LAMMPS BOP potential for the Ga-As system developed by Murdick et al. (2006) v001

Dewey A. Murdick; Xiaowang Zhou; Wadley, H. N. G.; D. Nguyen-Manh; Ralf Drautz; D. G. Pettifor

doi:10.25950/436e95e3

Jump to: Tests | Visualizers | Files | Wiki

Sim_LAMMPS_BOP_MurdickZhouWadley_2006_GaAs__SM_104202807866_001

Interatomic potential for Arsenic (As), Gallium (Ga).
Use this Potential

Title A single sentence description.	LAMMPS BOP potential for the Ga-As system developed by Murdick et al. (2006) v001
Description	An analytic, bond-order potential (BOP) is proposed and parametrized for the gallium arsenide system. The potential addresses primary (σ) and secondary (π) bonding and the valence-dependent character of heteroatomic bonding, and it can be combined with an electron counting potential to address the distribution of electrons on the GaAs surface. The potential was derived from a tight-binding description of covalent bonding by retaining the first two levels of an expanded Green’s function for the σ and π bond-order terms. Predictions using the potential were compared with independent estimates for the structures and binding energy of small clusters (dimers, trimers, and tetramers) and for various bulk lattices with coordinations varying from 4 to 12. The structure and energies of simple point defects and melting transitions were also investigated. The relative stabilities of the (001) surface reconstructions of GaAs were well predicted, especially under high-arsenic-overpressure conditions. The structural and binding energy trends of this GaAs BOP generally match experimental observations and ab initio calculations. HISTORY: Changes in version 001: * Parameter file formatted for compatibility with recent LAMMPS versions
Species The supported atomic species.	As, Ga
Disclaimer A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.	None
Content Origin	LAMMPS package 30-Jul-2021

Contributor	Ronald E. Miller
Maintainer	Ronald E. Miller
Developer	Dewey A. Murdick Xiaowang Zhou Wadley, H. N. G. D. Nguyen-Manh Ralf Drautz D. G. Pettifor
Published on KIM	2021
How to Cite	This Simulator Model originally published in [1] is archived in OpenKIM [2-4]. [1] Murdick DA, Zhou XW, Wadley HNG, Nguyen-Manh D, Drautz R, Pettifor DG. Analytic bond-order potential for the gallium arsenide system. Physical Review B [Internet]. 2006Jan;73(4). Available from: https://doi.org/10.1103/physrevb.73.045206 doi:10.1103/physrevb.73.045206 — (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] Murdick DA, Zhou X, Wadley HNG, Nguyen-Manh D, Drautz R, Pettifor DG. LAMMPS BOP potential for the Ga-As system developed by Murdick et al. (2006) v001. OpenKIM; 2021. doi:10.25950/436e95e3 [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. 53 Citations (22 used) Show Model Used Show All Help us to determine which of the papers that cite this potential actually used it to perform calculations. If you know, click the . M. Kurban, “MOLECULAR DYNAMICS STUDY ON THE STRUCTURAL, THERMAL AND ENERGETIC PROPERTIES OF GaAs NANOPARTICLES,” Anadolu University Journal of Science and Technology-A Applied Sciences and Engineering. 2018. link Times cited: 1 Abstract: In this work, the structural and energetic properties of GaA… read more Abstract: In this work, the structural and energetic properties of GaAs nanoparticles (NPs) are investigated using the bond order potential (BOP) based on modern classical molecular dynamics (MD) method. All MD simulations are performed by means of LAMMPS. Some physical properties such as variation of potential energy depending on temperature, order parameter, coordination number in terms of probability distribution and radial distribution function (RDF) are searched. The heat capacity calculation is also performed as depending on temperature using a non-equilibrated molecular dynamics simulation strategy. Temperature dependence of these physical properties was obtained. The calculated physical properties are found to be sensitive to temperature. read less D. Yi, J. Li, and P. Zhu, “Study of Nanoscratching Process of GaAs Using Molecular Dynamics,” Crystals. 2018. link Times cited: 12 Abstract: In this paper, molecular dynamics method was employed to inv… read more Abstract: In this paper, molecular dynamics method was employed to investigate the nanoscratching process of gallium arsenide (GaAs) in order to gain insights into the material deformation and removal mechanisms in chemical mechanical polishing of GaAs. By analyzing the distribution of hydrostatic pressure and coordination number of GaAs atoms, it was found that phase transformation and amorphization were the dominant deformation mechanisms of GaAs in the scratching process. Furthermore, anisotropic effect in nanoscratching of GaAs was observed. The diverse deformation behaviors of GaAs with different crystal orientations were due to differences in the atomic structure of GaAs. The scratching resistance of GaAs(001) surface was the biggest, while the friction coefficient of GaAs(111) surface was the smallest. These findings shed light on the mechanical wear mechanism in chemical mechanical polishing of GaAs. read less P. Fan, S. Goel, X. Luo, and H. Upadhyaya, “Atomic-Scale Friction Studies on Single-Crystal Gallium Arsenide Using Atomic Force Microscope and Molecular Dynamics Simulation,” Nanomanufacturing and Metrology. 2021. link Times cited: 9 P. Fan, S. Goel, X. Luo, and H. Upadhyaya, “Atomic-Scale Friction Studies on Single-Crystal Gallium Arsenide Using Atomic Force Microscope and Molecular Dynamics Simulation,” Nanomanufacturing and Metrology. 2021. link Times cited: 0 N. D. Prasolov et al., “The Study of Nanoindentation of Atomically Flat GaAs Surface using the Tip of Atomic-Force Microscope,” Semiconductors. 2019. link Times cited: 0 N. D. Prasolov, A. Gutkin, and P. Brunkov, “Molecular-Dynamics Simulation of the Low-Temperature Surface Reconstruction of a GaAs(001) Surface during the Nanoindentation Process,” Semiconductors. 2019. link Times cited: 2 V. Hùng, T. X. Linh, V. T. T. Ha, D. D. Phuong, and H. Hieu, “Investigation of elastic moduli and constants of zinc-blende AlyGa1-yAs alloy by statistical moment method,” The European Physical Journal B. 2018. link Times cited: 3 W. Wampler and S. Myers, “Model for transport and reaction of defects and carriers within displacement cascades in gallium arsenide,” Journal of Applied Physics. 2015. link Times cited: 12 Abstract: A model is presented for recombination of charge carriers at… read more Abstract: A model is presented for recombination of charge carriers at evolving displacement damage in gallium arsenide, which includes clustering of the defects in atomic displacement cascades produced by neutron or ion irradiation. The carrier recombination model is based on an atomistic description of capture and emission of carriers by the defects with time evolution resulting from the migration and reaction of the defects. The physics and equations on which the model is based are presented, along with the details of the numerical methods used for their solution. The model uses a continuum description of diffusion, field-drift and reaction of carriers, and defects within a representative spherically symmetric cluster of defects. The initial radial defect profiles within the cluster were determined through pair-correlation-function analysis of the spatial distribution of defects obtained from the binary-collision code MARLOWE, using recoil energies for fission neutrons. Properties of the defects are discussed and values for their parameters are given, many of which were obtained from density functional theory. The model provides a basis for predicting the transient response of III-V heterojunction bipolar transistors to displacement damage from energetic particle irradiation. read less J. Moussa, S. Foiles, and P. Schultz, “Simulation and modeling of the electronic structure of GaAs damage clusters,” Journal of Applied Physics. 2012. link Times cited: 2 Abstract: In an effort to build a stronger microscopic foundation for … read more Abstract: In an effort to build a stronger microscopic foundation for radiation damage models in gallium arsenide (GaAs), the electronic properties of radiation-induced damage clusters are studied with atomistic simulations. Molecular dynamics simulations are used to access the time and length scales required for direct simulation of a collision cascade, and density functional theory simulations are used to calculate the electronic properties of isolated damaged clusters that are extracted from these cascades. To study the physical properties of clusters, we analyze the statistics of a randomly generated ensemble of damage clusters because no single cluster adequately represents this class of defects. The electronic properties of damage clusters are accurately described by a classical model of the electrical charging of a semiconducting sphere embedded in a uniform dielectric. The effective band gap of the cluster depends on the degree of internal structural damage, and the gap closes to form a metal in the high-da... read less D. Ward, X. W. Zhou, B. M. Wong, F. Doty, and J. Zimmerman, “Accuracy of existing atomic potentials for the CdTe semiconductor compound.,” The Journal of chemical physics. 2011. link Times cited: 35 Abstract: CdTe and CdTe-based Cd(1-x)Zn(x)Te (CZT) alloys are importan… read more Abstract: CdTe and CdTe-based Cd(1-x)Zn(x)Te (CZT) alloys are important semiconductor compounds that are used in a variety of technologies including solar cells, radiation detectors, and medical imaging devices. Performance of such systems, however, is limited due to the propensity of nano- and micro-scale defects that form during crystal growth and manufacturing processes. Molecular dynamics simulations offer an effective approach to study the formation and interaction of atomic scale defects in these crystals, and provide insight on how to minimize their concentrations. The success of such a modeling effort relies on the accuracy and transferability of the underlying interatomic potential used in simulations. Such a potential must not only predict a correct trend of structures and energies of a variety of elemental and compound lattices, defects, and surfaces but also capture correct melting behavior and should be capable of simulating crystalline growth during vapor deposition as these processes sample a variety of local configurations. In this paper, we perform a detailed evaluation of the performance of two literature potentials for CdTe, one having the Stillinger-Weber form and the other possessing the Tersoff form. We examine simulations of structures and the corresponding energies of a variety of elemental and compound lattices, defects, and surfaces compared to those obtained from ab initio calculations and experiments. We also perform melting temperature calculations and vapor deposition simulations. Our calculations show that the Stillinger-Weber parameterization produces the correct lowest energy structure. This potential, however, is not sufficiently transferrable for defect studies. Origins of the problems of these potentials are discussed and insights leading to the development of a more transferrable potential suitable for molecular dynamics simulations of defects in CdTe crystals are provided. read less P. Fan et al., “Oblique nanomachining of gallium arsenide explained using AFM experiments and MD simulations,” Journal of Manufacturing Processes. 2023. link Times cited: 0 Z. Liang, Y. Jiang, X. Gong, and H. Gong, “Atomistic modelling of the immiscible Fe–Bi system from a constructed bond order potential,” Journal of Physics: Condensed Matter. 2021. link Times cited: 2 Abstract: An analytical bond-order potential (BOP) of Fe–Bi has been c… read more Abstract: An analytical bond-order potential (BOP) of Fe–Bi has been constructed and has been validated to have a better performance than the Fe–Bi potentials already published in the literature. Molecular dynamics simulations based on this BOP has been then conducted to investigate the ground-state properties of Bi, structural stability of the Fe–Bi binary system, and the effect of Bi on mechanical properties of BCC Fe. It is found that the present BOP could accurately predict the ground-state A7 structure of Bi and its structural parameters, and that a uniform amorphous structure of Fe100−x Bi x could be formed when Bi is located in the composition range of 26 ⩽ x < 70. In addition, simulations also reveal that the addition of a very small percentage of Bi would cause a considerable decrease of tensile strength and critical strain of BCC Fe upon uniaxial tensile loading. The obtained results are in nice agreement with similar experimental observations in the literature. read less P. Fan et al., “Molecular dynamics simulation of AFM tip-based hot scratching of nanocrystalline GaAs,” Materials Science in Semiconductor Processing. 2021. link Times cited: 11 D. S. Oliveira and M. Cotta, “Role of Group V Atoms during GaAs Nanowire Growth Revealed by Molecular Dynamics Simulations: Implications in the Formation of Sharp Interfaces.” 2021. link Times cited: 3 Abstract: Understanding atomistic mechanisms for catalyst-assisted nan… read more Abstract: Understanding atomistic mechanisms for catalyst-assisted nanowire growth is an essential step to improve control over the properties of these versatile nanomaterials. However, in silico approaches ... read less P. Fan, S. Goel, X. Luo, Y. Yan, Y. Geng, and Y. Wang, “An atomistic investigation on the wear of diamond during atomic force microscope tip-based nanomachining of gallium arsenide,” Computational Materials Science. 2021. link Times cited: 11 D. S. Oliveira, M. A. Cotta, and J. E. Padilha, “Interatomic potential for atomistic simulation of self-catalyzed GaAs nanowires growth,” Computational Materials Science. 2020. link Times cited: 5 G. Plummer and G. Tucker, “Bond-order potentials for theTi3AlC2andTi3SiC2MAX phases,” Physical Review B. 2019. link Times cited: 12 N. D. Prasolov, A. Gutkin, and P. Brunkov, “Molecular dynamics study of As dimer formation on the GaAs (001) As-rich surface,” Journal of Physics: Conference Series. 2019. link Times cited: 1 Abstract: Using the molecular dynamics modelling the study of the proc… read more Abstract: Using the molecular dynamics modelling the study of the process of As dimer formation on the GaAs (001) surface was carried out at different temperatures as a function of time. To describe GaAs properties the bond-order potential was used. It was found that the activation energy of formation of single dimer is about 38 meV, while the dimer dissociation energy is about 2 eV. The characteristic time of the single dimer generation lies in the range 10-6 – 10-8 s for temperatures from 28 to 37 K. read less M. Kurban, “Tunable electronic structure and structural transition of GaAs clusters at high pressure and temperature,” Journal of Alloys and Compounds. 2019. link Times cited: 8 N. D. Prasolov, P. Brunkov, and A. Gutkin, “Molecular dynamics simulations of GaAs-crystal surface modifications during nanoindentation with AFM tip.,” Journal of Physics: Conference Series. 2017. link Times cited: 0 Abstract: The nanoindentation model of atomically flat surface of GaAs… read more Abstract: The nanoindentation model of atomically flat surface of GaAs with the AFM tip was developed on the base of Molecular Dynamics. It was found that as a temperature rises above 100 K the nanoindention results in increase of number of atoms with higher number of neighbours, i.e. point defect appears in the topmost atomic layers of GaAs. The observed results can be explained with the kinetic concept of the mechanism of fracture of solid state where the generation of native point defects caused by the fluctuation of thermal energy and the external stress results in enhancement of the defect generation rate. read less M. Vasilenko, I. Neizvestny, and N. Shwartz, “Formation of GaAs nanostructures by droplet epitaxy—Monte Carlo simulation,” Computational Materials Science. 2015. link Times cited: 29 I. Neizvestny and N. Shwartz, “Monte Carlo Simulation of Semiconductor Nanostructure Growth.” 2017. link Times cited: 0 X. Jiang, H. Sun, K. Choudhary, H. Zhuang, and Q. Nian, “Interpretable Ensemble Learning for Materials Property Prediction with Classical Interatomic Potentials: Carbon as an Example,” ArXiv. 2023. link Times cited: 0 Abstract: Machine learning (ML) is widely used to explore crystal mate… read more Abstract: Machine learning (ML) is widely used to explore crystal materials and predict their properties. However, the training is time-consuming for deep-learning models, and the regression process is a black box that is hard to interpret. Also, the preprocess to transfer a crystal structure into the input of ML, called descriptor, needs to be designed carefully. To efficiently predict important properties of materials, we propose an approach based on ensemble learning consisting of regression trees to predict formation energy and elastic constants based on small-size datasets of carbon allotropes as an example. Without using any descriptor, the inputs are the properties calculated by molecular dynamics with 9 different classical interatomic potentials. Overall, the results from ensemble learning are more accurate than those from classical interatomic potentials, and ensemble learning can capture the relatively accurate properties from the 9 classical potentials as criteria for predicting the final properties. read less A. Thompson et al., “LAMMPS - A flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales,” Computer Physics Communications. 2021. link Times cited: 2377 X. Chen et al., “Machine learning enhanced empirical potentials for metals and alloys,” Comput. Phys. Commun. 2021. link Times cited: 5 M. C. Escaño and T. Nguyen, “Does GaAs bulk lattice really expand due to defects in the low concentration regime?,” Solid State Communications. 2020. link Times cited: 2 A. Thompson et al., “Automated Algorithms for Quantum-Level Accuracy in Atomistic Simulations: LDRD Final Report.” 2012. link Times cited: 3 Abstract: This report summarizes the result of LDRD project 12-0395, t… read more Abstract: This report summarizes the result of LDRD project 12-0395, titled “Automated Algorithms for Quantum-level Accuracy in Atomistic Simulations.” During the course of this LDRD, we have developed an interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected on to a basis of hyperspherical harmonics in four dimensions. The SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. Global optimization methods in the DAKOTA software package are used to seek out good choices of hyperparameters that define the overall structure of the SNAP potential. FitSnap.py, a Python-based software package interfacing to both LAMMPS and DAKOTA is used to formulate the linear regression problem, solve it, and analyze the accuracy of the resultant SNAP potential. We describe a SNAP potential for tantalum that accurately reproduces a variety of solid and liquid properties. Most significantly, in contrast to existing tantalum potentials, SNAP correctly predicts the Peierls barrier for screw dislocation motion. We also present results from SNAP potentials generated for indium phosphide (InP) and silica (SiO2). We describe efficient algorithms for calculating SNAP forces and energies in molecular dynamics simulations using massively parallel computers and advanced processor architectures. Finally, we briefly describe the MSM method for efficient calculation of electrostatic interactions on massively parallel computers. read less T. Hammerschmidt, R. Drautz, and D. Pettifor, “Atomistic modelling of materials with bond-order potentials,” International Journal of Materials Research. 2009. link Times cited: 26 Abstract: The atomistic modelling of materials with effective model po… read more Abstract: The atomistic modelling of materials with effective model potentials requires a reliable description of the breaking and making of interatomic bonds in different atomic environments. The bond-order potentials provide such a transferable description of atomic bonding while at the same time they are computationally efficient for application in large-scale atomistic simulations. We give an overview of the fundamentals of bond-order potentials and their derivation from the tight-binding electronic structure by linking the atomic structure to the electronic structure. We discuss the application of the structural energy difference theorem for studying trends in crystal phase stability and provide a brief summary of representative examples for modelling metals, hydrocarbons, and semiconductors with analytic and numerical bond-order potentials. read less X. W. Zhou and F. Doty, “Embedded-ion method: An analytical energy-conserving charge-transfer interatomic potential and its application to the La-Br system,” Physical Review B. 2008. link Times cited: 30 S. Munetoh, T. Motooka, K. Moriguchi, and A. Shintani, “Interatomic potential for Si–O systems using Tersoff parameterization,” Computational Materials Science. 2007. link Times cited: 382 R. Jones, C. Weinberger, S. Coleman, and G. Tucker, “Introduction to Atomistic Simulation Methods.” 2016. link Times cited: 1 G. Imbalzano and M. Ceriotti, “Modeling the Ga/As binary system across temperatures and compositions from first principles,” Physical Review Materials. 2021. link Times cited: 11 Abstract: Materials composed of elements from the third and fifth colu… read more Abstract: Materials composed of elements from the third and fifth columns of the periodic table display a very rich behavior, with the phase diagram usually containing a metallic liquid phase and a polar semiconducting solid. As a consequence, it is very hard to achieve transferable empirical models of interactions between the atoms that can reliably predict their behavior across the temperature and composition range that is relevant to the study of the synthesis and properties of III/V nanostructures and devices. We present a machine-learning potential trained on density functional theory reference data that provides a general-purpose model for the Ga$_x$As$_{1-x}$ system. We provide a series of stringent tests that showcase the accuracy of the potential, and its applicability across the whole binary phase space, computing with ab initio accuracy a large number of finite-temperature properties as well as the location of phase boundaries. We also show how a committe model can be used to reliably determine the uncertainty induced by the limitations of the ML model on its predictions, to identify regions of phase space that are predicted with insufficient accuracy, and to iteratively refine the training set to achieve consistent, reliable modeling. read less N. D. Prasolov, A. Gutkin, and P. Brunkov, “Molecular-Dynamics Study of Dimer Formation on a GaAs (001) Surface at Low Temperatures,” Semiconductors. 2021. link Times cited: 0 X. W. Zhou, D. Ward, and M. E. Foster, “A bond-order potential for the Al–Cu–H ternary system,” New Journal of Chemistry. 2018. link Times cited: 13 Abstract: Al-Based Al–Cu alloys have a very high strength to density r… read more Abstract: Al-Based Al–Cu alloys have a very high strength to density ratio, and are therefore important materials for transportation systems including vehicles and aircrafts. These alloys also appear to have a high resistance to hydrogen embrittlement, and as a result, are being explored for hydrogen related applications. To enable fundamental studies of mechanical behavior of Al–Cu alloys under hydrogen environments, we have developed an Al–Cu–H bond-order potential according to the formalism implemented in the molecular dynamics code LAMMPS. Our potential not only fits well to properties of a variety of elemental and compound configurations (with coordination varying from 1 to 12) including small clusters, bulk lattices, defects, and surfaces, but also passes stringent molecular dynamics simulation tests that sample chaotic configurations. Careful studies verified that this Al–Cu–H potential predicts structural property trends close to experimental results and quantum-mechanical calculations; in addition, it properly captures Al–Cu, Al–H, and Cu–H phase diagrams and enables simulations of H2 dissociation, chemisorption, and absorption on Al–Cu surfaces. read less X. W. Zhou, R. Jones, and K. Chu, “Polymorphic improvement of Stillinger-Weber potential for InGaN,” Journal of Applied Physics. 2017. link Times cited: 4 Abstract: A Stillinger-Weber potential is computationally very efficie… read more Abstract: A Stillinger-Weber potential is computationally very efficient for molecular dynamics simulations. Despite its simple mathematical form, the Stillinger-Weber potential can be easily parameterized to ensure that crystal structures with tetrahedral bond angles (e.g., diamond-cubic, zinc-blende, and wurtzite) are stable and have the lowest energy. As a result, the Stillinger-Weber potential has been widely used to study a variety of semiconductor elements and alloys. When studying an A-B binary system, however, the Stillinger-Weber potential is associated with two major drawbacks. First, it significantly overestimates the elastic constants of elements A and B, limiting its use for systems involving both compounds and elements (e.g., an A/AB multilayer). Second, it prescribes equal energy for zinc-blende and wurtzite crystals, limiting its use for compounds with large stacking fault energies. Here, we utilize the polymorphic potential style recently implemented in LAMMPS to develop a modified Stillinger-Weber potential for InGaN that overcomes these two problems.A Stillinger-Weber potential is computationally very efficient for molecular dynamics simulations. Despite its simple mathematical form, the Stillinger-Weber potential can be easily parameterized to ensure that crystal structures with tetrahedral bond angles (e.g., diamond-cubic, zinc-blende, and wurtzite) are stable and have the lowest energy. As a result, the Stillinger-Weber potential has been widely used to study a variety of semiconductor elements and alloys. When studying an A-B binary system, however, the Stillinger-Weber potential is associated with two major drawbacks. First, it significantly overestimates the elastic constants of elements A and B, limiting its use for systems involving both compounds and elements (e.g., an A/AB multilayer). Second, it prescribes equal energy for zinc-blende and wurtzite crystals, limiting its use for compounds with large stacking fault energies. Here, we utilize the polymorphic potential style recently implemented in LAMMPS to develop a modified Stillinger-Weber... read less X. W. Zhou, D. Ward, and M. E. Foster, “An analytical bond-order potential for the aluminum copper binary system,” Journal of Alloys and Compounds. 2016. link Times cited: 38 X. W. Zhou, D. Ward, and M. E. Foster, “An analytical bond‐order potential for carbon,” Journal of Computational Chemistry. 2015. link Times cited: 38 Abstract: Carbon is the most widely studied material today because it … read more Abstract: Carbon is the most widely studied material today because it exhibits special properties not seen in any other materials when in nano dimensions such as nanotube and graphene. Reduction of material defects created during synthesis has become critical to realize the full potential of carbon structures. Molecular dynamics (MD) simulations, in principle, allow defect formation mechanisms to be studied with high fidelity, and can, therefore, help guide experiments for defect reduction. Such MD simulations must satisfy a set of stringent requirements. First, they must employ an interatomic potential formalism that is transferable to a variety of carbon structures. Second, the potential needs to be appropriately parameterized to capture the property trends of important carbon structures, in particular, diamond, graphite, graphene, and nanotubes. Most importantly, the potential must predict the crystalline growth of the correct phases during direct MD simulations of synthesis to achieve a predictive simulation of defect formation. Because an unlimited number of structures not included in the potential parameterization are encountered, the literature carbon potentials are often not sufficient for growth simulations. We have developed an analytical bond order potential for carbon, and have made it available through the public MD simulation package LAMMPS. We demonstrate that our potential reasonably captures the property trends of important carbon phases. Stringent MD simulations convincingly show that our potential accounts not only for the crystalline growth of graphene, graphite, and carbon nanotubes but also for the transformation of graphite to diamond at high pressure. © 2015 Wiley Periodicals, Inc. read less X. W. Zhou, D. Ward, M. Foster, and J. Zimmerman, “An analytical bond-order potential for the copper–hydrogen binary system,” Journal of Materials Science. 2015. link Times cited: 18 X. Zhou, M. E. Foster, F. Swol, J. E. Martin, and B. M. Wong, “Analytical Bond-Order Potential for the Cd–Te–Se Ternary System,” Journal of Physical Chemistry C. 2014. link Times cited: 13 D. Ward, X. W. Zhou, B. M. Wong, J. Zimmerman, and F. Doty, “Analytical bond-order potential for the cadmium telluride binary system.” 2012. link Times cited: 69 Abstract: CdTe and Cd${}_{1\ensuremath{-}x}$Zn${}_{x}$Te are the leadi… read more Abstract: CdTe and Cd${}_{1\ensuremath{-}x}$Zn${}_{x}$Te are the leading semiconductor compounds for both photovoltaic and radiation detection applications. The performance of these materials is sensitive to the presence of atomic-scale defects in the structures. To enable accurate studies of these defects using modern atomistic simulation technologies, we have developed a high-fidelity analytical bond-order potential for the CdTe system. This potential incorporates primary ($\ensuremath{\sigma}$) and secondary ($\ensuremath{\pi}$) bonding and the valence dependence of the heteroatom interactions. The functional forms of the potential are directly derived from quantum-mechanical tight-binding theory under the condition that the first two and first four levels of the expanded Green's function for the $\ensuremath{\sigma}$- and $\ensuremath{\pi}$-bond orders, respectively, are retained. The potential parameters are optimized using iteration cycles that include first-fitting properties of a variety of elemental and compound configurations (with coordination varying from 1 to 12) including small clusters, bulk lattices, defects, and surfaces, and then checking crystalline growth through vapor deposition simulations. It is demonstrated that this CdTe bond-order potential gives structural and property trends close to those seen in experiments and quantum-mechanical calculations and provides a good description of melting temperature, defect characteristics, and surface reconstructions of the CdTe compound. Most importantly, this potential captures the crystalline growth of the ground-state structures for Cd, Te, and CdTe phases in vapor deposition simulations. read less S. Foiles, “Comparison of binary collision approximation and molecular dynamics for displacement cascades in GaAs.” 2011. link Times cited: 7 Abstract: The predictions of binary collision approximation (BCA) and … read more Abstract: The predictions of binary collision approximation (BCA) and molecular dynamics (MD) simulations of displacement cascades in GaAs are compared. There are three issues addressed in this work. The first is the optimal choice of the effective displacement threshold to use in the BCA calculations to obtain the best agreement with MD results. Second, the spatial correlations of point defects are compared. This is related to the level of clustering that occurs for different types of radiation. Finally, the size and structure of amorphous zones seen in the MD simulations is summarized. BCA simulations are not able to predict the formation of amorphous material. read less J. Los, C. Bichara, and R. Pellenq, “Tight binding within the fourth moment approximation: Efficient implementation and application to liquid Ni droplet diffusion on graphene.” 2011. link Times cited: 9 Abstract: (Received 8 February 2011; revised manuscript received 13 Ma… read more Abstract: (Received 8 February 2011; revised manuscript received 13 May 2011; published 31 August 2011)Application of the fourth moment approximation (FMA) to the local density of states within a tight bindingdescription to build a reactive, interatomic interaction potential for use in large scale molecular simulations,is a logical and signiﬁcant step forward to improve the second moment approximation, standing at the basisof several, widely used (semi-)empirical interatomic interaction models. In this paper we present a sufﬁcientlydetailed description of the FMA and its technical implications, containing the essential elements for an efﬁcientimplementationinasimulationcode.Usingarecent,existingFMA-basedmodelforC-Nisystems,weinvestigatedthesizedependenceofthediffusionofaliquidNiclusteronagraphenesheetandﬁndapowerlawdependenceofthediffusionconstantontheclustersize(numberofclusteratoms)withanexponentverycloseto−2 read less K. Fichthorn, Y. Tiwary, T. Hammerschmidt, P. Kratzer, and M. Scheffler, “Analytic many-body potential for GaAs(001) homoepitaxy: Bulk and surface properties,” Physical Review B. 2011. link Times cited: 14 Abstract: We employ atomic-scale simulation methods to investigate bul… read more Abstract: We employ atomic-scale simulation methods to investigate bulk and surface properties of an analytic TersoffAbell type potential for describing interatomic interactions in GaAs. The potential is a modified form of that proposed by Albe and colleagues [Phys. Rev. B 66, 035205 (2002)] in which the cut-off parameters for the As-As interaction have been shortened. With this modification, many bulk properties predicted by the potential for solid GaAs are the same as those in the original potential, but properties of the GaAs(001) surface better match results from first-principles calculations with density-functional theory (DFT). We tested the ability of the potential to reproduce the phonon dispersion and heat capacity of bulk solid GaAs by comparing it to experiment and the overall agreement is good. In the modified potential, the GaAs(001) β2(2 × 4) reconstruction is favored under As-rich growth conditions in agreement with DFT calculations. Additionally, the binding energies and diffusion barriers for a Ga adatom on the β2(2 × 4) reconstruction generally match results from DFT calculations. These studies indicate that the potential is suitable for investigating aspects of GaAs(001) homoepitaxy. read less X. W. Zhou and R. Jones, “Effects of cutoff functions of Tersoff potentials on molecular dynamics simulations of thermal transport,” Modelling and Simulation in Materials Science and Engineering. 2011. link Times cited: 19 Abstract: Past molecular dynamics studies of thermal transport have pr… read more Abstract: Past molecular dynamics studies of thermal transport have predominantly used Stillinger–Weber potentials. As materials continuously shrink, their properties increasingly depend on defect and surface effects. Unfortunately, Stillinger–Weber potentials are best used for diamond-cubic-like bulk crystals. They cannot represent the energies of many metastable phases, nor can they accurately predict the energetics of defective and surface regions. To study nanostructured materials, where these regions can dominate thermal transport, the accuracy of Tersoff potentials in representing these structures is more desirable. Based upon an analysis of thermal transport in a GaN system, we demonstrate that the cutoff function of the existing Tersoff potentials may lead to problems in determining the thermal conductivity. To remedy this issue, improved cutoff schemes are proposed and evaluated. read less P. S. Branicio, J. Rino, C. Gan, and H. Tsuzuki, “Interaction potential for indium phosphide: a molecular dynamics and first-principles study of the elastic constants, generalized stacking fault and surface energies,” Journal of Physics: Condensed Matter. 2009. link Times cited: 31 Abstract: Indium phosphide is investigated using molecular dynamics (M… read more Abstract: Indium phosphide is investigated using molecular dynamics (MD) simulations and density-functional theory calculations. MD simulations use a proposed effective interaction potential for InP fitted to a selected experimental dataset of properties. The potential consists of two- and three-body terms that represent atomic-size effects, charge–charge, charge–dipole and dipole–dipole interactions as well as covalent bond bending and stretching. Predictions are made for the elastic constants as a function of density and temperature, the generalized stacking fault energy and the low-index surface energies. read less T. Hammerschmidt, P. Kratzer, and M. Scheffler, “Analytic many-body potential for InAs/GaAs surfaces and nanostructures: Formation energy of InAs quantum dots,” Physical Review B. 2008. link Times cited: 46 Abstract: A parametrization of the Abell‐Tersoff potential for In, Ga,… read more Abstract: A parametrization of the Abell‐Tersoff potential for In, Ga, As, InAs, and GaAs is presented by using both experimental data and results from density-functional calculations as input. This parametrization is optimized for the description of structural and elastic properties of bulk In, Ga, As, InAs, and GaAs, as well as for the structure and energy of several reconstructed low-index GaAs and InAs surfaces. We demonstrate the transferability to GaAs and InAs high-index surfaces and compare the results to those obtained with previously published parametrizations. Furthermore, we demonstrate the applicability to epitaxial InAs/GaAs films by comparing the Poisson ratio and elastic energy for biaxial strain, as obtained numerically with our potential and analytically from continuum-elasticity theory. Limitations for the description of point defects and surface diffusion are pointed out. This parametrization enables us to perform atomically detailed studies of InAs/GaAs heterostructures. The formation energy of InAs quantum dots on GaAs001 obtained from our atomistic approach is in good agreement with previous results from a hybrid approach. read less J. Schall, G. Gao, and J. Harrison, “Elastic constants of silicon materials calculated as a function of temperature using a parametrization of the second-generation reactive empirical bond-order potential,” Physical Review B. 2008. link Times cited: 48 Abstract: A parametrization for silicon is presented that is based on … read more Abstract: A parametrization for silicon is presented that is based on the second-generation reactive empirical bondorder REBO formalism Brenner, Shenderova, Harrison, Stuart, Ni, and Sinnott J. Phys.: Condens. Matter 14, 783 2002 . Because it shares the same analytic form as Brenner’s second-generation REBO, this new potential is a step toward a single potential that can model many atom systems that contain C, Si, and H, where bond breaking and bond making are important. The widespread use of Brenner’s REBO potential, its ability to model both zero-Kelvin elastic constants of diamond and the temperature dependence of the elastic constants, and the existence of parameters for many atom types were the motivating factors for obtaining this parametrization for Si. While Si-C-H classical bond-order potentials do exist, they are based on Brenner’s original formalism. This new parametrization is validated by examining the structure and stability of a large number of crystalline silicon structures, by examining the relaxation energies of point defects, the energies of silicon surfaces, the effects of adatoms on surface energies, and the structures of both liquid silicon and amorphous silicon. Finally, the elastic constants of diamond-cubic and amorphous silicon between 0 and 1100 K are calculated with this new parametrization and compared to values calculated using a previously published potential. read less D. Murdick, H. Wadley, and X. W. Zhou, “Condensation mechanisms of an arsenic-rich vapor on GaAs (001) surfaces,” Physical Review B. 2007. link Times cited: 21 Abstract: The homoepitaxial assembly of a 001 GaAs surface from atomic… read more Abstract: The homoepitaxial assembly of a 001 GaAs surface from atomic gallium and molecular As2 vapor fluxes has been investigated with molecular dynamics simulations using a recently developed bond-order potential. The approach enables dynamic atomic assembly events to be observed as atoms condense to form thin film structures. During simulation of epitaxial growth, we observed a temperature-dependent arsenic solubility limit consistent with experimental results. The As2 sticking probabilities and dynamic dimer-surface binding states for both galliumand arsenic-terminated 001 surfaces were also explored. On gallium-terminated surfaces, significant switching between two weakly bound precursor states and an intermediate chemisorbed state was observed during the surface diffusion of arsenic dimers. The switching frequency was strongly temperature dependent. The arsenic dimers bound to arsenic-terminated surfaces were found to be more likely to desorb instead of diffuse when thermally perturbed from their adsorption sites. This sticking probability was strongly dependent on surface temperature, atomic adsorption site environment, and the orientation of the incoming dimer. read less R. Drautz, X. W. Zhou, D. Murdick, B. Gillespie, H. Wadley, and D. Pettifor, “Analytic bond-order potentials for modelling the growth of semiconductor thin films,” Progress in Materials Science. 2007. link Times cited: 28 T. Hammerschmidt, E. Schöll, and M. Scheffler, “Growth simulations of InAs/GaAs quantum dots.” 2006. link Times cited: 6 Abstract: Semiconductor nanostructures, and particularly quantum dots … read more Abstract: Semiconductor nanostructures, and particularly quantum dots (QDs), have promising potential for technical applications such as light-emitting diodes, lasers, new devices, and quantum computers. But the big number of QDs needed, less than billions are hardly useful, is far beyond the means of normal manufacturing methods. For this nanotechnology to prevail, the QDs have to build themselves by self-assembly and self-organization. In this work, we study the growth of InAs QDs on GaAs substrates. For this purpose we developed a many-body potential of the Abell-Tersoff type that is able to account for the energetic balance of strain relief and QD side-facet formation during QD growth. It simultaneously captures many microscopic quantities of In, Ga, As, GaAs, and InAs bulk phases, as well as GaAs and InAs surface structures as obtained from experiment and density-functional theory (DFT) calculations with good overall accuracy. Its predictions for biaxial strained GaAs and InAs are in good agreement with DFT calculations and analytic results of continuum-elasticity theory. Based on recent STM results, we set up detailed atomic structures of InAs QDs with InAs wetting layers and homogenous InAs films on GaAs, relax them with our potential, and compare the resulting total energies. We show that the lateral elastic interaction of ‘hut’-like QDs dominated by {317} facets is significantly larger than that of ‘dome’-like QDs dominated by {101} facets. A strain-tensor analysis suggests that this effect is due to the relative orientations of the QD side facets to the elastic principal axes. Our calculated onset of the Stranski-Krastanov growth mode with respect to the InAs coverage is in good agreement with experimentally deduced values. The critical nucleus for QD formation is approximately 70 In atoms in size and poses an energy barrier of 5.3 eV. Furthermore, we can explain the experimentally observed shape sequence of ‘hut’-like QDs and ‘dome’-like QDs through the finding of distinct stability regimes. The regime separation depends strongly on the chemical potentials and the QD density. The experimental finding of vertical growth correlation in QD stacks can be explained by a distinct minimum in the potential-energy-surface (PES) of freestanding QDs in different lateral positions above overgrown QDs. This effect vanishes with increasing distance between the stacked QDs. The energy gain observed in our calculations can lower the energy barrier for QD formation to 3.5 eV and the size of the critical nucleus to only 25 In atoms. Additionally, we calculated the PES for In adsorption on surfaces that correspond to major side facets of ‘hut’and ‘dome’-like QDs by means of DFT to study possible kinetic effects. The dominating diffusion paths are perpendicular and parallel to the QD contour lines on {317} facets, but only perpendicular on {101} facets. The In incorporation on {317} facets could be kinetically limited due to the high barrier of approximately 1 eV for breaking As dimers. The diffusion barriers on {101} facets are lowered near the bottom of ‘dome’-like QDs, which supports the interpretation of the {317} facets on top as kinetic effect. read less X. W. Zhou, D. Murdick, and H. Wadley, “An electron counting modification to potentials for covalently bonded surfaces,” Journal of Applied Physics. 2006. link Times cited: 4 Abstract: The surface structure of covalently bonded semiconductor mat… read more Abstract: The surface structure of covalently bonded semiconductor materials undergoes reconstructions that are driven by electron redistribution between dangling and interatom bonds. Conventional interatomic potentials account for neither this electron redistribution nor its effects upon the atomic structure of surfaces. We have utilized an electron counting analysis to develop a surface interatomic potential that captures many of the effects of electron redistribution upon the surface structures of covalently bonded materials. The contributions from this potential decrease rapidly to zero beneath a surface. As a result, this surface potential can be added to many interatomic potentials for covalent materials without affecting its predictions of bulk properties such as cohesive energy, lattice parameters, and elastic constants. We demonstrate the approach by combining the surface potential with a recently proposed bond order potential and use it in a molecular statics simulation of the atomic reconstruction of a w... read less L. Safina, J. Baimova, and R. Mulyukov, “Nickel nanoparticles inside carbon nanostructures: atomistic simulation,” Mechanics of Advanced Materials and Modern Processes. 2019. link Times cited: 17 S. Winczewski, J. Dziedzic, and J. Rybicki, “Central-force decomposition of spline-based modified embedded atom method potential,” Modelling and Simulation in Materials Science and Engineering. 2016. link Times cited: 0 Abstract: Central-force decompositions are fundamental to the calculat… read more Abstract: Central-force decompositions are fundamental to the calculation of stress fields in atomic systems by means of Hardy stress. We derive expressions for a central-force decomposition of the spline-based modified embedded atom method (s-MEAM) potential. The expressions are subsequently simplified to a form that can be readily used in molecular-dynamics simulations, enabling the calculation of the spatial distribution of stress in systems treated with this novel class of empirical potentials. We briefly discuss the properties of the obtained decomposition and highlight further computational techniques that can be expected to benefit from the results of this work. To demonstrate the practicability of the derived expressions, we apply them to calculate stress fields due to an edge dislocation in bcc Mo, comparing their predictions to those of linear elasticity theory. read less
Funding	Not available

Short KIM ID The unique KIM identifier code.	SM_104202807866_001
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_BOP_MurdickZhouWadley_2006_GaAs__SM_104202807866_001
DOI	10.25950/436e95e3 https://doi.org/10.25950/436e95e3 https://commons.datacite.org/doi.org/10.25950/436e95e3
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	bop
Simulator Potential	bop
Run Compatibility	portable-models

Previous Version	Sim_LAMMPS_BOP_MurdickZhouWadley_2006_GaAs__SM_104202807866_000

Verification Check Dashboard

(Click here to learn more about Verification Checks)

Grade	Name	Category	Brief Description	Full Results	Aux File(s)
N/A Unable to perform verification check due to an error.	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
N/A Unable to perform verification check due to an error.	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
F The model is C^0 continuous. This means that the model has continuous energy, but a discontinuous first derivative.	vc-dimer-continuity-c1	informational	The energy versus separation relation of a pair of atoms is C1 continuous (i.e. the function and its first derivative are continuous); see full description.	Results	Files
N/A Unable to perform verification check due to an error.	vc-objectivity	informational	Total energy is unchanged and forces transform correctly under rigid-body translation and rotation; see full description.	Results	Files
N/A Unable to perform verification check due to an error.	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: As

Species: Ga

Tests

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 As in AFLOW crystal prototype A_cP1_221_a v002	view	93277
Equilibrium crystal structure and energy for Ga in AFLOW crystal prototype A_hR22_166_ae3h v002	view	8077009
Equilibrium crystal structure and energy for As in AFLOW crystal prototype A_hR2_166_c v002	view	101449
Equilibrium crystal structure and energy for As in AFLOW crystal prototype A_oC8_64_f v002	view	56325
Equilibrium crystal structure and energy for As in AFLOW crystal prototype A_tI4_139_e v002	view	88492
Equilibrium crystal structure and energy for AsGa in AFLOW crystal prototype AB_cF8_216_a_c v002	view	131560
Equilibrium crystal structure and energy for AsGa in AFLOW crystal prototype AB_cP16_205_c_c v002	view	70299
Equilibrium crystal structure and energy for AsGa in AFLOW crystal prototype AB_hP4_186_b_b v002	view	55899

EquilibriumCrystalStructure__TD_457028483760_003

Equilibrium structure and energy for a crystal structure at zero temperature and pressure v003

Creators:
Contributor: ilia
Publication Year: 2025
DOI: https://doi.org/10.25950/866c7cfa

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 Ga in AFLOW crystal prototype A_cI12_220_a v003	view	223956
Equilibrium crystal structure and energy for Ga in AFLOW crystal prototype A_oC40_63_2cf3g v003	view	433740
Equilibrium crystal structure and energy for Ga in AFLOW crystal prototype A_oC4_63_c v003	view	1131169
Equilibrium crystal structure and energy for Ga in AFLOW crystal prototype A_oC8_63_g v003	view	229401
Equilibrium crystal structure and energy for Ga in AFLOW crystal prototype A_oC8_64_f v003	view	200015

Errors

EquilibriumCrystalStructure__TD_457028483760_000

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for Ga in AFLOW crystal prototype A_hR22_166_ae3h v000	other	view
Equilibrium crystal structure and energy for Ga in AFLOW crystal prototype A_oC4_63_c v000	other	view
Equilibrium crystal structure and energy for Ga in AFLOW crystal prototype A_oC8_63_g v000	other	view
Equilibrium crystal structure and energy for Ga in AFLOW crystal prototype A_oC8_64_f v000	other	view
Equilibrium crystal structure and energy for As in AFLOW crystal prototype A_tI4_139_e v000	other	view

EquilibriumCrystalStructure__TD_457028483760_002

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for AsGa in AFLOW crystal prototype AB_oI4_44_a_b v002	other	view
Equilibrium crystal structure and energy for AsGa in AFLOW crystal prototype AB_oP2_25_a_b v002	other	view

EquilibriumCrystalStructure__TD_457028483760_003

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for Ga in AFLOW crystal prototype A_mC2_12_a v003	other	view
Equilibrium crystal structure and energy for Ga in AFLOW crystal prototype A_mC4_15_e v003	other	view
Equilibrium crystal structure and energy for Ga in AFLOW crystal prototype A_tI2_139_a v003	other	view

LatticeConstantCubicEnergy__TD_475411767977_007

Test	Error Categories	Link to Error page
Equilibrium zero-temperature lattice constant for bcc As v007	other	view
Equilibrium zero-temperature lattice constant for bcc Ga v007	other	view
Equilibrium zero-temperature lattice constant for diamond As v007	other	view
Equilibrium zero-temperature lattice constant for diamond Ga v007	other	view
Equilibrium zero-temperature lattice constant for fcc As v007	other	view
Equilibrium zero-temperature lattice constant for fcc Ga v007	other	view
Equilibrium zero-temperature lattice constant for sc As v007	other	view
Equilibrium zero-temperature lattice constant for sc Ga v007	other	view

LatticeConstantHexagonalEnergy__TD_942334626465_005

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

No Driver

Verification Check	Error Categories	Link to Error page
DimerContinuityC1__VC_303890932454_004	other	view
PeriodicitySupport__VC_895061507745_004	other	view

Files

CMakeLists.txt
GaAs.bop.table
LICENSE
kimprovenance.edn
kimspec.edn
smspec.edn

Download

Sim_LAMMPS_BOP_MurdickZhouWadley_2006_GaAs__SM_104202807866_001.txz	Tar+XZ	Linux and OS X archive
Sim_LAMMPS_BOP_MurdickZhouWadley_2006_GaAs__SM_104202807866_001.zip	Zip	Windows archive

Wiki

Wiki is ready to accept new content.

Sim_LAMMPS_BOP_MurdickZhouWadley_2006_GaAs__SM_104202807866_001

Verification Check Dashboard

Visualizers (in-page)

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

Tests

Errors

Files

Download

Wiki