EMT potential for Cu-Mg metallic glasses developed by Bailey, Schiotz, and Jacobsen (2004) v001

Karsten W. Jacobsen; Nicholas P. Bailey; Jakob Schiøtz

doi:10.25950/dfe6edcd

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EMT_Asap_MetalGlass_BaileySchiotzJacobsen_2004_CuMg__MO_228059236215_001

Interatomic potential for Copper (Cu), Magnesium (Mg).
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Title A single sentence description.	EMT potential for Cu-Mg metallic glasses developed by Bailey, Schiotz, and Jacobsen (2004) v001
Description A short description of the Model describing its key features including for example: type of model (pair potential, 3-body potential, EAM, etc.), modeled species (Ac, Ag, ..., Zr), intended purpose, origin, and so on.	Effective Medium Theory (EMT) model based on the EMT implementation in ASAP (https://wiki.fysik.dtu.dk/asap). Effective Medium Theory is a many-body potential of the same class as Embedded Atom Method, Finnis-Sinclair etc. The main term in the energy per atom is the local density of atoms. The functional form implemented here is that of Ref. 1. The principles behind EMT are described in Refs. 2 and 3 (with 2 being the more detailed and 3 being the most pedagogical). Be aware that the functional form and even some of the principles have changed since refs 2 and 3. EMT can be considered the last step of a series of approximations starting with Density Functional Theory; see Ref 4. This model implements a special parametrization optimized for CuMg [5] bulk metallic glasses only! It probably gives reasonable results for other CuMg compounds. These files are based on Asap version 3.11.5. REFERENCES: [1] Jacobsen, K. W., Stoltze, P., & Nørskov, J.: "A semi-empirical effective medium theory for metals and alloys". Surf. Sci. 366, 394–402 (1996). [2] Jacobsen, K. W., Nørskov, J., & Puska, M.: "Interatomic interactions in the effective-medium theory". Phys. Rev. B 35, 7423–7442 (1987). [3] Jacobsen, K. W.: "Bonding in Metallic Systems: An Effective-Medium Approach". Comments Cond. Mat. Phys. 14, 129-161 (1988). [4] Chetty, N., Stokbro, K., Jacobsen, K. W., & Nørskov, J.: "Ab initio potential for solids". Phys. Rev. B 46, 3798–3809 (1992). [5] Bailey, N., Schiøtz, J., & Jacobsen, K. W.: "Simulation of Cu-Mg metallic glass: Thermodynamics and structure". Phys. Rev. B 69, 144205 (2004). KNOWN ISSUES / BUGS: * On-the-fly modifications of the parameters is not supported, and should be implemented in the future.
Species The supported atomic species.	Cu, Mg
Disclaimer A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.	None
Content Origin	https://gitlab.com/asap/asap

Contributor	Jakob Schiøtz
Maintainer	Jakob Schiøtz
Developer	Karsten W. Jacobsen Nicholas P. Bailey Jakob Schiøtz
Published on KIM	2019
How to Cite	This Model originally published in [1-3] is archived in OpenKIM [4-7]. [1] Jacobsen KW, Stoltze P, Nørskov JK. A semi-empirical effective medium theory for metals and alloys. Surface Science. 1996;366(2):394–402. doi:10.1016/0039-6028(96)00816-3 [2] Bailey NP, Schiøtz J, Jacobsen KW. Simulation of Cu-Mg metallic glass: Thermodynamics and structure. Physical Review B. 2004Apr;69(14):144205. doi:10.1103/PhysRevB.69.144205 — (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. [3] Bailey NP, Schiøtz J, Jacobsen KW. Erratum: Simulation of Cu-Mg metallic glass: Thermodynamics and structure. Physical Review B. 2017Aug;96(5):059904. doi:10.1103/PhysRevB.96.059904 [4] Jacobsen KW, Bailey NP, Schiøtz J. EMT potential for Cu-Mg metallic glasses developed by Bailey, Schiotz, and Jacobsen (2004) v001. OpenKIM; 2019. doi:10.25950/dfe6edcd [5] Jacobsen KW, Stoltze P, Nørskov JK. Effective Medium Theory (EMT) potential driver v004. OpenKIM; 2019. doi:10.25950/7e5b8be7 [6] 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 [7] 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. 56 Citations (32 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 . J. Chun and B. Lee, “Atomistic calculations of mechanical properties of Ni-Ti-C metallic glass systems,” Journal of Mechanical Science and Technology. 2013. link Times cited: 3 J. Chun and B. Lee, “Atomistic calculations of mechanical properties of Ni-Ti-C metallic glass systems,” Journal of Mechanical Science and Technology. 2013. link Times cited: 0 S. Zhao, J. Li, and B. Liu, “Local structure of the Zr–Al metallic glasses studied by proposed n-body potential through molecular dynamics simulation,” Journal of Materials Research. 2010. link Times cited: 9 Abstract: An n -body potential is first constructed for the Zr–Al syst… read more Abstract: An n -body potential is first constructed for the Zr–Al system and proven to be realistic by reproducing a number of important properties of the system. Applying the constructed potential, molecular dynamics simulations, chemical short-range order (CSRO) calculation, and Honeycutt and Anderson (HA) pair analysis are carried out to study the Zr–Al metallic glasses. It is found that for the binary Zr–Al system, metallic glasses are energetically favored to be formed within composition range of 35–75 at.% Al. The calculation shows that the CSRO parameter is negative and could be up to −0.17, remarkably indicating that there exists a chemical short-range order in the Zr–Al metallic glasses. The HA pair analysis also reveals that there are diverse short-range packing units in the Zr–Al metallic glasses, in which icosahedra and icosahedra/face-centered cubic (fcc)-defect structures are predominant. read less S. Jiang, M. Jiang, L. Dai, and Y. Yao, “Atomistic Origin of Rate-Dependent Serrated Plastic Flow in Metallic Glasses,” Nanoscale Research Letters. 2008. link Times cited: 23 N. Bailey, J. Schiøtz, A. Lemaître, and K. Jacobsen, “Avalanche size scaling in sheared three-dimensional amorphous solid.,” Physical review letters. 2007. link Times cited: 74 Abstract: We study the statistics of plastic rearrangement events in a… read more Abstract: We study the statistics of plastic rearrangement events in a simulated amorphous solid at T=0. Events are characterized by the energy release and the "slip volume", the product of plastic strain and system volume. Their distributions for a given system size L appear to be exponential, but a characteristic event size cannot be inferred, because the mean values of these quantities increase as Lalpha with alpha approximately 3/2. In contrast with results obtained in 2D models, we do not see simply connected avalanches. The exponent suggests a fractal shape of the avalanches, which is also evidenced by the mean fractal dimension and participation ratio. read less N. Bailey, J. Schiøtz, and K. Jacobsen, “Atomistic simulation study of the shear-band deformation mechanism in Mg-Cu metallic glasses,” Physical Review B. 2006. link Times cited: 81 Abstract: We have simulated plastic deformation of a model Mg-Cu metal… read more Abstract: We have simulated plastic deformation of a model Mg-Cu metallic glass in order to study shear banding. In uniaxial tension, we find a necking instability occurs rather than shear banding. We can force the latter to occur by deforming in plane strain, forbidding the change of length in one of the transverse directions. Furthermore, in most of the simulations a notch is used to initiate shear bands, which lie at a 45 deg. angle to the tensile loading direction. The shear bands are characterized by the Falk and Langer local measure of plastic deformation D{sub min}{sup 2}, averaged here over volumes containing many atoms. The D{sub min}{sup 2} profile has a peak whose width is around 10 nm; this width is largely independent of the strain rate. Most of the simulations were, at least nominally, at 100 K, about T{sub g}/3 for this system. The development of the shear bands takes a few tens of ps, once plastic flow has started, more or less independent of strain rate. The shear bands can also be characterized using a correlation function defined in terms of D{sub min}{sup 2}, which, moreover, can detect incipient shear bands in cases where they do not fullymore » form. By averaging the kinetic energy over small regions, the local temperature can be calculated, and this is seen to be higher in the shear bands by about 50-100 K. Increases in temperature appear to initiate from interactions of the shear bands with the free surfaces and with each other, and are delayed somewhat with respect to the localization of plastic flow itself. We observe a slight decrease in density, up to 1%, within the shear band, which is consistent with notions of increased free volume or disorder within a plastically deforming amorphous material.« less read less B. Waters, D. S. Karls, I. Nikiforov, R. Elliott, E. Tadmor, and B. Runnels, “Automated determination of grain boundary energy and potential-dependence using the OpenKIM framework,” Computational Materials Science. 2022. link Times cited: 5 N. Dubinin and R. Ryltsev, “Self-Diffusion Coefficients of Components in Liquid Binary Alloys of Noble Metals,” Metals. 2022. link Times cited: 1 Abstract: An accurate determination of transport coefficients in liqui… read more Abstract: An accurate determination of transport coefficients in liquids, such as diffusivity, is crucial for studying fundamental chemical processes, for constructing and verifying model theories of liquid, and for the optimization of technological processes. However, a reliable experimental determination of the diffusivity is a difficult and sometimes nearly impossible task. In this regard, the development of model theories that allow calculating characteristics of atomic transport is of special interest. Here, the concentration dependencies of the self-diffusion coefficients of the components in Cu-Ag, Cu-Au, and Ag-Au liquid alloys at T = 1423 K and T = 1573 K are calculated in the framework of the linear trajectory approximation in conjunction with the square-well model and the semi-analytical representation of the mean spherical approximation. We reveal that peculiarities in the behavior of the obtained dependencies are related to the peculiarities of the phase diagrams of the alloys under consideration. Additionally, we verify our calculation method on Al80-Cu20 and Al80-Au20 liquid alloys. The results obtained are in good agreement with available experimental and molecular-dynamic simulation data. In the cases when the experimental information is not available, the presented results can be considered as predictive to estimate the quantities under consideration approximately. read less K. Saksl et al., “Atomic structure of the Mg66Zn30Ca4 metallic glass,” Journal of Non-crystalline Solids. 2021. link Times cited: 1 L. Chen, Q. Chen, D. Ando, Y. Sutou, M. Kubo, and J. Koike, “Potential of low-resistivity Cu2Mg for highly scaled interconnects and its challenges,” Applied Surface Science. 2021. link Times cited: 8 D. Ma, J. Zhang, Y. Di, J. Wang, S. Guan, and T. Zhang, “Atomic structure of Co 92− x B x Ta 8 glassy alloys studied by ab initio molecular dynamics simulations,” International Journal of Quantum Chemistry. 2020. link Times cited: 1 R. Dai, R. Ashcraft, A. Gangopadhyay, and K. Kelton, “Predicting metallic glass formation from properties of the high temperature liquid,” Journal of Non-crystalline Solids. 2019. link Times cited: 11 X. Yue, C. Liu, S. Pan, A. Inoue, P. Liaw, and C. Fan, “Effect of cooling rate on structures and mechanical behavior of Cu50Zr50 metallic glass: A molecular-dynamics study,” Physica B: Condensed Matter. 2018. link Times cited: 24 M. Kbirou, M. Mazroui, and A. Hasnaoui, “Atomic packing and fractal behavior of Al-Co metallic glasses,” Journal of Alloys and Compounds. 2018. link Times cited: 17 W. Cui, C. Peng, L. Wang, Y. Qi, and T. Fang, “Structure and dynamics of undercooled FeNi,” Physics and Chemistry of Liquids. 2014. link Times cited: 2 Abstract: Molecular dynamics simulation has been performed to explore … read more Abstract: Molecular dynamics simulation has been performed to explore the structural and dynamical properties of undercooled FeNi melt based on the embedded atom method (EAM), namely due to G. Bonny. The simulated partial pair correlation function (PPCF) and coordination number (CN) of liquid FeNi indicate that no stronger interaction of heterogenic atom pairs than those of the same atom pairs happen in melts. FeNi melt is close to an ideal mixing system without chemical short-range order (CSRO). The undercooled FeNi exhibits icosahedral short-range order (ISRO) that is reflected directly as a large number of 1551, 1541 bonded pairs as well as snapshot of icosahedron clusters. The mean squared displacement (MSD) and self diffusion coefficient of Fe and Ni is quite similar, which is consistent with the strong glass formation liquid of Ni36Zr64. Our work gives the detailed structure and dynamics information of undercooled FeNi melt. read less J. Ding, Y. Q. Cheng, and E. Ma, “Charge-transfer-enhanced prism-type local order in amorphous Mg65Cu25Y10: Short-to-medium-range structural evolution underlying liquid fragility and heat capacity,” Acta Materialia. 2013. link Times cited: 53 J.-C. Huang, S. Chang, and H. Chen, “Evaluation of Microstructure and Glass Transition Temperature of Al-Cu-Cr-Fe-Ni High-Entropy Alloy by Molecular Dynamics Simulation,” Advanced Materials Research. 2012. link Times cited: 2 Abstract: In this study, the microstructure and glass transition tempe… read more Abstract: In this study, the microstructure and glass transition temperature (Tg) of five elements (Al-Cu-Cr-Fe-Ni) high-entropy alloy was evaluated under different Al content by molecular dyItalic textnamics (MD) simulations. The ensemble and COMPASS potential were used. Firstly, the Al-Cu-Cr-Fe-Ni high-entropy alloys were melted at high temperature and were cooled with a high quenching rate further. The radial distribution function (RDF),Wendt-Abraham parameter and X-ray diffractometer (XRD) were used to analyze the change on the microstructure and glass transition temperature (Tg) of Al-Cu-Cr-Fe-Ni high-entropy alloys. Simulation results show that the micro-structure of different aluminum content of AlxCuCrFeNi alloy after fast quenching are all amorphous state. When the aluminum content decreased, the amorphous state are more obvious and the glass transition temperature decreases. read less C. Wang and C. Wong, “Short-to-medium range order of Al–Mg metallic glasses studied by molecular dynamics simulations,” Journal of Alloys and Compounds. 2011. link Times cited: 37 B. Jelinek et al., “Modified embedded atom method potential for Al, Si, Mg, Cu, and Fe alloys,” Physical Review B. 2011. link Times cited: 218 Abstract: A set of modified embedded-atom method (MEAM) potentials for… read more Abstract: A set of modified embedded-atom method (MEAM) potentials for the interactions between Al, Si, Mg, Cu, and Fe was developed from a combination of each element's MEAM potential in order to study metal alloying. Previously published MEAM parameters of single elements have been improved for better agreement to the generalized stacking fault energy (GSFE) curves when compared with ab initio generated GSFE curves. The MEAM parameters for element pairs were constructed based on the structural and elastic properties of element pairs in the NaCl reference structure garnered from ab initio calculations, with adjustment to reproduce the ab initio heat of formation of the most stable binary compounds. The new MEAM potentials were validated by comparing the formation energies of defects, equilibrium volumes, elastic moduli, and heat of formation for several binary compounds with ab initio simulations and experiments. Single elements in their ground-state crystal structure were subjected to heating to test the potentials at elevated temperatures. An Al potential was modified to avoid formation of an unphysical solid structure at high temperatures. The thermal expansion coefficient of a compound with the composition of AA 6061 alloy was evaluated and compared with experimental values. MEAM potential tests performed in this work, utilizing the universal atomistic simulation environment (ASE), are distributed to facilitate reproducibility of the results. read less Y. Cheng and E. Ma, “Atomic-level structure and structure–property relationship in metallic glasses,” Progress in Materials Science. 2011. link Times cited: 1296 D. S. Liu, J. Qin, and T. Gu, “The structure of liquid Mg–Cu binary alloys,” Journal of Non-crystalline Solids. 2010. link Times cited: 16 A. Paduraru, U. G. Andersen, A. Thyssen, N. Bailey, K. Jacobsen, and J. Schiøtz, “Computer simulations of nanoindentation in Mg–Cu and Cu–Zr metallic glasses,” Modelling and Simulation in Materials Science and Engineering. 2010. link Times cited: 17 Abstract: The formation of shear bands during plastic deformation of C… read more Abstract: The formation of shear bands during plastic deformation of Cu0.50Zr0.50 and Mg0.85Cu0.15 metallic glasses is studied using atomic-scale computer simulations. The atomic interactions are described using realistic many-body potentials within the effective medium theory, and are compared with similar simulations using a Lennard-Jones description of the material. The metallic glasses are deformed both in simple shear and in a simulated nanoindentation experiment. Plastic shear localizes into shear bands with a width of approximately 5 nm in CuZr and 8 nm in MgCu. In simple shear, the shear band formation is very clear, whereas only incipient shear bands are seen in nanoindentation. The shear band formation during nanoindentation is sensitive to the indentation velocity, indenter radius and the cooling rate during the formation of the metallic glass. For comparison, a similar nanoindentation simulation was made with a nanocrystalline sample, showing how the presence of a polycrystalline structure leads to a different and more spatially distributed deformation pattern, where dislocation avalanches play an important role. read less F. Delogu, “A numerical investigation of the stability of nanometer-sized amorphous structures,” Intermetallics. 2010. link Times cited: 2 Z. Hou, L.-X. Liu, R.-su Liu, Z.-an Tian, and J. Wang, “Short-range and medium-range order in Ca7Mg3 metallic glass,” Journal of Applied Physics. 2010. link Times cited: 34 Abstract: A molecular dynamics simulation has been performed on the ra… read more Abstract: A molecular dynamics simulation has been performed on the rapid quenching processes of Ca7Mg3 alloy including 100 000 atoms. The structures of short-range order (SRO) and medium-range order (MRO) in Ca7Mg3 metallic glass are investigated by means of several structural analysis methods. It is found that the SRO in Ca7Mg3 metallic glass can be modeled by neither a uniquely prescribed stereo-chemical structure nor five Bernal polyhedra but rather various types of basic clusters in which the icosahedron is dominant. The local energy together with the geometrical constraint plays very important roles in the favorable local structure in metal glasses. The MRO in Ca7Mg3 metallic glass is characterized by certain types of extended icosahedral clusters combined by intercross-sharing atoms in the form of chains or dendrites, which is different from the fcc or icosahedral building schemes for the MRO in metallic glasses with significant chemical SRO. The size distributions of these MRO clusters present a magic numbe... read less F. Liu, R.-su Liu, Z. Hou, H.-rong Liu, Z.-an Tian, and L.-li Zhou, “Formation mechanism of atomic cluster structures in Al–Mg alloy during rapid solidification processes,” Annals of Physics. 2009. link Times cited: 26 A. Takeuchi, K. Yubuta, and A. Inoue, “Phase stability of Cu2Mg and CuMg2 compounds against noncrystallizations analyzed with a plastic crystal model,” Intermetallics. 2008. link Times cited: 7 N. Bailey, U. R. Pedersen, N. Gnan, T. Schrøder, and J. Dyre, “Pressure-energy correlations in liquids. I. Results from computer simulations.,” The Journal of chemical physics. 2008. link Times cited: 187 Abstract: We show that a number of model liquids at fixed volume exhib… read more Abstract: We show that a number of model liquids at fixed volume exhibit strong correlations between equilibrium fluctuations of the configurational parts of (instantaneous) pressure and energy. We present detailed results for 13 systems, showing in which systems these correlations are significant. These include Lennard-Jones liquids (both single- and two-component) and several other simple liquids, neither hydrogen-bonding liquids such as methanol and water, nor the Dzugutov liquid, which has significant contributions to pressure at the second nearest neighbor distance. The pressure-energy correlations, which for the Lennard-Jones case are shown to also be present in the crystal and glass phases, reflect an effective inverse power-law potential dominating fluctuations, even at zero and slightly negative pressure. An exception to the inverse power-law explanation is a liquid with hard-sphere repulsion and a square-well attractive part, where a strong correlation is observed, but only after time averaging. The companion paper [N. P. Bailey et al., J. Chem. Phys. 129, 184508 (2008)] gives a thorough analysis of the correlations, with a focus on the Lennard-Jones liquid, and a discussion of some experimental and theoretical consequences. read less W. Li, Z. Yan-ning, M. Xiu-Ming, and P. Chuan-xiao, “Formation of NiZr 2 Binary Metallic Glass: Experimental and Molecular Dynamics Analyses,” Chinese Physics Letters. 2007. link Times cited: 5 Abstract: The local atomic structure of an amorphous NiZr2 alloy is id… read more Abstract: The local atomic structure of an amorphous NiZr2 alloy is identified by using x-ray diffraction, transmission electron microscopy, and differential scanning calorimeter. Based on the experimental results, molecular dynamics simulation is performed to investigate the glass formation of liquid NiZr2 alloy. Some relevant features of the pair correlation functions are in good agreement with those obtained by experiment. The pair analysis parameters are calculated, suggesting that there exist icosahedral ordering, four-fold symmetrical bipyramid and triangular-faced polyhedral units in the amorphous NiZr2 structure. The result is beneficial to open avenues toward the understanding of fundamental theoretical problems of glass formation of simple binary alloys. read less M. Baricco et al., “Thermal stability and hardness of Mg–Cu–Au–Y amorphous alloys,” Journal of Alloys and Compounds. 2007. link Times cited: 14 S. Ö. Kart, M. Tomak, M. Uludoǧan, and T. Çagin, “Structural, thermodynamical, and transport properties of undercooled binary Pd–Ni alloys,” Materials Science and Engineering A-structural Materials Properties Microstructure and Processing. 2006. link Times cited: 15 N. Yedla and S. Ghosh, “Nature of atomic trajectories and convective flow during plastic deformation of amorphous Cu50Zr50 alloy at room temperature-classical molecular dynamics studies,” Intermetallics. 2017. link Times cited: 15 W. Zhao et al., “Atomic bond proportions and relations to physical properties in metallic glasses,” Materials & Design. 2015. link Times cited: 9 E. Kirova and V. Pisarev, “Morphological aspect of crystal nucleation in wall-confined supercooled metallic film,” Journal of Physics: Condensed Matter. 2020. link Times cited: 1 Abstract: In this paper, we simulate the nucleation and growth of crys… read more Abstract: In this paper, we simulate the nucleation and growth of crystalline nuclei in a molybdenum film cooled at different rates confined between two amorphous walls. We also compare the results for the wall-confined and wall-free systems. We apply the same methodology as in the work (Kirova and Pisarev 2019 J. Cryst. Growth 528 125266) which is based on reconstructing the probability density function for the largest crystalline nucleus in the system. The size of the nucleus and the asphericity parameter are considered as the reaction coordinates. We demonstrate that in both the free and confined systems there are two mechanisms of crystal growth: the attachment of atoms to the biggest crystal from the amorphous phase and the merging of the biggest crystal cluster with small ones (coalescence). We show that the attachment mechanism is dominant in the melt cooled down at a slower rate, and the mechanism gradually shifts to coalescence as cooling rate increases. We also observe the formation of long-lived crystal clusters and demonstrate that amorphous walls do not affect their geometric characteristics. However, system confined between walls demonstrates higher glass-forming ability. read less B. Parsaeifard, D. Tomerini, D. De, and S. Goedecker, “Maximum volume simplex method for automatic selection and classification of atomic environments and environment descriptor compression.,” The Journal of chemical physics. 2020. link Times cited: 3 Abstract: Fingerprint distances, which measure the similarity of atomi… read more Abstract: Fingerprint distances, which measure the similarity of atomic environments, are commonly calculated from atomic environment fingerprint vectors. In this work, we present the simplex method that can perform the inverse operation, i.e., calculating fingerprint vectors from fingerprint distances. The fingerprint vectors found in this way point to the corners of a simplex. For a large dataset of fingerprints, we can find a particular largest simplex, whose dimension gives the effective dimension of the fingerprint vector space. We show that the corners of this simplex correspond to landmark environments that can be used in a fully automatic way to analyze structures. In this way, we can, for instance, detect atoms in grain boundaries or on edges of carbon flakes without any human input about the expected environment. By projecting fingerprints on the largest simplex, we can also obtain fingerprint vectors that are considerably shorter than the original ones but whose information content is not significantly reduced. read less A. A. Deshmukh and S. Pal, “Dynamic probing of structural evolution for Co50Ni50 metallic glass during pressurized cooling using atomistic simulation,” Journal of Molecular Modeling. 2020. link Times cited: 1 T. Mizuguchi, S. Tatsumi, and S. Fujiwara, “Icosahedral order in liquid and glassy phases of cyclohexane,” Molecular Simulation. 2020. link Times cited: 1 Abstract: ABSTRACT We performed all-atom molecular dynamics simulation… read more Abstract: ABSTRACT We performed all-atom molecular dynamics simulations for bulk cyclohexane and analysed the short- and medium-range structures in supercooled and glassy states by using the Voronoi tessellation technique. From the analyses of both the potential energy of the system and the radial distribution function of molecules, cyclohexane was found to be vitrified as the temperature decreased. Furthermore, the icosahedral-like local structures are dominant at all temperatures and grow in a supercooled liquid, whereas the face-centred cubic structures do not grow when the temperature decreases. It was also ascertained that the icosahedral-like structure is more dominant than the full-icosahedral one. The network of the distorted icosahedron spreads throughout the system at low temperatures. Our simulation demonstrates the stability of the icosahedral local structure even in a non-spherical molecule such as cyclohexane. read less B. Bocklund, R. Otis, A. Egorov, A. Obaied, I. Roslyakova, and Z.-kui Liu, “ESPEI for efficient thermodynamic database development, modification, and uncertainty quantification: application to Cu–Mg,” MRS Communications. 2019. link Times cited: 47 Abstract: The software package ESPEI has been developed for efficient … read more Abstract: The software package ESPEI has been developed for efficient evaluation of thermodynamic model parameters within the CALPHAD method. ESPEI uses a linear fitting strategy to parameterize Gibbs energy functions of single phases based on their thermochemical data and refines the model parameters using phase equilibrium data through Bayesian parameter estimation within a Markov Chain Monte Carlo machine learning approach. In this paper, the methodologies employed in ESPEI are discussed in detail and demonstrated for the Cu–Mg system down to 0 K using unary descriptions based on segmented regression. The model parameter uncertainties are quantified and propagated to the Gibbs energy functions. read less X. Yue, C. Liu, S. Pan, A. Inoue, P. Liaw, and C. Fan, “Effect of concentration on the structure of isothermally-annealed CuZr metallic glasses,” Materials Science and Technology. 2018. link Times cited: 4 Abstract: ABSTRACT To clarify the influence of isothermal annealing on… read more Abstract: ABSTRACT To clarify the influence of isothermal annealing on CuxZr100-x (x = 36, 44, 50, 56, and 64) metallic glasses, the annealing process was conducted using molecular dynamics (MD) simulation. The local structure is analysed by means of the radial distribution functions, Voronoi tessellation and the nearest-neighbour correlation index, Cij. The results show that Cu-centered < 0 0 12 0 > and Zr-centered < 0 0 12 4 > dramatically increases after an isothermal annealing treatment and presents a strong tendency of being the nearest neighbour with each other, as the Cu concentration is over 50%. These two kinds of clusters are formed the Cu2Zr Laves phase which can be directly observed in the Cu-rich glasses. read less Y. Shi, “Creating Atomic Models of Brittle Glasses for In Silico Mechanical Tests,” International Journal of Applied Glass Science. 2016. link Times cited: 5 Abstract: Atomic level computer simulation has become indispensable in… read more Abstract: Atomic level computer simulation has become indispensable in understanding the mechanical properties of glasses, among other properties. However, the majority of model glasses are more ductile than their intended experimental counterparts, partially reflected by the overestimation of the Poisson's ratio. We have previously introduced an effective force field tuning method of imposing an additional energy penalty term to embrittle a binary Lennard–Jones glass. Here, we improved this method by varying the applied range of the energy penalty. The new method stabilizes the model glass even for high energy penalty values. Furthermore, unlike the old method, there is no unintended reduction in density for brittle glasses. Uniaxial tension tests were conducted to show the ductile-to-brittle transition as the energy penalty increases in strength. Crack propagation simulation was also conducted to demonstrate the efficacy of studying brittle fracture using the model glass. read less P. M. Larsen, S. Schmidt, and J. Schiøtz, “Robust structural identification via polyhedral template matching,” Modelling and Simulation in Materials Science and Engineering. 2016. link Times cited: 532 Abstract: Successful scientific applications of large-scale molecular … read more Abstract: Successful scientific applications of large-scale molecular dynamics often rely on automated methods for identifying the local crystalline structure of condensed phases. Many existing methods for structural identification, such as common neighbour analysis, rely on interatomic distances (or thresholds thereof) to classify atomic structure. As a consequence they are sensitive to strain and thermal displacements, and preprocessing such as quenching or temporal averaging of the atomic positions is necessary to provide reliable identifications. We propose a new method, polyhedral template matching (PTM), which classifies structures according to the topology of the local atomic environment, without any ambiguity in the classification, and with greater reliability than e.g. common neighbour analysis in the presence of thermal fluctuations. We demonstrate that the method can reliably be used to identify structures even in simulations near the melting point, and that it can identify the most common ordered alloy structures as well. In addition, the method makes it easy to identify the local lattice orientation in polycrystalline samples, and to calculate the local strain tensor. An implementation is made available under a Free and Open Source Software license. read less S. Adibi, P. S. Branicio, Y. Zhang, and S. Joshi, “Composition and grain size effects on the structural and mechanical properties of CuZr nanoglasses,” Journal of Applied Physics. 2014. link Times cited: 66 Abstract: Nanoglasses (NGs), metallic glasses (MGs) with a nanoscale g… read more Abstract: Nanoglasses (NGs), metallic glasses (MGs) with a nanoscale grain structure, have the potential to considerably increase the ductility of traditional MGs while retaining their outstanding mechanical properties. We investigated the effects of composition on the structural and mechanical properties of CuZr NG films with grain sizes between 3 to 15 nm using molecular dynamics simulations. Results indicate a transition from localized shear banding to homogeneous superplastic flow with decreasing grain size, although the critical average grain size depends on composition: 5 nm for Cu36Zr64 and 3 nm for Cu64Zr36. The flow stress of the superplastic NG at different compositions follows the trend of the yield stress of the parent MG, i.e., Cu36Zr64 yield/flow stress: 2.54 GPa/1.29 GPa and Cu64Zr36 yield/flow stress: 3.57 GPa /1.58 GPa. Structural analysis indicates that the differences in mechanical behavior as a function of composition are rooted at the distinct statistics of prominent atomic Voronoi polyhedra. T... read less A. Malins, S. R. Williams, J. Eggers, and C. Royall, “Identification of structure in condensed matter with the topological cluster classification.,” The Journal of chemical physics. 2013. link Times cited: 115 Abstract: We describe the topological cluster classification (TCC) alg… read more Abstract: We describe the topological cluster classification (TCC) algorithm. The TCC detects local structures with bond topologies similar to isolated clusters which minimise the potential energy for a number of monatomic and binary simple liquids with m ≤ 13 particles. We detail a modified Voronoi bond detection method that optimizes the cluster detection. The method to identify each cluster is outlined, and a test example of Lennard-Jones liquid and crystal phases is considered and critically examined. read less O. Senkov, Y. Cheng, and Y. Cheng, “Ab Initio Molecular Dynamics Simulation of the Amorphous Structure of Ca-Mg-Cu and Ca-Mg-Zn Alloys,” Metallurgical and Materials Transactions A. 2013. link Times cited: 9 O. Senkov, Y. Cheng, D. Miracle, E. Barney, A. Hannon, and C. Woodward, “Atomic structure of Ca40+XMg25Cu35−X metallic glasses,” Journal of Applied Physics. 2012. link Times cited: 28 Abstract: The atomic structures of four Ca40+XMg25Cu35−X (X = 0, 5, 10… read more Abstract: The atomic structures of four Ca40+XMg25Cu35−X (X = 0, 5, 10, and 20 at. %) ternary metallic glasses have been determined using a synergistic combination of neutron diffraction, ab initio molecular dynamics (MD) simulation, and constrained reverse Monte Carlo modeling. It is described as close-packing of efficiently packed Cu-centered clusters that have Ca, Mg, and Cu atoms in the first coordination shell. The close-packed arrangement of the clusters provides a characteristic medium range order in these alloys. An average coordination number (CN) of 10 (with about 5–7 Ca, 2–3 Mg, and 1–2 Cu atoms) is most common for the Cu-centered clusters. The average coordination numbers around Mg and Ca are 12–13 (∼6–8 Ca, 3 Mg, and 1–4 Cu) and 13–15 (7–9 Ca, 3–4 Mg, and 2–5 Cu), respectively, and they are composition dependent. Strong interaction of Cu with Mg and Ca results in pair bond shortening. Icosahedral short range order does not dominate in these amorphous alloys, although polytetrahedral packing and five-fo... read less N. Wang, L. Ji, W. Yao, and Y. Zheng, “Correlation between fragility and eutectic instability and glass-forming ability in binary metallic glasses under growth controlled conditions,” Journal of Applied Physics. 2012. link Times cited: 5 Abstract: We find that the fragility can be correlated to the eutectic… read more Abstract: We find that the fragility can be correlated to the eutectic instability and the glass forming ability in binary metallic glass formers under growth controlled conditions via a dimensionless parameter β defined as DfT0/2(Te − T0), where Df is fragility parameter, T0 is Vogel-Fulcher-Tammann temperature, and Te is eutectic temperature. It is shown that the large β value, which results from high Df and from that T0 is close to the eutectic temperature, can lead to small interface growth velocity and undercooling of eutectic structure, and good glass forming ability. This indicates that high β leads to small characteristic diffusion length resulting from sluggish material transport that governs the glass forming ability. The results might provide an in-depth insight into the glass formation mechanism and be helpful for searching new glasses in growth controlled process. read less J. Pang, M. Tan, and K. M. Liew, “Structural evolution of Ti50Cu50 on rapid cooling by molecular dynamics simulation,” Applied Physics A. 2012. link Times cited: 4 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 J. Wang, J. Wang, P. Hodgson, J. Zhang, W. Yan, and C. Yang, “Effects of quenching rate on amorphous structures of Cu46Zr54 metallic glass,” Journal of Materials Processing Technology. 2009. link Times cited: 33 L. Yang, X.-L. Wang, A. Stoica, J. Almer, D. Shi, and W. H. Wang, “Multistage Devitrification Behavior of Mg65Cu25Tb10 Bulk Metallic Glass,” Metallurgical and Materials Transactions A. 2008. link Times cited: 6 P. Jóvári et al., “Atomic structure of glassy Mg60Cu30Y10 investigated with EXAFS, x-ray and neutron diffraction, and reverse Monte Carlo simulations,” Physical Review B. 2007. link Times cited: 30 Abstract: Short range order of amorphous Mg{sub 60}Cu{sub 30}Y{sub 10}… read more Abstract: Short range order of amorphous Mg{sub 60}Cu{sub 30}Y{sub 10} was investigated by x-ray and neutron diffraction, Cu and Y K-edge x-ray absorption fine structure measurements, and the reverse Monte Carlo simulation technique. We found that Mg-Mg and Mg-Cu nearest neighbor distances are very similar to values found in crystalline Mg{sub 2}Cu. The Cu-Y coordination number is 1.1{+-}0.2, and the Cu-Y distance is {approx}4% shorter than the sum of atomic radii, suggesting that attraction between Cu and Y plays an important role in stabilizing the glassy state. Thermal stability and structure evolution upon annealing were also studied by differential scanning calorimetry and in situ x-ray powder diffraction. The alloy shows a glass transition and three crystallization events, the first and dominant one at 456 K corresponding to eutectic crystallization of at least three phases: Mg{sub 2}Cu and most likely cubic MgY and CuMgY. read less A. Paduraru, A. Kenoufi, N. Bailey, and J. Schiøtz, “An Interatomic Potential for Studying CuZr Bulk Metallic Glasses,” Advanced Engineering Materials. 2007. link Times cited: 22 Abstract: Binary alloys capable of forming metallic glasses have been … read more Abstract: Binary alloys capable of forming metallic glasses have been discovered recently. The mechanical properties of BMGs are remarkably different from the ones of ordinary metallic alloys due to the atomic level disorder in the glassy state. Unlike crystalline materials plastic deformation in metallic glasses cannot be caused by lattice defects but takes place through atomic-scale deformation events and may furthermore involve localization through formation of shear bands. For understanding the origin of their mechanical properties it is important to get the basic understanding of fundamental theoretical problems through atomistic simulations. Molecular dynamics (MD) treats atomic systems according to Newtonian mechanic laws. Atoms are point particles, interacting through an interatomic potential, describing the energy of an atom as a function of the positions of all atoms in a neighboring region of space. The time evolution of the system is obtained by numerically integrating Newton’s second law. Often the interatomic potential is a classical potential, no quantum mechanical description of the material is attempted, but the functional form of the potential may be derived from quantum mechanical arguments. MD is able to treat systems with millions of atoms, and permits the average calculations of transport (diffusion, thermal conductivities, viscosity), or mechanical quantities (elastic constant, plastic yield), and also the modeling of complex phenomena (shear band localization, fracture appearance, neutronic cascades). The quality of the results will depend on the quality of the interatomic potential, simple potentials giving a less accurate description of the interatomic interactions while allowing very large simulations, more complicated potentials may give a better description of the interaction, but limit the simulation size. Many-body potentials such as the Embedded Atom Method and the Effective Medium Theory (EMT) have been shown to give a good description of the late transition metals crystallizing in close-packed structures, and their alloys, while still allowing simulations with millions of atoms. In this paper, we create an EMT potential optimized for modeling the mechanical and thermodynamic properties of CuZr bulk metallic glass. CuZr was recently discovered to be a binary bulk metallic glass. Since binary alloys are easier to model than alloys with more elements, this makes CuZr an attractive bulk metallic glass to study theoretically. Previously, an interatomic force field has been fitted to CuZr by Duan et al., but we find that the EMT force field described here provides a better description of the structure of the metallic glass. The potential developed here will be used to model the mechanical properties of CuZr, to be published elsewhere. read less G. Liang, H. Fang, D. Katz, Z. Tang, and K. Salama, “Phase formation in Cu-sheathed MgB2 wires,” Physica C-superconductivity and Its Applications. 2006. link Times cited: 19 P. Demo, A. M. Sveshnikov, K. Nitsch, M. Rodová, and Z. Kožíšek, “Duration of nucleation process in supercooled halide melts.,” The Journal of chemical physics. 2005. link Times cited: 1 Abstract: We present a model allowing to estimate the so-called time l… read more Abstract: We present a model allowing to estimate the so-called time lag of nucleating halide melts using electrical conductivity measurements. Due to the complex-forming nature of molten halide salts we suppose two basic types of charge carriers in the melt: complexes (playing the role of monomers-building units) and clusters of a newly forming solid phase. Within context of the nonstationary nucleation theory we determined a formula expressing the time dependency of electrical conductivity of such a system and compared this result with the experimental data obtained for the melts of PbBr2, PbCl2, and KPb2Cl5. In terms of this formula the time lag of nucleation may be estimated. This important quantity characterizing the moment from which the nucleated clusters only grow to the macroscopic sizes has been found to be approximately 75% of the total duration of the nucleation process itself. read less G. Duan et al., “Molecular dynamics study of the binary Cu_(46)Zr_(54) metallic glass motivated by experiments: Glass formation and atomic-level structure,” Physical Review B. 2005. link Times cited: 216 Abstract: We have identified a binary bulk metallic glass forming allo… read more Abstract: We have identified a binary bulk metallic glass forming alloy Cu_(46_Zr_(54) by analyzing the structure and thermal behaviors of copper mold cast samples using x-ray diffraction, transmission electron microscopy, and differential scanning calorimeter. Motivated by these experimental results, we fitted the effective Rosato-Guillope-Legrand-type force field parameters for the binary Cu-Zr alloy system and the atomistic description of glass formation and structure analysis of the Cu_(46)Zr_(54) alloy based on molecular dynamics simulation will be also presented. read less J. Pang, “Metallic glasses : thermal, mechanical properties and their correlation.” 2012. link Times cited: 0 W. Guang-hai, P. Hui, K. Fu-jiu, X. Meng-Fen, and B. Yilong, “Study Of Mechanical Properties Of Amorphous Copper With Molecular Dynamics Simulation,” Chinese Physics B. 2008. link Times cited: 8 Abstract: The formation and mechanical properties of amorphous copper … read more Abstract: The formation and mechanical properties of amorphous copper are studied using molecular dynamics simulation. The simulations of tension and shearing show that more pronounced plasticity is found under shearing, compared to tension. Apparent strain hardening and strain rate effect are observed. Interestingly, the variations of number density of atoms during deformation indicate free volume creation, especially under higher strain rate. In particular, it is found that shear induced dilatation does appear in the amorphous metal. read less
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_228059236215_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.	EMT_Asap_MetalGlass_BaileySchiotzJacobsen_2004_CuMg__MO_228059236215_001
DOI	10.25950/dfe6edcd https://doi.org/10.25950/dfe6edcd https://commons.datacite.org/doi.org/10.25950/dfe6edcd
KIM Item Type Specifies whether this is a Portable Model (software implementation of an interatomic model); Portable Model with parameter file (parameter file to be read in by a Model Driver); Model Driver (software implementation of an interatomic model that reads in parameters).	Portable Model using Model Driver EMT_Asap__MD_128315414717_004
Driver	EMT_Asap__MD_128315414717_004
KIM API Version	2.0.2
Potential Type	eam

Previous Version	EMT_Asap_MetalGlass_BaileySchiotzJacobsen_2004_CuMg__MO_228059236215_000

Verification Check Dashboard

(Click here to learn more about Verification Checks)

Grade	Name	Category	Brief Description	Full Results	Aux File(s)
P All elements claimed by model are supported in at least one of the tested configurations.	vc-species-supported-as-stated	mandatory	The model supports all species it claims to support; see full description.	Results	Files
P Periodic boundary conditions were correctly supported for all configurations that the model was able to compute.	vc-periodicity-support	mandatory	Periodic boundary conditions are handled correctly; see full description.	Results	Files
P Model energy has permutation symmetry for all configurations the model was able to compute.	vc-permutation-symmetry	mandatory	Total energy and forces are unchanged when swapping atoms of the same species; see full description.	Results	Files
A The letter grade A was assigned because the normalized error in the computation was 1.53139e-09 compared with a machine precision of 2.22045e-16. The letter grade was based on 'score=log10(error/eps)', with ranges A=[0, 7.5], B=(7.5, 10.0], C=(10.0, 12.5], D=(12.5, 15.0), F>15.0. 'A' is the best grade, and 'F' indicates failure.	vc-forces-numerical-derivative	consistency	Forces computed by the model agree with numerical derivatives of the energy; see full description.	Results	Files
F The model is C^-1 continuous. This means that the model has discontinuous energy.	vc-dimer-continuity-c1	informational	The energy versus separation relation of a pair of atoms is C1 continuous (i.e. the function and its first derivative are continuous); see full description.	Results	Files
P Model energy and forces are invariant with respect to rigid-body motion (translation and rotation) for all configurations the model was able to compute.	vc-objectivity	informational	Total energy is unchanged and forces transform correctly under rigid-body translation and rotation; see full description.	Results	Files
P Model energy has inversion symmetry for all configurations the model was able to compute.	vc-inversion-symmetry	informational	Total energy is unchanged and forces change sign when inverting a configuration through the origin; see full description.	Results	Files
P No memory leak detected.	vc-memory-leak	informational	The model code does not have memory leaks (i.e. it releases all allocated memory at the end); see full description.	Results	Files
P All threads give identical results for tested case. Model appears to be thread-safe.	vc-thread-safe	mandatory	The model returns the same energy and forces when computed in serial and when using parallel threads for a set of configurations. Note that this is not a guarantee of thread safety; see full description.	Results	Files
P Unit conversion successful	vc-unit-conversion	mandatory	The model is able to correctly convert its energy and/or forces to different unit sets; see full description.	Results	Files

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

Species: Mg

Species: Cu

Cohesive Energy Graph

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

Species: Mg

Species: Cu

Diamond Lattice Constant

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

Species: Mg

Species: Cu

Dislocation Core Energies

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

(No matching species)

FCC Elastic Constants

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

Species: Cu

Species: Mg

FCC Lattice Constant

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

Species: Cu

Species: Mg

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.

Species: Cu

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.

Species: Cu

SC Lattice Constant

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

Species: Mg

Species: Cu

Cubic Crystal Basic Properties Table

Species: Cu

Species: Mg

Tests

CohesiveEnergyVsLatticeConstant__TD_554653289799_003

Cohesive energy versus lattice constant curve for monoatomic cubic lattices v003

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

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

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Cohesive energy versus lattice constant curve for bcc Cu v004	view	3764
Cohesive energy versus lattice constant curve for bcc Mg v004	view	2188
Cohesive energy versus lattice constant curve for diamond Cu v004	view	2572
Cohesive energy versus lattice constant curve for diamond Mg v004	view	2198
Cohesive energy versus lattice constant curve for fcc Cu v004	view	3392
Cohesive energy versus lattice constant curve for fcc Mg v004	view	2317
Cohesive energy versus lattice constant curve for sc Cu v004	view	2128
Cohesive energy versus lattice constant curve for sc Mg v004	view	2356

ElasticConstantsCrystal__TD_034002468289_000

Elastic constants for arbitrary crystals at zero temperature and pressure v000

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

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Elastic constants for CuMg in AFLOW crystal prototype A2B_cF24_227_c_b at zero temperature and pressure v000		view	100254

ElasticConstantsCubic__TD_011862047401_006

Elastic constants for cubic crystals at zero temperature and pressure v006

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

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

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Elastic constants for bcc Cu at zero temperature v006	view	5918
Elastic constants for bcc Mg at zero temperature v006	view	1631
Elastic constants for diamond Mg at zero temperature v001	view	7262
Elastic constants for fcc Cu at zero temperature v006	view	2175
Elastic constants for fcc Mg at zero temperature v006	view	5886
Elastic constants for sc Cu at zero temperature v006	view	1887
Elastic constants for sc Mg at zero temperature v006	view	3871

ElasticConstantsHexagonal__TD_612503193866_003

Elastic constants for hexagonal crystals at zero temperature v003

Creators: Junhao Li
Contributor: jl2922
Publication Year: 2018
DOI: https://doi.org/10.25950/2e4b93d9

Computes the elastic constants for hcp crystals by calculating the hessian of the energy density with respect to strain. An estimate of the error associated with the numerical differentiation performed is reported.

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Elastic constants for hcp Cu at zero temperature		view	2354
Elastic constants for hcp Mg at zero temperature		view	1580

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 Cu in AFLOW crystal prototype A_cF4_225_a v001		view	78038
Equilibrium crystal structure and energy for Cu in AFLOW crystal prototype A_cI2_229_a v001		view	73252

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	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 CuMg in AFLOW crystal prototype A2B_cF24_227_c_b v002		view	202695
Equilibrium crystal structure and energy for CuMg in AFLOW crystal prototype AB2_oF48_70_e_ef v002		view	1278199

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 Mg in AFLOW crystal prototype A_cF4_225_a v003	view	142239
Equilibrium crystal structure and energy for Mg in AFLOW crystal prototype A_cI2_229_a v003	view	169268
Equilibrium crystal structure and energy for Mg in AFLOW crystal prototype A_hP2_194_c v003	view	173672

GrainBoundaryCubicCrystalSymmetricTiltRelaxedEnergyVsAngle__TD_410381120771_003

Relaxed energy as a function of tilt angle for a symmetric tilt grain boundary within a cubic crystal v003

Creators:
Contributor: brunnels
Publication Year: 2022
DOI: https://doi.org/10.25950/2c59c9d6

Computes grain boundary energy for a range of tilt angles given a crystal structure, tilt axis, and material.

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)
Relaxed energy as a function of tilt angle for a 100 symmetric tilt grain boundary in fcc Cu v001	view	13070426
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Cu v001	view	77964377
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Cu v001	view	46660295
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Cu v001	view	159963373

LatticeConstantCubicEnergy__TD_475411767977_007

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

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

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

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Equilibrium zero-temperature lattice constant for bcc Cu v007	view	1887
Equilibrium zero-temperature lattice constant for bcc Mg v007	view	1887
Equilibrium zero-temperature lattice constant for diamond Cu v007	view	3039
Equilibrium zero-temperature lattice constant for diamond Mg v007	view	3647
Equilibrium zero-temperature lattice constant for fcc Cu v007	view	3711
Equilibrium zero-temperature lattice constant for fcc Mg v007	view	3711
Equilibrium zero-temperature lattice constant for sc Cu v007	view	1951
Equilibrium zero-temperature lattice constant for sc Mg v007	view	2335

LatticeConstantHexagonalEnergy__TD_942334626465_004

Equilibrium lattice constants for hexagonal bulk structures at zero temperature and pressure v004

Creators: Junhao Li
Contributor: jl2922
Publication Year: 2018
DOI: https://doi.org/10.25950/25bcc28b

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Equilibrium lattice constants for hcp Cu		view	7835
Equilibrium lattice constants for hcp Mg		view	5159

LinearThermalExpansionCoeffCubic__TD_522633393614_001

Linear thermal expansion coefficient of cubic crystal structures v001

Creators: Mingjian Wen
Contributor: mjwen
Publication Year: 2019
DOI: https://doi.org/10.25950/fc69d82d

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Linear thermal expansion coefficient of fcc Cu at 293.15 K under a pressure of 0 MPa v001		view	21607866

PhononDispersionCurve__TD_530195868545_004

Phonon dispersion relations for an fcc lattice v004

Creators: Matt Bierbaum
Contributor: mattbierbaum
Publication Year: 2019
DOI: https://doi.org/10.25950/64f4999b

Calculates the phonon dispersion relations for fcc lattices and records the results as curves.

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)
Phonon dispersion relations for fcc Cu v004		view	49775

StackingFaultFccCrystal__TD_228501831190_002

Stacking and twinning fault energies of an fcc lattice at zero temperature and pressure v002

Creators:
Contributor: SubrahmanyamPattamatta
Publication Year: 2019
DOI: https://doi.org/10.25950/b4cfaf9a

Intrinsic and extrinsic stacking fault energies, unstable stacking fault energy, unstable twinning energy, stacking fault energy as a function of fractional displacement, and gamma surface for a monoatomic FCC lattice at zero temperature and pressure.

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)
Stacking and twinning fault energies for fcc Cu v002		view	13717139

SurfaceEnergyCubicCrystalBrokenBondFit__TD_955413365818_004

High-symmetry surface energies in cubic lattices and broken bond model v004

Creators: Matt Bierbaum
Contributor: mattbierbaum
Publication Year: 2019
DOI: https://doi.org/10.25950/6c43a4e6

Calculates the surface energy of several high symmetry surfaces and produces a broken-bond model fit. In latex form, the fit equations are given by:

E_{FCC} (\vec{n}) = p_1 (4 \left( |x+y| + |x-y| + |x+z| + |x-z| + |z+y| +|z-y|\right)) + p_2 (8 \left( |x| + |y| + |z|\right)) + p_3 (2 ( |x+ 2y + z| + |x+2y-z| + |x-2y + z| + |x-2y-z| + |2x+y+z| + |2x+y-z| +|2x-y+z| +|2x-y-z| +|x+y+2z| +|x+y-2z| +|x-y+2z| +|x-y-2z| ) + c

E_{BCC} (\vec{n}) = p_1 (6 \left( | x+y+z| + |x+y-z| + |-x+y-z| + |x-y+z| \right)) + p_2 (8 \left( |x| + |y| + |z|\right)) + p_3 (4 \left( |x+y| + |x-y| + |x+z| + |x-z| + |z+y| +|z-y|\right)) +c.

In Python, these two fits take the following form:

def BrokenBondFCC(params, index):

import numpy
x, y, z = index
x = x / numpy.sqrt(x**2.+y**2.+z**2.)
y = y / numpy.sqrt(x**2.+y**2.+z**2.)
z = z / numpy.sqrt(x**2.+y**2.+z**2.)

return params[0]*4* (abs(x+y) + abs(x-y) + abs(x+z) + abs(x-z) + abs(z+y) + abs(z-y)) + params[1]*8*(abs(x) + abs(y) + abs(z)) + params[2]*(abs(x+2*y+z) + abs(x+2*y-z) +abs(x-2*y+z) +abs(x-2*y-z) + abs(2*x+y+z) +abs(2*x+y-z) +abs(2*x-y+z) +abs(2*x-y-z) + abs(x+y+2*z) +abs(x+y-2*z) +abs(x-y+2*z) +abs(x-y-2*z))+params[3]

def BrokenBondBCC(params, x, y, z):

import numpy
x, y, z = index
x = x / numpy.sqrt(x**2.+y**2.+z**2.)
y = y / numpy.sqrt(x**2.+y**2.+z**2.)
z = z / numpy.sqrt(x**2.+y**2.+z**2.)

return params[0]*6*(abs(x+y+z) + abs(x-y-z) + abs(x-y+z) + abs(x+y-z)) + params[1]*8*(abs(x) + abs(y) + abs(z)) + params[2]*4* (abs(x+y) + abs(x-y) + abs(x+z) + abs(x-z) + abs(z+y) + abs(z-y)) + params[3]

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)
Broken-bond fit of high-symmetry surface energies in fcc Cu v004		view	50319

VacancyFormationEnergyRelaxationVolume__TD_647413317626_001

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

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

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Monovacancy formation energy and relaxation volume for fcc Cu		view	595663

VacancyFormationMigration__TD_554849987965_001

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

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

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Vacancy formation and migration energy for fcc Cu		view	1919581

Errors

ElasticConstantsCubic__TD_011862047401_006

Test	Error Categories	Link to Error page
Elastic constants for diamond Cu at zero temperature v001	other	view

LatticeConstantHexagonalEnergy__TD_942334626465_005

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

StackingFaultFccCrystal__TD_228501831190_001

Test	Error Categories	Link to Error page
Stacking and twinning fault energies for fcc Cu	other	view

No Driver

Verification Check	Error Categories	Link to Error page
PeriodicitySupport__VC_895061507745_004	other	view

Files

CMakeLists.txt
EMT_Asap_MetalGlass_BaileySchiotzJacobsen_2004_CuMg__MO_228059236215.params
LICENSE
LICENSE.CDDL
LICENSE.GPL
LICENSE.LGPL
README
kimprovenance.edn
kimspec.edn

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EMT_Asap__MD_128315414717_004.zip	Zip	Windows archive

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EMT_Asap_MetalGlass_BaileySchiotzJacobsen_2004_CuMg__MO_228059236215_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

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