilicate glasses that contain lithium, sodium, potassium, or calcium as modifiers. As input data for the optimization, we used the radial distribution functions of the liquid at high temperature generated by means of ab initio molecular dynamics simulations and density and elastic modulus of glass at room temperature from experiments. The new interaction potentials are able to reproduce reliably the structure and various mechanical and vibrational properties over a wide range of compositions for binary silicates. We have tested these potentials for various ternary systems and find that they are transferable and can be mixed, thus allowing us to reproduce and predict the structure and properties of multicomponent glasses. read less F. Grigoriev, V. Sulimov, and A. Tikhonravov, “Simulation of the optical coating deposition,” Advanced Optical Technologies. 2018. link Times cited: 5 Abstract: A brief review of the mathematical methods of thin-film grow… read more Abstract: A brief review of the mathematical methods of thin-film growth simulation and results of their applications is presented. Both full-atomistic and multi-scale approaches that were used in the studies of thin-film deposition are considered. The results of the structural parameter simulation including density profiles, roughness, porosity, point defect concentration, and others are discussed. The application of the quantum level methods to the simulation of the thin-film electronic and optical properties is considered. Special attention is paid to the simulation of the silicon dioxide thin films. read less S. Izvekov, N. S. Weingarten, and E. F. C. Byrd, “Effect of a core-softened O-O interatomic interaction on the shock compression of fused silica,” Journal of Chemical Physics. 2018. link Times cited: 2 Abstract: Isotropic soft-core potentials have attracted considerable a… read more Abstract: Isotropic soft-core potentials have attracted considerable attention due to their ability to reproduce thermodynamic, dynamic, and structural anomalies observed in tetrahedral network-forming compounds such as water and silica. The aim of the present work is to assess the relevance of effective core-softening pertinent to the oxygen-oxygen interaction in silica to the thermodynamics and phase change mechanisms that occur in shock compressed fused silica. We utilize the MD simulation method with a recently published numerical interatomic potential derived from an ab initio MD simulation of liquid silica via force-matching. The resulting potential indicates an effective shoulder-like core-softening of the oxygen-oxygen repulsion. To better understand the role of the core-softening we analyze two derivative force-matching potentials in which the soft-core is replaced with a repulsive core either in the three-body potential term or in all the potential terms. Our analysis is further augmented by a comparison ... read less S. Halbert, S. Ispas, C. Raynaud, and O. Eisenstein, “Modelling the surface of amorphous dehydroxylated silica: the influence of the potential on the nature and density of defects,” New Journal of Chemistry. 2018. link Times cited: 5 Abstract: Molecular dynamics (MD) calculations using two effective pai… read more Abstract: Molecular dynamics (MD) calculations using two effective pair potentials BKS and CHIK have been carried out to represent the structures of the amorphous dehydroxylated silica surface in liquid (3400 and 2500 K) and glassy (1000 and 300 K) states. Previous studies have shown that CHIK performs better to represent the properties of bulk silica and this may result from the different values of the Si–O and O–O parameters, as well as from an additional Si⋯Si short range interaction term. The two potentials show similar trends in the change of structures upon going from the internal to the surface parts of the samples. However, the additional flexibility, likely due to the presence of the Si⋯Si short range interaction, relative to BKS, results in a surface which has overall more defects like in particular small 2-membered rings (SiO2)2 and dangling Si–O bonds. This cumulated density of defects corresponds qualitatively to the density of functionalized Si–OH obtained experimentally. This study shows that CHIK gives a good representation of the silica surface. read less T. Dufils, N. Folliet, B. Mantisi, N. Sator, and B. Guillot, “Properties of magmatic liquids by molecular dynamics simulation: The example of a MORB melt,” Chemical Geology. 2017. link Times cited: 18 B. Cowen and M. El-Genk, “Estimates of point defect production in α-quartz using molecular dynamics simulations,” Modelling and Simulation in Materials Science and Engineering. 2017. link Times cited: 5 Abstract: Molecular dynamics (MD) simulations are performed to investi… read more Abstract: Molecular dynamics (MD) simulations are performed to investigate the production of point defects in α-quartz by oxygen and silicon primary knock-on atoms (PKAs) of 0.25–2 keV. The Wigner–Seitz (WS) defect analysis is used to identify the produced vacancies, interstitials, and antisites, and the coordination defect analysis is used to identify the under and over-coordinated oxygen and silicon atoms. The defects at the end of the ballistic phase and the residual defects, after annealing, increase with increased PKA energy, and are statistically the same for the oxygen and silicon PKAs. The WS defect analysis results show that the numbers of the oxygen vacancies and interstitials (VO, Oi) at the end of the ballistic phase is the highest, followed closely by those of the silicon vacancies and interstitials (VSi, Sii). The number of the residual oxygen and silicon vacancies and interstitials are statistically the same. In addition, the under-coordinated OI and SiIII, which are the primary defects during the ballistic phase, have high annealing efficiencies (>89%). The over-coordinated defects of OIII and SiV, which are not nearly as abundant in the ballistic phase, have much lower annealing efficiencies (<63%) that decrease with increased PKA energy. read less W. Kob and S. Ispas, “First‐principles Simulations of Glass‐formers,” Encyclopedia of Glass Science, Technology, History, and Culture. 2016. link Times cited: 3 Abstract: In this article we review results of computer simulation of … read more Abstract: In this article we review results of computer simulation of glasses carried out using first principles approaches, notably density functional theory. We start with a brief introduction to this method and compare the pros and cons of this approach with the ones of simulations with classical potentials. This is followed by a discussion of simulation results of various glass-forming systems that have been obtained via ab initio simulations and that demonstrate the usefulness of this approach to understand the properties of glasses on the microscopic level. read less S. Izvekov and B. Rice, “A new parameter-free soft-core potential for silica and its application to simulation of silica anomalies.,” The Journal of chemical physics. 2015. link Times cited: 7 Abstract: A core-softening of the effective interaction between oxygen… read more Abstract: A core-softening of the effective interaction between oxygen atoms in water and silica systems and its role in developing anomalous thermodynamic, transport, and structural properties have been extensively debated. For silica, the progress with addressing these issues has been hampered by a lack of effective interaction models with explicit core-softening. In this work, we present an extension of a two-body soft-core interatomic force field for silica recently reported by us [S. Izvekov and B. M. Rice, J. Chem. Phys. 136(13), 134508 (2012)] to include three-body forces. Similar to two-body interaction terms, the three-body terms are derived using parameter-free force-matching of the interactions from ab initio MD simulations of liquid silica. The derived shape of the O-Si-O three-body potential term affirms the existence of repulsion softening between oxygen atoms at short separations. The new model shows a good performance in simulating liquid, amorphous, and crystalline silica. By comparing the soft-core model and a similar model with the soft-core suppressed, we demonstrate that the topology reorganization within the local tetrahedral network and the O-O core-softening are two competitive mechanisms responsible for anomalous thermodynamic and kinetic behaviors observed in liquid and amorphous silica. The studied anomalies include the temperature of density maximum locus and anomalous diffusivity in liquid silica, and irreversible densification of amorphous silica. We show that the O-O core-softened interaction enhances the observed anomalies primarily through two mechanisms: facilitating the defect driven structural rearrangements of the silica tetrahedral network and modifying the tetrahedral ordering induced interactions toward multiple characteristic scales, the feature which underlies the thermodynamic anomalies. read less R. Vuilleumier, A. Seitsonen, N. Sator, and B. Guillot, “Carbon dioxide in silicate melts at upper mantle conditions: Insights from atomistic simulations,” Chemical Geology. 2015. link Times cited: 30 D. Corradini, Y. Ishii, N. Ohtori, and M. Salanne, “DFT-based polarizable force field for TiO2 and SiO2,” Modelling and Simulation in Materials Science and Engineering. 2015. link Times cited: 9 Abstract: TiO2 and SiO2 are materials with unique importance in materi… read more Abstract: TiO2 and SiO2 are materials with unique importance in materials science. They are often modelled using conventional force fields, but including polarization effects is compulsory for enhancing the accuracy of the simulations. Here we parameterize a force field for the two materials in the framework of the polarizable ion model. The parameterization is performed via a generalized force-fitting methodology using DFT calculations as reference data. We show that it is possible to generate a force field in which the same parameters are used for the oxide ion in both SiO2 and TiO2, and which is able to reproduce accurately the equilibrium structure of their various crystalline polymorphs, as well as glassy silica. read less J. Harvey, A. Gheribi, and P. Asimow, “A self-consistent optimization of multicomponent solution properties: Ab initio molecular dynamic simulations and the MgO–SiO 2 miscibility gap under pressure,” Geochimica et Cosmochimica Acta. 2015. link Times cited: 6 J. Habasaki and K. Ngai, “Molecular dynamics study of network statistics in lithium disilicate: Q(n) distribution and the pressure-volume diagram.,” The Journal of chemical physics. 2013. link Times cited: 17 Abstract: Molecular dynamics simulations have been performed to study … read more Abstract: Molecular dynamics simulations have been performed to study the structures along the pressure-volume diagram of network-glasses and melts exemplified by the lithium disilicate system. Experimentally, densification of the disilicate glass by elevated pressure is known and this feature is reasonably reproduced by the simulations. During the process of densification or decompression of the system, the statistics of Q(n) (i.e., SiO4 tetrahedron unit with n bridging oxygen linked to the silicon atom where n = 0, 1, 2, 3, or 4) change, and the percentage of the Q3 structures show the maximum value near atmospheric pressure at around T(g). Changes of Q(n) distribution are driven by the changes of volume (or pressure) and are explained by the different volumes of structural units. Furthermore, some pairs of network structures with equi-volume, but having different distributions of Q(n) (or different heterogeneity), are found. Therefore, for molecular dynamics simulations of the Q(n) distributions, it is important to take into account the complex phase behavior including poly-structures with different heterogeneities as well as the position of the system in the P-V-T diagram. read less T. Köhler, M. Turowski, H. Ehlers, M. Landmann, D. Ristau, and T. Frauenheim, “Computational approach for structure design and prediction of optical properties in amorphous TiO2 thin-film coatings,” Journal of Physics D: Applied Physics. 2013. link Times cited: 26 Abstract: We have investigated the structural and electronic propertie… read more Abstract: We have investigated the structural and electronic properties of amorphous TiO2 using molecular dynamics (MD) simulations based on ab initio density functional theory, a numerically efficient density-functional-based tight-binding approach and classical many-body potentials. The lower level approximations are successively validated by the higher level ones through comparison of the calculated structural and electronic properties. The classical results reproduce all relevant structural features of a-TiO2 as obtained by quantum-mechanical simulation and reproduce the experimentally observed reduced radial distribution function. This gives convincing justification for the use of classical MD in the simulation of ion beam sputtering synthesis of large-area amorphous thin films. Cross-correlation of electronic data with the statistics of disorder-induced under- and over-coordination is derived as a basis for evaluating the optical quality of thin-film coatings. read less L. Cheng, J. A. Morrone, and B. Berne, “Structure and Dynamics of Acetonitrile Confined in a Silica Nanopore,” Journal of Physical Chemistry C. 2012. link Times cited: 37 Abstract: Acetonitrile confined in silica nanopores with surfaces of v… read more Abstract: Acetonitrile confined in silica nanopores with surfaces of varying functionality is studied by means of molecular dynamics simulation. The hydrogen-bonding interaction between the surface and the liquid is parametrized by means of first-principles molecular dynamics simulations. It is found that acetonitrile orders into bilayer like structures near the surface, in agreement with prior simulations and experiments. A newly developed method is applied to calculate relevant time correlation functions for molecules in different layers of the pore. This method takes into account the short lifetimes of the molecules in the layers. We compare this method with prior techniques that do not take this lifetime into account and discuss their pitfalls. We show that in agreement with experiment, the dynamics of the system may be described by a two population model that accounts for bulk-like relaxation in the center and frustrated dynamics near the surface of the pore. Specific hydrogen-bonding interactions are found to... read less B. Guillot and N. Sator, “Noble gases in high-pressure silicate liquids: A computer simulation study,” Geochimica et Cosmochimica Acta. 2011. link Times cited: 42 M. Salanne and P. Madden, “Polarization effects in ionic solids and melts,” Molecular Physics. 2011. link Times cited: 127 Abstract: Ionic solids and melts are compounds in which the interactio… read more Abstract: Ionic solids and melts are compounds in which the interactions are dominated by electrostatic effects. However, the polarization of the ions also plays an important role in many respects as has been clarified in recent years thanks to the development of realistic polarizable interaction potentials. After detailing these models, we illustrate the importance of polarization effects on a series of examples concerning the structural properties, such as the stabilization of particular crystal structures or the formation of highly-coordinated multivalent ions in the melts, as well as the dynamic properties such as the diffusion of ionic species. The effects on the structure of molten salt interfaces (with vacuum and electrified metal) is also described. Although most of the results described here concern inorganic compounds (molten fluorides and chlorides, ionic oxides...), the particular case of the room-temperature ionic liquids, a special class of molten salts in which at least one species is organic, will also be briefly discussed to indicate how the ideas gained from the study of ‘simple’ molten salts are being transferred to these more complex systems. read less M. Tokuyama, “Universality in self-diffusion of atoms among distinctly different glass-forming liquids.,” The journal of physical chemistry. B. 2011. link Times cited: 11 Abstract: The long-time self-diffusion coefficients D(S)(L) in distinc… read more Abstract: The long-time self-diffusion coefficients D(S)(L) in distinctly different glass-forming liquids are analyzed from a unified point of view recently proposed by the present author. It is shown that as long as the systems are in equilibrium, they are all described by the following two types of master curves, depending on whether the control parameter is intensive or extensive: D(S)(L)(x) = d(0)x(-1)(1 - x)(2+η) exp[cx(3+η)(1 - x)(2+η)] for a reduced intensive control parameter x, such as a reduced inverse temperature, and D(S)(L)(x) = d(0)x(-1)(1 - x)(2) for a reduced extensive control parameter x, such as a reduced volume fraction, where d(0) and c are constant. Here, the exponent η (≠0) results from many-body correlations in a supercooled liquid state. The constants η and c depend on the systems and are given by (η,c) = (4/3,62) for fragile liquids, (5/3, 62) for strong liquids, and (0,0) for other glass-forming systems in which the peak heights of their non-Gaussian parameters are always much less than 1.0. It is also shown that all of the data for the diffusion coefficient start to deviate from the master curves at lower temperatures (or higher volume fraction), where the systems become out of equilibrium, leading to a glass state. read less I. Saika-Voivod, H. King, P. Tartaglia, F. Sciortino, and E. Zaccarelli, “Silica through the eyes of colloidal models—when glass is a gel,” Journal of Physics: Condensed Matter. 2011. link Times cited: 11 Abstract: We perform molecular dynamics simulations of ‘floating bond’… read more Abstract: We perform molecular dynamics simulations of ‘floating bond’ (FB) models of network-forming liquids and compare the structure and dynamics against the BKS model of silica (van Beest et al 1990 Phys. Rev. Lett. 64 1955), with the aim of gaining a better understanding of glassy silica in terms of the variety of non-ergodic states seen in colloids. At low densities, all the models form tetrahedral networks. At higher densities, tailoring the FB model to allow a higher number of bonds does not capture the structure seen in BKS. Upon rescaling the time and length in order to compare mean squared displacements between models, we find that there are significant differences in the temperature dependence of the diffusion coefficient at high density. Additionally, the FB models show a greater range in variability in the behavior of the non-ergodicity parameter and caging length, quantities used to distinguish colloidal gels and glasses. Hence, we find that the glassy behavior of BKS silica can be interpreted as a ‘gel’ at low densities, with only a marginal gel-to-glass crossover at higher densities. read less D. Rodney, A. Tanguy, and D. Vandembroucq, “Modeling the mechanics of amorphous solids at different length scale and time scale,” Modelling and Simulation in Materials Science and Engineering. 2011. link Times cited: 244 Abstract: We review the recent literature on the simulation of the str… read more Abstract: We review the recent literature on the simulation of the structure and deformation of amorphous solids, including oxide and metallic glasses. We consider simulations at different length scale and time scale. At the nanometer scale, we review studies based on atomistic simulations, with a particular emphasis on the role of the potential energy landscape and of the temperature. At the micrometer scale, we present the different mesoscopic models of amorphous plasticity and show the relation between shear banding and the type of disorder and correlations (e.g. elastic) included in the models. At the macroscopic range, we review the different constitutive laws used in finite-element simulations. We end with a critical discussion on the opportunities and challenges offered by multiscale modeling and information transfer between scales to study amorphous plasticity. read less C. Zhang, Z. Duan, and M. Li, “Interstitial voids in silica melts and implication for argon solubility under high pressures,” Geochimica et Cosmochimica Acta. 2010. link Times cited: 17 S. Tyaginov, V. Sverdlov, I. Starkov, W. Gös, and T. Grasser, “Impact of O-Si-O bond angle fluctuations on the Si-O bond-breakage rate,” Microelectron. Reliab. 2009. link Times cited: 2 S. Tyaginov, V. Sverdlov, W. Gos, and T. Grasser, “Statistics of Si-O Bond-Breakage Rate Variations Induced by O-Si-O Angle Fluctuations,” 2009 13th International Workshop on Computational Electronics. 2009. link Times cited: 1 Abstract: The McPherson model for the Si-O bond-breakage has been exte… read more Abstract: The McPherson model for the Si-O bond-breakage has been extended in a manner to capture the effect of O-Si-O angle variations on the breakage rate. Using a distribution function of the O-Si-O bond angle, a series of breakage rate probability densities has been calculated as a function of the applied electric field. Using such a distribution function we have calculated the mean vale and the standard deviation of the breakage rate and compare them to the nominal rate corresponding to the fixed angle of 109.48deg observed in crystalline alpha-quartz. It is shown that the mean value of this rate is substantially higher than and the standard deviation is comparable with the nominal rate. Obtained dependencies demonstrate a linear trend in a log-fin space, thereby validating the thermo-chemical model for the time-dependent-dielectric breakdown also in the case of non-uniform O-Si-O angle distribution typical for amorphous silica. read less S. Paramore, L. Cheng, and B. Berne, “A Systematic Comparison of Pairwise and Many-Body Silica Potentials.,” Journal of chemical theory and computation. 2008. link Times cited: 15 Abstract: The role of many-body effects in modeling silica was investi… read more Abstract: The role of many-body effects in modeling silica was investigated using self-consistent force matching. Both pairwise and polarizable classical force fields were developed systematically from ab initio density functional theory force calculations, allowing for a direct comparison of the role of polarization in silica. It was observed that the pairwise potential performed remarkably well at reproducing the basic silica tetrahedral structure. However, the Si-O-Si angle that links the silica tetrahedra showed small but distinct differences with the polarizable potential, a result of the inability of the pairwise potential to properly account for variations in the polarization of the oxygens. Furthermore, the transferability of the polarizable potential was investigated and suggests that additional forces may be necessary to more completely describe silica annealing. read less M. Malshe, R. Narulkar, L. Raff, M. Hagan, S. Bukkapatnam, and R. Komanduri, “Parametrization of analytic interatomic potential functions using neural networks.,” The Journal of chemical physics. 2008. link Times cited: 29 Abstract: A generalized method that permits the parameters of an arbit… read more Abstract: A generalized method that permits the parameters of an arbitrary empirical potential to be efficiently and accurately fitted to a database is presented. The method permits the values of a subset of the potential parameters to be considered as general functions of the internal coordinates that define the instantaneous configuration of the system. The parameters in this subset are computed by a generalized neural network (NN) with one or more hidden layers and an input vector with at least 3n-6 elements, where n is the number of atoms in the system. The Levenberg-Marquardt algorithm is employed to efficiently affect the optimization of the weights and biases of the NN as well as all other potential parameters being treated as constants rather than as functions of the input coordinates. In order to effect this minimization, the usual Jacobian employed in NN operations is modified to include the Jacobian of the computed errors with respect to the parameters of the potential function. The total Jacobian employed in each epoch of minimization is the concatenation of two Jacobians, one containing derivatives of the errors with respect to the weights and biases of the network, and the other with respect to the constant parameters of the potential function. The method provides three principal advantages. First, it obviates the problem of selecting the form of the functional dependence of the parameters upon the system's coordinates by employing a NN. If this network contains a sufficient number of neurons, it will automatically find something close to the best functional form. This is the case since Hornik et al., [Neural Networks 2, 359 (1989)] have shown that two-layer NNs with sigmoid transfer functions in the first hidden layer and linear functions in the output layer are universal approximators for analytic functions. Second, the entire fitting procedure is automated so that excellent fits are obtained rapidly with little human effort. Third, the method provides a procedure to avoid local minima in the multidimensional parameter hyperspace. As an illustrative example, the general method has been applied to the specific case of fitting the ab initio energies of Si(5) clusters that are observed in a molecular dynamics (MD) simulation of the machining of a silicon workpiece. The energies of the Si(5) configurations obtained in the MD calculations are computed using the B3LYP procedure with a 6-31G(*) basis set. The final ab initio database, which comprises the density functional theory energies of 10 202 Si(5) clusters, is fitted to an empirical Tersoff potential containing nine adjustable parameters, two of which are allowed to be the functions of the Si(5) configuration. The fitting error averaged over all 10 202 points is 0.0148 eV (1.43 kJ mol(-1)). This result is comparable to the accuracy achieved by more general fitting methods that do not rely on an assumed functional form for the potential surface. read less J. Horbach, “Molecular dynamics computer simulation of amorphous silica under high pressure,” Journal of Physics: Condensed Matter. 2008. link Times cited: 42 Abstract: The structural and dynamic properties of silica melts under … read more Abstract: The structural and dynamic properties of silica melts under high pressure are studied using molecular dynamics (MD) computer simulation. The interactions between the ions are modelled by a pairwise-additive potential, the so-called CHIK potential, that has been recently proposed by Carré et al 2008 Europhys. Lett. 82 17001. The experimental equation of state is well reproduced by the CHIK model. With increasing pressure (density), the structure changes from a tetrahedral network to a network containing a high number of five- and six-fold Si–O coordinations. In the partial static structure factors, this change of the structure with increasing density is reflected by a shift of the first sharp diffraction peak towards higher wavenumbers q, eventually merging with the main peak at densities around 4.2 g cm−3. The self-diffusion constants as a function of pressure show the experimentally known maximum, occurring around a pressure of about 20 GPa. read less T. Voigtmann and J. Horbach, “The dynamics of silica melts under high pressure: mode-coupling theory results,” Journal of Physics: Condensed Matter. 2008. link Times cited: 14 Abstract: The high-pressure dynamics of a computer-modelled silica mel… read more Abstract: The high-pressure dynamics of a computer-modelled silica melt is studied in the framework of the mode-coupling theory of the glass transition using static structure input from molecular dynamics computer simulation. The theory reproduces the experimentally known viscosity minimum (diffusivity maximum) as a function of density or pressure and explains it in terms of a corresponding minimum in its critical temperature. This minimum arises from a gradual change in the equilibrium static structure which shifts from being dominated by tetrahedral ordering to showing the cageing known from high-density liquids. The theory is in qualitative agreement with computer simulation results. read less J. Habasaki, C. León, and K. Ngai, “Molecular Dynamics Simulation of Silicate Glasses,” Topics in Applied Physics. 2017. link Times cited: 1 J. Habasaki, C. León, and K. Ngai, “Molecular Dynamics Simulations,” Topics in Applied Physics*. 2017. link Times cited: 1
Funding	Award Title: Innovative Nanoinformatics models and tools: towards a Solid, verified and Integrated Approach to Predictive (eco)Toxicology (NanoSolveIT) Award Number: 814572 Award URI: https://cordis.europa.eu/project/id/814572 Funder: EU H2020

Short KIM ID The unique KIM identifier code.	SM_886641404623_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.	Sim_LAMMPS_Buckingham_CarreHorbachIspas_2008_SiO__SM_886641404623_000
DOI	10.25950/dbac5d53 https://doi.org/10.25950/dbac5d53 https://commons.datacite.org/doi.org/10.25950/dbac5d53
KIM Item Type	Simulator Model
KIM API Version	2.2
Simulator Name The name of the simulator as defined in kimspec.edn.	LAMMPS
Potential Type	buckingham
Simulator Potential	buck/coul/long
Run Compatibility	portable-models

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
N/A Unable to perform verification check due to an error.	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
N/A Unable to perform verification check due to an error.	vc-forces-numerical-derivative	consistency	Forces computed by the model agree with numerical derivatives of the energy; see full description.	Results	Files
N/A Unable to perform verification check due to an error.	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
N/A Unable to perform verification check due to an error.	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
N/A Thread safety can only be checked for KIM Models.	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

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.

(No matching species)

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.

(No matching species)

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.

(No matching species)

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.

(No matching species)

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.

(No matching species)

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: O

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	1495
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1114
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1177
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1273
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1241
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1177
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1209
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1209
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1304
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1336
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	955
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1082
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1273
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1082
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1209
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1241
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1336
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1145
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1114
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	955
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	827
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1114
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	986
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1177
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1273
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1368
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1241
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1241
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1273
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	986
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1273
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1082
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1177
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	955
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1177
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1273
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1145
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1177
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1273
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	986
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1241
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1145
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1177
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	764
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1114
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1400
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1209
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1241
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1241
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1304
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1082
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1432
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	986
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1145
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1209
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1114
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1241
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1336
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	955
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1273
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1400
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1082
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1018
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1304
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1273
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1241
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1336
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1241
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1177
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1400
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1432
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1114
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	827
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1050
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1177
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1114
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	859
Conjugate gradient relaxation of random finite cluster of Si atoms v003	view	1209

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	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 OSi in AFLOW crystal prototype A2B_aP12_1_8a_4a at zero temperature and pressure v000	view	140884941
Elastic constants for OSi in AFLOW crystal prototype A2B_aP18_1_12a_6a at zero temperature and pressure v000	view	177701856
Elastic constants for OSi in AFLOW crystal prototype A2B_cF12_225_c_a at zero temperature and pressure v000	view	105350862
Elastic constants for OSi in AFLOW crystal prototype A2B_cF24_227_c_a at zero temperature and pressure v000	view	140279893
Elastic constants for OSi in AFLOW crystal prototype A2B_cF408_227_efgh_aeg at zero temperature and pressure v000	view	449157242
Elastic constants for OSi in AFLOW crystal prototype A2B_cF96_227_cf_e at zero temperature and pressure v000	view	477592375
Elastic constants for OSi in AFLOW crystal prototype A2B_cI144_206_2de_e at zero temperature and pressure v000	view	297226679
Elastic constants for OSi in AFLOW crystal prototype A2B_cI48_206_ad_c at zero temperature and pressure v000	view	575874956
Elastic constants for OSi in AFLOW crystal prototype A2B_cI72_230_g_d at zero temperature and pressure v000	view	857292309
Elastic constants for OSi in AFLOW crystal prototype A2B_cP12_205_c_a at zero temperature and pressure v000	view	133799292
Elastic constants for OSi in AFLOW crystal prototype A2B_cP24_198_ab_2a at zero temperature and pressure v000	view	180284581
Elastic constants for OSi in AFLOW crystal prototype A2B_cP36_195_fgj_j at zero temperature and pressure v000	view	272810456
Elastic constants for OSi in AFLOW crystal prototype A2B_cP72_205_2d_d at zero temperature and pressure v000	view	646268758
Elastic constants for OSi in AFLOW crystal prototype A2B_hP12_182_cg_f at zero temperature and pressure v000	view	208036146
Elastic constants for OSi in AFLOW crystal prototype A2B_hP12_194_cg_f at zero temperature and pressure v000	view	206230438
Elastic constants for OSi in AFLOW crystal prototype A2B_hP18_179_ab_b at zero temperature and pressure v000	view	168127295
Elastic constants for OSi in AFLOW crystal prototype A2B_hP18_194_gh_h at zero temperature and pressure v000	view	183394095
Elastic constants for OSi in AFLOW crystal prototype A2B_hP36_162_2ijk_l at zero temperature and pressure v000	view	296334176
Elastic constants for OSi in AFLOW crystal prototype A2B_hP36_163_g3h_i at zero temperature and pressure v000	view	92553338
Elastic constants for OSi in AFLOW crystal prototype A2B_hP36_163_ghi_i at zero temperature and pressure v000	view	523649852
Elastic constants for OSi in AFLOW crystal prototype A2B_hP36_177_j2lm_n at zero temperature and pressure v000	view	548654172
Elastic constants for OSi in AFLOW crystal prototype A2B_hP36_181_fhij_k at zero temperature and pressure v000	view	176236932
Elastic constants for OSi in AFLOW crystal prototype A2B_hP36_194_ghk_k at zero temperature and pressure v000	view	378212833
Elastic constants for OSi in AFLOW crystal prototype A2B_hP72_180_4k_gik at zero temperature and pressure v000	view	129982410

EquilibriumCrystalStructure__TD_457028483760_001

Equilibrium structure and energy for a crystal structure at zero temperature and pressure v001

Creators:
Contributor: ilia
Publication Year: 2023
DOI: https://doi.org/10.25950/e8a7ed84

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	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 crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC72_5_12c_ab5c v001		view	16928519

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 OSi in AFLOW crystal prototype A2B_aP12_1_8a_4a v002	view	2731173
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_aP18_1_12a_6a v002	view	1735235
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_aP36_1_24a_12a v002	view	10259238
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_aP48_2_16i_8i v002	view	8470491
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cF12_225_c_a v002	view	119486
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cF144_210_fg_g v002	view	264415903
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cF24_227_c_a v002	view	5630508
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cF408_227_efgh_aeg v002	view	37148315
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cF96_227_cf_e v002	view	706396
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cI144_206_2de_e v002	view	19107805
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cI48_206_ad_c v002	view	329137
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cI72_199_2bc_c v002	view	4229868
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cI72_211_hi_i v002	view	45807632
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cI72_230_g_d v002	view	3971638
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cP12_205_c_a v002	view	112713
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cP144_224_ij2k_l v002	view	20271116
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cP24_198_ab_2a v002	view	7289239
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cP36_195_fgj_j v002	view	1137063
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cP72_205_2d_d v002	view	21264472
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cP72_223_jk_j v002	view	946519
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP12_182_cg_f v002	view	992150
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP12_194_cg_f v002	view	50005
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP18_179_ab_b v002	view	1908685
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP18_194_gh_h v002	view	1277054
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP36_162_2ijk_l v002	view	5420309
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP36_163_g3h_i v002	view	1620226
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP36_163_ghi_i v002	view	1598110
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP36_177_j2lm_n v002	view	3297871
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP36_177_jk2l_n v002	view	2570148
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP36_181_fhij_k v002	view	7272086
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP36_194_ghk_k v002	view	34714863
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP72_180_4k_gik v002	view	23587787
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP9_154_c_a v002	view	1747972
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP9_180_i_d v002	view	763632
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hR18_148_2f_f v002	view	15088595
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hR18_148_def_f v002	view	2587222
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hR18_166_def_h v002	view	3638795
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hR18_167_de_e v002	view	557307
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hR36_166_2fgh_i v002	view	43979267
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hR36_166_fg2h_i v002	view	36788826
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hR36_167_d3e_f v002	view	32556384
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hR36_167_def_f v002	view	6524227
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hR72_148_8f_4f v002	view	23211353
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC168_12_e7i10j_7j v002	view	80903408
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC24_15_aef_f v002	view	6404174
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC24_5_4c_2c v002	view	1076849
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC24_5_ab3c_2c v002	view	2624224
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC24_9_4a_2a v002	view	7926351
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC48_15_ae3f_2f v002	view	91808
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC72_12_2ghi4j_3j v002	view	24913104
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC72_12_eg2i4j_3j v002	view	29586312
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC72_12_gh2i4j_3j v002	view	4278415
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC72_8_4a10b_6b v002	view	2522816
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC96_12_4i6j_2i3j v002	view	7188516
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC96_12_g3i6j_4j v002	view	7455799
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mP12_3_ab3e_2e v002	view	1286665
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mP12_6_2a2b2c_2a2b v002	view	673282
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mP12_7_4a_2a v002	view	1266493
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mP24_14_4e_2e v002	view	6978414
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mP48_14_8e_4e v002	view	7545116
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mP54_13_ae8g_f4g v002	view	2641298
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mP84_10_i4m3n10o_7o v002	view	29142233
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oC108_63_acd2fg2h_cfgh v002	view	9267966
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oC108_65_ehnopq2r_gopr v002	view	41139135
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oC24_20_abc_c v002	view	2791254
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oC48_63_defg_h v002	view	13843746
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oC48_64_cdef_g v002	view	3057686
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oC48_68_cegh_i v002	view	6659269
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oC72_36_2a5b_2a2b v002	view	64668763
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oC72_63_def3g_2c2g v002	view	14645179
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oC96_21_2ehk6l_4l v002	view	7088140
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oF216_69_himn3p_f2mp v002	view	63709230
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oF48_70_ce_f v002	view	30726620
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oF96_70_c2ef_h v002	view	24900420
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oI108_71_egkl2n2o_hlno v002	view	61993614
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oI24_24_bcd_2a v002	view	6674508
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oP12_33_2a_a v002	view	567134
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oP12_60_d_c v002	view	1147891
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oP24_48_eghi_m v002	view	1361571
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oP24_50_eghi_m v002	view	3519870
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oP24_54_abcd_f v002	view	1460184
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oP24_54_acde_f v002	view	5471696
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oP24_56_ace_e v002	view	1195331
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oP36_60_3d_cd v002	view	1622474
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oP48_55_gh3i_2i v002	view	5886842
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oP72_19_12a_6a v002	view	17150926
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tI12_122_d_a v002	view	1236831
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tI24_98_ce_f v002	view	1118835
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tI48_120_ehi_i v002	view	1559527
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tI48_121_2ij_fi v002	view	15352893
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tI48_121_fij_j v002	view	1704865
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tI48_98_2cef_g v002	view	1526656
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tI96_140_ehlm_jl v002	view	35364491
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tI96_140_ijkl_m v002	view	21232079
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tI96_141_cehi_gh v002	view	5824575
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tI96_141_fg2h_i v002	view	41196339
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP12_92_b_a v002	view	1057224
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP24_116_eij_j v002	view	3742277
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP24_118_fhi_i v002	view	1214896
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP24_132_fil_n v002	view	1272254
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP24_95_bcd_d v002	view	4762805
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP36_92_3b_ab v002	view	1425004
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP36_96_3b_ab v002	view	1772673
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP3_123_h_a v002	view	423254
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP48_114_4e_2e v002	view	2093729
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP48_125_ijlm_n v002	view	11138414
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP48_126_f2hi_k v002	view	10270722
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP48_126_fik_k v002	view	3051003
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP48_133_hjk_k v002	view	9245851
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP6_136_f_a v002	view	46542
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP96_127_fg2jk2l_jkl v002	view	6222796
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cF136_227_aeg v002	view	107957543
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cF4_225_a v002	view	2240493
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cF8_227_a v002	view	2295574
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cI12_229_d v002	view	3110245
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cP46_223_cik v002	view	20293491
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP1_191_a v002	view	568571
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP2_194_c v002	view	447801
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP40_191_hjmno v002	view	3096512
Equilibrium crystal structure and energy for O in AFLOW crystal prototype A_hP4_194_f v002	view	63755
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP4_194_f v002	view	803273
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP58_164_2d3i3j v002	view	4447085
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP68_194_ef2h2kl v002	view	29096588
Equilibrium crystal structure and energy for O in AFLOW crystal prototype A_hR2_166_c v002	view	90897
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_mC164_15_e20f v002	view	16018220
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_mC16_12_4i v002	view	959157
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_oC92_63_ce2f2g3h v002	view	9198639
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_tI4_141_a v002	view	90111
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_tP106_137_a5g4h v002	view	7442189

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	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1336
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1336
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	859
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1273
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	859
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1368
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1336
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	891
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1273
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1432
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1336
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1336
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1241
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	923
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1241
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	923
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	923
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1304
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1241
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	795
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	795
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1145
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1273
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1304
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1400
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed bcc structure v003	view	1304
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1241
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1145
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	923
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	891
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	923
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	859
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1241
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1304
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1145
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1273
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	891
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1241
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	923
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1368
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1336
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1241
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1368
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1304
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	923
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	859
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	859
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1241
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1336
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1241
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1145
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	891
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1241
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1145
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	923
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1241
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1273
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1145
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1273
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1304
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed diamond structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1241
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1273
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	859
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	859
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1050
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1145
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1209
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	986
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	923
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	923
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1241
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed random structure v003	view	1145
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1145
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1273
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	955
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	891
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	827
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1177
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1304
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1145
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1304
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1114
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1082
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	891
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1018
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1336
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1400
Potential energy and atomic forces of periodic, non-orthogonal cell of Si atoms in a perturbed sh structure v003	view	1177

Errors

ClusterEnergyAndForces__TD_000043093022_003

Test	Error Categories	Link to Error page
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
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Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view
Conjugate gradient relaxation of random finite cluster of Si atoms v003	other	view

ElasticConstantsCrystal__TD_034002468289_000

Test	Error Categories	Link to Error page
Elastic constants for OSi in AFLOW crystal prototype A2B_cF144_210_fg_g at zero temperature and pressure v000	other	view
Elastic constants for OSi in AFLOW crystal prototype A2B_cI72_211_hi_i at zero temperature and pressure v000	other	view

EquilibriumCrystalStructure__TD_457028483760_000

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_aP12_1_8a_4a v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cF12_225_c_a v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cF24_227_c_a v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cF96_227_cf_e v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cI72_199_2bc_c v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cI72_211_hi_i v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cP144_224_ij2k_l v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP36_163_g3h_i v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hR18_166_def_h v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hR36_166_2fgh_i v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hR36_166_fg2h_i v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC24_5_4c_2c v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC72_12_eg2i4j_3j v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC96_12_g3i6j_4j v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mP48_14_8e_4e v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oC72_36_2a5b_2a2b v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oF216_69_himn3p_f2mp v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oP24_48_eghi_m v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oP36_60_3d_cd v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oP72_19_12a_6a v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tI12_122_d_a v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tI48_121_2ij_fi v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP12_92_b_a v000	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP24_118_fhi_i v000	other	view
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hP68_194_ef2h2kl v000	other	view
Equilibrium crystal structure and energy for O in AFLOW crystal prototype A_hR2_166_c v000	other	view
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_tI4_141_a v000	other	view

EquilibriumCrystalStructure__TD_457028483760_001

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP36_181_fhij_k v001	other	view

EquilibriumCrystalStructure__TD_457028483760_002

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_aP24_1_16a_8a v002	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_aP54_1_36a_18a v002	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_cI36_217_g_d v002	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hP18_162_fgi_k v002	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_hR9_155_de_e v002	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC18_5_3c_ac v002	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC24_15_cef_f v002	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mC72_5_12c_ab5c v002	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mP12_13_abce_g v002	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mP12_4_4a_2a v002	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_mP48_14_ad7e_4e v002	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oI24_46_abc_c v002	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_oP24_19_4a_2a v002	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tI24_82_2g_g v002	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP24_125_efk_m v002	other	view
Equilibrium crystal structure and energy for OSi in AFLOW crystal prototype A2B_tP48_85_4g_2g v002	other	view
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cI16_206_c v002	other	view
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_cI82_217_acgh 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 O in AFLOW crystal prototype A_mC16_12_2ij v002	other	view
Equilibrium crystal structure and energy for O in AFLOW crystal prototype A_mC4_12_i v002	other	view
Equilibrium crystal structure and energy for O in AFLOW crystal prototype A_oC12_63_cg v002	other	view
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_oF16_69_gh v002	other	view
Equilibrium crystal structure and energy for O in AFLOW crystal prototype A_oP24_61_3c v002	other	view
Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_tI8_139_h v002	other	view

LatticeConstantCubicEnergy__TD_475411767977_007

Test	Error Categories	Link to Error page
Equilibrium zero-temperature lattice constant for bcc O v007	other	view
Equilibrium zero-temperature lattice constant for bcc Si v007	other	view
Equilibrium zero-temperature lattice constant for diamond O v007	other	view
Equilibrium zero-temperature lattice constant for diamond Si v007	other	view
Equilibrium zero-temperature lattice constant for fcc O v007	other	view
Equilibrium zero-temperature lattice constant for fcc Si v007	other	view
Equilibrium zero-temperature lattice constant for sc O 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 O v005	other	view
Equilibrium lattice constants for hcp Si v005	other	view

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SiO2.charges
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kimprovenance.edn
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Sim_LAMMPS_Buckingham_CarreHorbachIspas_2008_SiO__SM_886641404623_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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