EAM potential (LAMMPS cubic hermite tabulation) for the Pb-Cu system developed by Hoyt et al. (2003) v005

Mark Asta; J. J. Hoyt; Justin Garvin; EB Webb III

doi:10.25950/f6e7d52c

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EAM_Dynamo_HoytGarvinWebb_2003_PbCu__MO_119135752160_005

Interatomic potential for Copper (Cu), Lead (Pb).
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Title A single sentence description.	EAM potential (LAMMPS cubic hermite tabulation) for the Pb-Cu system developed by Hoyt et al. (2003) v005
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.	A simple procedure is used to formulate a Cu–Pb pair interaction function within the embedded atom (EAM) method framework. Embedding, density and pair functions for pure Cu and pure Pb are taken from previously published EAM studies. Optimization of the Cu–Pb potential was achieved by comparing with experiment the computed heats of mixing for Cu–Pb liquid alloys and the equilibrium phase diagram, the latter being determined via a thermodynamic integration technique. The topology of the temperature-composition phase diagram computed with this EAM potential is consistent with experiment and features a liquid–liquid miscibility gap, low solubility of Pb in solid Cu and a monotectic reaction at approximately 1012 K.
Species The supported atomic species.	Cu, Pb
Disclaimer A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.	None
Content Origin	http://www.ctcms.nist.gov/potentials/Pb.html

Contributor	J. J. Hoyt
Maintainer	J. J. Hoyt
Developer	Mark Asta J. J. Hoyt Justin Garvin EB Webb III
Published on KIM	2018
How to Cite	This Model originally published in [1] is archived in OpenKIM [2-5]. [1] Hoyt JJ, Garvin JW, III EBW, Asta M. An embedded atom method interatomic potential for the Cu–Pb system. Modelling and Simulation in Materials Science and Engineering. 2003;11(3):287. doi:10.1088/0965-0393/11/3/302 — (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] Asta M, Hoyt JJ, Garvin J, III EBW. EAM potential (LAMMPS cubic hermite tabulation) for the Pb-Cu system developed by Hoyt et al. (2003) v005. OpenKIM; 2018. doi:10.25950/f6e7d52c [3] Foiles SM, Baskes MI, Daw MS, Plimpton SJ. EAM Model Driver for tabulated potentials with cubic Hermite spline interpolation as used in LAMMPS v005. OpenKIM; 2018. doi:10.25950/68defa36 [4] Tadmor EB, Elliott RS, Sethna JP, Miller RE, Becker CA. The potential of atomistic simulations and the Knowledgebase of Interatomic Models. JOM. 2011;63(7):17. doi:10.1007/s11837-011-0102-6 [5] Elliott RS, Tadmor EB. Knowledgebase of Interatomic Models (KIM) Application Programming Interface (API). OpenKIM; 2011. doi:10.25950/ff8f563a Click here to download the above citation in BibTeX format.
Citations This panel presents information regarding the papers that have cited the interatomic potential (IP) whose page you are on. The OpenKIM machine learning based Deep Citation framework is used to determine whether the citing article actually used the IP in computations (denoted by "USED") or only provides it as a background citation (denoted by "NOT USED"). For more details on Deep Citation and how to work with this panel, click the documentation link at the top of the panel. The word cloud to the right is generated from the abstracts of IP principle source(s) (given below in "How to Cite") and the citing articles that were determined to have used the IP in order to provide users with a quick sense of the types of physical phenomena to which this IP is applied. The bar chart shows the number of articles that cited the IP per year. Each bar is divided into green (articles that USED the IP) and blue (articles that did NOT USE the IP). Users are encouraged to correct Deep Citation errors in determination by clicking the speech icon next to a citing article and providing updated information. This will be integrated into the next Deep Citation learning cycle, which occurs on a regular basis. OpenKIM acknowledges the support of the Allen Institute for AI through the Semantic Scholar project for providing citation information and full text of articles when available, which are used to train the Deep Citation ML algorithm.	This panel provides information on past usage of this interatomic potential (IP) powered by the OpenKIM Deep Citation framework. The word cloud indicates typical applications of the potential. The bar chart shows citations per year of this IP (bars are divided into articles that used the IP (green) and those that did not (blue)). The complete list of articles that cited this IP is provided below along with the Deep Citation determination on usage. See the Deep Citation documentation for more information. 53 Citations (37 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 . I. Talyzin and V. Samsonov, “Molecular Dynamics of Solid State Spreading in a Pb (Nanoparticle)/Cu (Substrate) System,” Bulletin of the Russian Academy of Sciences: Physics. 2019. link Times cited: 0 V. Korolev, V. Samsonov, and P. Protsenko, “Molecular Dynamics Simulation of Unstable Equilibrium of a Spherical Nucleus for Determining the Interfacial Energy in a Pb–Cu Two-Component System,” Colloid Journal. 2019. link Times cited: 0 P. Zhao, Y.-bo Guo, F. Zhang, Y. He, and Y. Yan, “Element proportion effect on internal stress from interfaces and other microstructural components in Cu–Pb alloys,” Molecular Simulation. 2019. link Times cited: 2 Abstract: ABSTRACT Polycrystalline materials like Cu–Pb alloy consist … read more Abstract: ABSTRACT Polycrystalline materials like Cu–Pb alloy consist of four types of microstructural components, including grain cells, grain boundaries, triple junctions and vertex points, the mechanical properties of which governed by the atomic proportion of the alloy elements to a certain degree. The internal stresses from such microstructural components are quite different. Due to experimental limitations, the internal stresses from the alloy materials are difficult to measure directly, especially in the microstructural components. Here, we report a bottom-up approach using an atomistic calculation to obtain atomic properties in Cu-based alloy, as well as that in the microstructural components. The results reveal that a steep stress gradient exists at the interfaces of the alloy, which decreases significantly with the increase of the Pb. The defects evolution process in the alloy samples are investigated during tensile loading, revealing that the defect nucleation is delayed due to the decreasing von Mises stress gradient in the interfaces region as Pb increased. And the increased hydrostatic pressure in the interfaces regions, as a secondary factor can promote the defect nucleation. Among alloy samples with a grain size of 18.58 nm, that with 6.6 at.% Pb has minimal defects and the best mechanical properties. read less M. Chatzidakis, S. Prabhudev, P. Saidi, C. Chiang, J. Hoyt, and G. Botton, “Bulk Immiscibility at the Edge of the Nanoscale.,” ACS nano. 2017. link Times cited: 8 Abstract: In the quest to identify more effective catalyst nanoparticl… read more Abstract: In the quest to identify more effective catalyst nanoparticles for many industrially important applications, the Au-Pt system has gathered considerable attention. Despite considerable effort the interplay between phase equilibrium behavior and surface segregation in Au-Pt nanoparticles is still poorly understood. Here we investigate the phase equilibrium behavior of 20 nm Au-Pt nanoparticles using a combination of high-resolution scanning transmission electron microscopy and a hybrid Monte Carlo and molecular dynamics atomistic simulation technique. Our approach takes into account the effects of immiscibility, elastic strain, interfacial free energy, and surface segregation. This is used to explain two key phenomena taking place in these nanoparticles. The first is whether the binary system remains immiscible at the nanoscale, and if so what morphology would the secondary phase take. Our findings suggest that even at sizes of 20 nm, thermally equilibrated Au-Pt nanoparticles remain largely immiscible and behave thermodynamically as bulk-like systems. We explain why 20 nm Au-Pt nanoparticles phase separate into hemispheres as opposed to a thick-shelled core-shell structure. These insights are central to further optimization of Au-Pt nanoparticles toward enhanced catalytic activities. The phase-separated Janus particles observed in this study offer enhanced material functionality arising from the nonuniformity of their plasmonic, catalytic, and surface properties. read less J. P. Palafox-Hernandez and B. Laird, “Orientation dependence of heterogeneous nucleation at the Cu-Pb solid-liquid interface.,” The Journal of chemical physics. 2016. link Times cited: 16 Abstract: In this work, we examine the effect of surface structure on … read more Abstract: In this work, we examine the effect of surface structure on the heterogeneous nucleation of Pb crystals from the melt at a Cu substrate using molecular-dynamics (MD) simulation. In a previous work [Palafox-Hernandez et al., Acta Mater. 59, 3137 (2011)] studying the Cu/Pb solid-liquid interface with MD simulation, we observed that the structure of the Cu(111) and Cu(100) interfaces was significantly different at 625 K, just above the Pb melting temperature (618 K for the model). The Cu(100) interface exhibited significant surface alloying in the crystal plane in contact with the melt. In contrast, no surface alloying was seen at the Cu(111) interface; however, a prefreezing layer of crystalline Pb, 2-3 atomic planes thick and slightly compressed relative to bulk Pb crystal, was observed to form at the interface. We observe that at the Cu(111) interface the prefreezing layer is no longer present at 750 K, but surface alloying in the Cu(100) interface persists. In a series of undercooling MD simulations, heterogeneous nucleation of fcc Pb is observed at the Cu(111) interface within the simulation time (5 ns) at 592 K-a 26 K undercooling. Nucleation and growth at Cu(111) proceeded layerwise with a nearly planar critical nucleus. Quantitative analysis yielded heterogeneous nucleation barriers that are more than two orders of magnitude smaller than the predicted homogeneous nucleation barriers from classical nucleation theory. Nucleation was considerably more difficult on the Cu(100) surface-alloyed substrate. An undercooling of approximately 170 K was necessary to observe nucleation at this interface within the simulation time. From qualitative observation, the critical nucleus showed a contact angle with the Cu(100) surface of over 90°, indicating poor wetting of the Cu(100) surface by the nucleating phase, which according to classical heterogeneous nucleation theory provides an explanation of the large undercooling necessary to nucleate on the Cu(100) surface, relative to Cu(111), whose surface is more similar to the nucleating phase due to the presence of the prefreezing layer. read less T. Rupert, “Solid Solution Strengthening and Softening Due to Collective Nanocrystalline Deformation Physics,” arXiv: Materials Science. 2014. link Times cited: 34 L. Zhang, E. Martínez, A. Caro, X.-Y. Liu, and M. Demkowicz, “Liquid-phase thermodynamics and structures in the Cu–Nb binary system,” Modelling and Simulation in Materials Science and Engineering. 2013. link Times cited: 37 Abstract: An embedded atom method (EAM) interatomic potential is const… read more Abstract: An embedded atom method (EAM) interatomic potential is constructed to reproduce the main topological features of the experimental equilibrium phase diagram of the Cu–Nb system in both solid and liquid states. The potential is fitted to composition-dependent enthalpies of mixing for bcc and fcc random solid solutions obtained from first-principles calculations at 0 K. Compared with two other EAM Cu–Nb potentials in the literature, the phase diagram of the current potential shows better agreement with the experimental phase diagram. Our potential predicts that the Cu–Nb liquid phase at equilibrium is compositionally patterned over lengths of about 2.3 nm. The newly constructed potential may be used to study the effect of liquid thermodynamics and structure on properties of binary systems, such as radiation-induced mixing. read less C. Wu, D. A. Thomas, Z. Lin, and L. Zhigilei, “Runaway lattice-mismatched interface in an atomistic simulation of femtosecond laser irradiation of Ag film–Cu substrate system,” Applied Physics A. 2011. link Times cited: 39 C. Deng and F. Sansoz, “Fundamental differences in the plasticity of periodically twinned nanowires in Au, Ag, Al, Cu, Pb and Ni,” Acta Materialia. 2009. link Times cited: 136 Y. Sun and E. Webb, “The atomistic mechanism of high temperature contact line advancement: results from molecular dynamics simulations,” Journal of Physics: Condensed Matter. 2009. link Times cited: 13 Abstract: Atomic scale phenomena driving contact line advancement duri… read more Abstract: Atomic scale phenomena driving contact line advancement during the wetting of a solid by a liquid are investigated via molecular dynamics simulations of Ag(l) drops spreading on Ni substrates. For the homologous temperature ∼5% above melting for Ag, essentially non-reactive wetting is observed with relatively high spreading velocity. Analyzing atomic positions with time, including computing flow fields, permits investigation of atomic scale transport mechanisms associated with advancement of the contact line. Delivery of material to the contact line occurs preferentially along the liquid/vapor interface. Ag(l) atoms transported along the liquid/vapor interface become new droplet edge material, effectively displacing existing edge material. Evidence is also shown of a prominent transport and flow mechanism more typically associated with the molecular kinetic theory of spreading: some portion of Ag(l) atoms move along the solid/liquid interface to eventually occupy the contact line region. Selected atomic trajectories are shown to illustrate atoms moving with the contact line, detaching and re-attaching at sites along the solid/liquid interface. However, this latter solid/liquid interface transport mechanism contributed a lower percentage of new material to the advancing contact line compared to the liquid/vapor interface transport mechanism. Features of the AgNi system that may contribute to the dominance of a liquid/vapor interface transport mechanism are highlighted, including a relatively low liquid/vapor surface tension. read less D. Belashchenko, “Embedded atom model application to liquid metals: Liquid rubidium,” Russian Journal of Physical Chemistry. 2006. link Times cited: 13 S. Rana, D. S. Monder, and A. Chatterjee, “Thermodynamic calculations using reverse Monte Carlo: A computational workflow for accelerated construction of phase diagrams for metal hydrides,” Computational Materials Science. 2023. link Times cited: 0 W. Bian, X. Chen, W. Guo, H.-tao Xue, C. Chen, and Z. Yu, “Study of wetting promotion mechanism of Pb/Cu interface assisted by ultrasonic vibration from molecular dynamics simulation and experiments,” Materials Chemistry and Physics. 2023. link Times cited: 0 H. Men, C. Fang, and Z. Fan, “Prenucleation at the Liquid/Substrate Interface: An Overview,” Metals. 2022. link Times cited: 6 Abstract: Prenucleation refers to the phenomenon of substrate-induced … read more Abstract: Prenucleation refers to the phenomenon of substrate-induced atomic ordering in the liquid adjacent to the liquid/substrate interface at temperatures above the nucleation temperature. We investigated the effects of the physical and chemical properties of the substrate on prenucleation, using the classical molecular dynamics (MD) and ab initio MD simulations. We found that the physical origin of prenucleation is structural templating, which is affected significantly by the lattice misfit between the solid and the substrate, chemical interaction between the solid and the substrate, and the substrate surface roughness at the atomic level. Prenucleation ultimately determines the nucleation potency of a substrate and provides a precursor for heterogeneous nucleation at the nucleation temperature. In this paper, we provide an overview of the recent advances in the understanding of prenucleation made by the LiME Research Hub. After a brief review of the historical research on atomic ordering at the liquid/substrate interface in the literature, we present an overview of the recent advances in understanding prenucleation, covering the concept of prenucleation, the effect of temperature, lattice misfit and substrate chemistry, and substrate surface roughness at the atomic level. Our discussions will be focused on the effect of prenucleation on heterogeneous nucleation and its consequences on grain refinement. read less M. M. Rahman and S. R. Ahmed, “Effects of work-hardening and post thermal-treatment on tensile behaviour of solder-affected copper,” Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications. 2022. link Times cited: 1 Abstract: In order to explore the reuse potential of waste/scraped cop… read more Abstract: In order to explore the reuse potential of waste/scraped copper, an effective characterization of its functional properties under various operating conditions is of great practical importance. The present paper is an attempt to reconnoiter the solder-affected waste copper for high-value engineering applications through the characterization of major mechanical properties. More specifically, the tensile properties of traditional lead-solder-affected copper are investigated and analyzed under the influence of work-hardening and post-thermal treatments. The influential effects of individual elements of the solder on the tensile properties of copper are discussed in a comparative fashion, in which two additional alloy samples, namely, high-copper/tin alloy and high-copper/lead alloy are taken into consideration together with those of copper–tin–lead–alloy as well as pure copper samples. The results of the investigation show that the inclusion of trace-amount of tin and lead in copper affects the corresponding tensile behaviour quite significantly. The strength rising trends due to cold working are observed to be more prominent for the inclusion of lead compared to that of tin. The post-thermal treatments of the work-hardened alloy samples have lowered ultimate strength, yield strength and elastic modulus, but increased the fracture elongation at elevated temperatures. Strain rate variations are also found to be highly influential on all the tensile properties of the solder-affected alloys. Micrographs of the alloy samples have verified the changes in grain shape and grain size responsible for the variation of tensile properties. read less L. Wang and J. Hoyt, “Layering misalignment and negative temperature dependence of interfacial free energy of B2-liquid interfaces in a glass forming system,” Acta Materialia. 2021. link Times cited: 8 M. M. Rahman, S. R. Ahmed, and M. S. Kaiser, “On the investigation of reuse potential of SnPb-solder affected copper subjected to work-hardening and thermal ageing,” Materials Characterization. 2021. link Times cited: 6 S. Raman, J. Hoyt, P. Saidi, and M. Asta, “Molecular dynamics study of the thermodynamic and kinetic properties of the solid-liquid interface in FeMn,” Computational Materials Science. 2020. link Times cited: 14 J. Hou, H. J. Zhang, and S. H. Zhang, “Electrical Resistivity and Structure of Cu-Pb Alloy during Cooling Process,” IOP Conference Series: Materials Science and Engineering. 2020. link Times cited: 0 Abstract: The variations of electrical resistivity and cooling curve f… read more Abstract: The variations of electrical resistivity and cooling curve for monotectic Cu-Pb alloy have been measured from liquid state to ambient temperature. The structural transitions were discussed during cooling process. And the correlations between the variations of electrical resistivity, heat and structural transitions were also investigated. The linear relationship between the electrical resistivity and temperature curves in liquid state means there is no structural change in liquid Cu-Pb alloy. And during the solidification process, the electrical resistivity and cooling curves change with the occurrence of new phases. read less K. Ueno and Y. Shibuta, “Composition dependence of solid-liquid interfacial energy of Fe-Cr binary alloy from molecular dynamics simulations,” Computational Materials Science. 2019. link Times cited: 17 Y. Yang, S. Li, Y. Liang, and B. Li, “The wetting phenomenon and precursor film characteristics of Sn-37Pb/Cu under ultrasonic fields,” Materials Letters. 2019. link Times cited: 9 K. Ueno and Y. Shibuta, “Solute partition at solid-liquid interface of binary alloy from molecular dynamics simulation,” Materialia. 2018. link Times cited: 6 J. Hoyt, S. Raman, N. Ma, and M. Asta, “Unusual temperature dependence of the solid-liquid interfacial free energy in the Cu-Zr system,” Computational Materials Science. 2018. link Times cited: 21 H. N. Pishkenari, F. S. Yousefi, and A. Taghibakhshi, “Determination of surface properties and elastic constants of FCC metals: a comparison among different EAM potentials in thin film and bulk scale,” Materials Research Express. 2018. link Times cited: 22 Abstract: Three independent elastic constants C11, C12, and C44 were c… read more Abstract: Three independent elastic constants C11, C12, and C44 were calculated and compared using available potentials of eight different metals with FCC crystal structure; Gold, Silver, Copper, Nickel, Platinum, Palladium, Aluminum and Lead. In order to calculate the elastic constants, the second derivative of the energy density of each system was calculated with respect to different directions of strains. Each set of the elastic constants of the metals in bulk scale was compared with experimental results, and the average relative error was for each was calculated and compared with other available potentials. Then, using the Voigt-Reuss-Hill method, approximated values for Young and shear moduli and Poisson’s ratio of the FCC metals in the bulk scale were found for each potential. Furthermore, to observe the surface effects on the metals in nanoscale, surface elastic constants of the thin films of the metals have been calculated. In the study of the thin films of materials in nanoscale, the number of surface atoms is considerable compared to all atoms of the object. This leads to an increase in the surface effects, which influence the elastic properties. By considering this fact and employing related definitions and equations, the properties of the thin films of the metals were calculated, and the surface effects for different crystallographic directions were compared. Subsequently, in some cases, comparisons among characteristics of the metals in the thin film and bulk material were made. read less P. Saidi, C. Dai, T. Power, Z. Yao, and M. Daymond, “An embedded atom method interatomic potential for the zirconium-iron system,” Computational Materials Science. 2017. link Times cited: 5 X. Sun, S. Xiao, H. Deng, and W. Hu, “Molecular dynamics simulation of wetting behaviors of Li on W surfaces,” Fusion Engineering and Design. 2017. link Times cited: 14 S. M. Rassoulinejad-Mousavi, Y. Mao, and Y. Zhang, “Evaluation of Copper, Aluminum and Nickel Interatomic Potentials on Predicting the Elastic Properties,” arXiv: Computational Physics. 2016. link Times cited: 63 Abstract: Choice of appropriate force field is one of the main concern… read more Abstract: Choice of appropriate force field is one of the main concerns of any atomistic simulation that needs to be seriously considered in order to yield reliable results. Since, investigations on mechanical behavior of materials at micro/nanoscale has been becoming much more widespread, it is necessary to determine an adequate potential which accurately models the interaction of the atoms for desired applications. In this framework, reliability of multiple embedded atom method based interatomic potentials for predicting the elastic properties was investigated. Assessments were carried out for different copper, aluminum and nickel interatomic potentials at room temperature which is considered as the most applicable case. Examined force fields for the three species were taken from online repositories of National Institute of Standards and Technology (NIST), as well as the Sandia National Laboratories, the LAMMPS database. Using molecular dynamic simulations, the three independent elastic constants, C11, C12 and C44 were found for Cu, Al and Ni cubic single crystals. Voigt-Reuss-Hill approximation was then implemented to convert elastic constants of the single crystals into isotropic polycrystalline elastic moduli including Bulk, Shear and Young's modulus as well as Poisson's ratio. Simulation results from massive molecular dynamic were compared with available experimental data in the literature to justify the robustness of each potential for each species. Eventually, accurate interatomic potentials have been recommended for finding each of the elastic properties of the pure species. Exactitude of the elastic properties was found to be sensitive to the choice of the force fields. Those potentials were fitted for a specific compound may not necessarily work accurately for all the existing pure species. read less S. Fensin, S. Valone, E. Cerreta, P. Rigg, and G. Gray, “Nucleation and Evolution of Dynamic Damage at Cu/Pb Interfaces using Molecular Dynamics,” Bulletin of the American Physical Society. 2015. link Times cited: 4 Abstract: For ductile metals, the process of dynamic fracture occurs t… read more Abstract: For ductile metals, the process of dynamic fracture occurs through nucleation, growth and coalescence of voids. For high purity single-phase metals, it has been observed by numerous investigators that voids tend to heterogeneously nucleate at grain boundaries and all grain boundaries are not equally susceptible to void nucleation. However, for materials of engineering significance, especially those with second phase particles, it is less clear if the type of bi-metal interface between the two phases will affect void nucleation and growth. To approach this problem in a systematic manner two bi-metal interfaces between Cu and Pb have been investigated: {111} and {100}. Qualitative and quantitative analysis of the collected data from molecular dynamics shock and spall simulations suggests that Pb becomes disordered during shock compression and is the preferred location for void nucleation under tension. Despite the interfaces being aligned with the spall plane (by design), they are not the preferred location... read less E. Webb and B. Shi, “Early stage spreading: Mechanisms of rapid contact line advance,” Current Opinion in Colloid and Interface Science. 2014. link Times cited: 7 V. Timoshenko, V. Bochenkov, V. Traskine, and P. Protsenko, “Anisotropy of Wetting and Spreading in Binary Cu-Pb Metallic System: Experimental Facts and MD Modeling,” Journal of Materials Engineering and Performance. 2012. link Times cited: 16 A. A. Potter and J. Hoyt, “A molecular dynamics simulation study of the crystal–melt interfacial free energy and its anisotropy in the Cu–Ag–Au ternary system,” Journal of Crystal Growth. 2011. link Times cited: 28 J. P. Palafox-Hernandez, B. Laird, and M. Asta, “Atomistic characterization of the Cu–Pb solid–liquid interface,” Acta Materialia. 2011. link Times cited: 57 J. Hoyt, “Linear stability analysis of phase separation in nanoscale systems,” Acta Materialia. 2009. link Times cited: 2 J. Hoyt, “Molecular dynamics study of equilibrium concentration profiles and the gradient energy coefficient in Cu-Pb nanodroplets,” Physical Review B. 2007. link Times cited: 16 E. Webb, J. Hoyt, and G. Grest, “High temperature wetting: Insights from atomistic simulations,” Current Opinion in Solid State & Materials Science. 2005. link Times cited: 16 E. Webb, G. Grest, D. Heine, and J. Hoyt, “Dissolutive wetting of Ag on Cu: A molecular dynamics simulation study,” Acta Materialia. 2004. link Times cited: 60 Y.-M. Kim and B.-J. Lee, “A modified embedded-atom method interatomic potential for the Cu–Zr system,” Journal of Materials Research. 2004. link Times cited: 65 Y. Lei et al., “An Embedded-Atom Method Potential for studying the properties of Fe-Pb solid-liquid interface,” Journal of Nuclear Materials. 2022. link Times cited: 1 Z. Trautt, F. Tavazza, and C. Becker, “Facilitating the selection and creation of accurate interatomic potentials with robust tools and characterization,” Modelling and Simulation in Materials Science and Engineering. 2015. link Times cited: 14 Abstract: The Materials Genome Initiative seeks to significantly decre… read more Abstract: The Materials Genome Initiative seeks to significantly decrease the cost and time of development and integration of new materials. Within the domain of atomistic simulations, several roadblocks stand in the way of reaching this goal. While the NIST Interatomic Potentials Repository hosts numerous interatomic potentials (force fields), researchers cannot immediately determine the best choice(s) for their use case. Researchers developing new potentials, specifically those in restricted environments, lack a comprehensive portfolio of efficient tools capable of calculating and archiving the properties of their potentials. This paper elucidates one solution to these problems, which uses Python-based scripts that are suitable for rapid property evaluation and human knowledge transfer. Calculation results are visible on the repository website, which reduces the time required to select an interatomic potential for a specific use case. Furthermore, property evaluation scripts are being integrated with modern platforms to improve discoverability and access of materials property data. To demonstrate these scripts and features, we will discuss the automation of stacking fault energy calculations and their application to additional elements. While the calculation methodology was developed previously, we are using it here as a case study in simulation automation and property calculations. We demonstrate how the use of Python scripts allows for rapid calculation in a more easily managed way where the calculations can be modified, and the results presented in user-friendly and concise ways. Additionally, the methods can be incorporated into other efforts, such as openKIM. read less S. Cajahuaringa and A. Antonelli, “Non-equilibrium free-energy calculation of phase-boundaries using LAMMPS,” Computational Materials Science. 2021. link Times cited: 2 A. Akbarzadeh, Y. Cui, and Z. Chen, “Thermal wave: from nonlocal continuum to molecular dynamics,” RSC Advances. 2017. link Times cited: 24 Abstract: It is well known that the continuum model of Fourier's … read more Abstract: It is well known that the continuum model of Fourier's law of heat conduction violates the relativity theory, admits an instantaneous thermal response, and assumes a quasi-equilibrium thermodynamic condition. Transient heat transport, however, is a non-equilibrium phenomenon with a finite thermal wave speed for applications involving very low temperatures, extremely high temperature gradients, and ballistic heat transfers. Hyperbolic and phase-lag heat conduction models have enabled detection of the finite thermal wave speed in heat transport. To accommodate effects of thermomass and size-dependency of thermophysical properties on nano/microscale heat transport and to remove the theoretical singularity of temperature gradients across the thermal wavefront, a nonlocal, fractional-order, three-phase-lag heat conduction is introduced. The model is capable of simulating heat conduction phenomena in multiple spatio-temporal scales. To confirm the existence of thermal waves in nano/microscale heat transport, a molecular dynamics simulation is implemented for the heat transfer within a nanoscale copper slab. Correlating thermal responses in continuum and atomistic scales sheds light on the effect of length scale, fractional order, and phase-lags in multiscale heat transport. The multiscale simulation is of practical importance for microelectromechanical system design, photothermal techniques, and ultrafast laser-assisted processing of advanced materials. read less H.-shan Li, S. Zhou, and Y. Cao, “Calculation of Liquid–Solid Interfacial Free Energy in Pb–Cu Binary Immiscible System,” Zeitschrift für Naturforschung A. 2016. link Times cited: 3 Abstract: Based on the solid–liquid interfacial free energy theory of … read more Abstract: Based on the solid–liquid interfacial free energy theory of the complex Warren binary & pseudo-binary system and through the simplification of it by taking Pb–Cu binary system as an example, the physical model for it in binary immiscible system can be obtained. Next, its thermodynamic formula is derived to obtain a theoretical formula that only contains two parameters, and comparisons are made with regard to γSL calculated values and experimental values of MPE (multiphase equilibrium method) under several kinds of temperatures. As manifested in the outcomes, the improved physical model and theoretical formula will become not only easy to understand but also simple for calculation (the calculated value of γSL depends on two parameters, i.e. temperature and percentage composition of Cu atom). It can be treated as the foundation of application for the γSL calculation of liquid–solid interfacial free energy in other immiscible systems. read less P. Saidi, T. Frolov, J. Hoyt, and M. Asta, “An angular embedded atom method interatomic potential for the aluminum–silicon system,” Modelling and Simulation in Materials Science and Engineering. 2014. link Times cited: 19 Abstract: A modified version of the Stillinger–Weber (SW) interatomic … read more Abstract: A modified version of the Stillinger–Weber (SW) interatomic potential for pure Si has been developed. In contrast to the original SW form, the modified version allows one to grow diamond cubic crystal structures from the melt at high temperatures. Now, the modified SW potential has been combined with an embedded atom (EAM) description of pure Al developed by Mendelev et al to formulate an Al–Si binary potential of the angular EAM type. The Al–Si potential reproduces quite well the experimental enthalpy of mixing in the liquid. It also predicts an Al–Si phase diagram with a eutectic concentration for the liquid that agrees with experimental values within 4 at% and a eutectic temperature that differs from experimental values by just 13 K. read less D. Belashchenko, “Computer simulation of liquid metals,” Physics—Uspekhi. 2013. link Times cited: 84 Abstract: Methods for and the results of the computer simulation of li… read more Abstract: Methods for and the results of the computer simulation of liquid metals are reviewed. Two basic methods, classical molecular dynamics with known interparticle potentials and the ab initio method, are considered. Most attention is given to the simulated results obtained using the embedded atom model (EAM). The thermodynamic, structural, and diffusion properties of liquid metal models under normal and extreme (shock) pressure conditions are considered. Liquid-metal simulated results for the Groups I–IV elements, a number of transition metals, and some binary systems (Fe–C, Fe–S) are examined. Possibilities for the simulation to account for the thermal contribution of delocalized electrons to energy and pressure are considered. Solidification features of supercooled metals are also discussed. read less D. Belashchenko, “Computer simulation of copper and silver under shock compression conditions,” Inorganic Materials. 2013. link Times cited: 2 D. Belashchenko, “Embedded atom method potentials for liquid copper and silver,” Inorganic Materials. 2012. link Times cited: 7 M. Mendelev, M. Asta, M. J. Rahman, and J. Hoyt, “Development of interatomic potentials appropriate for simulation of solid–liquid interface properties in Al–Mg alloys,” Philosophical Magazine. 2009. link Times cited: 126 Abstract: Different approaches are analyzed for construction of semi-e… read more Abstract: Different approaches are analyzed for construction of semi-empirical potentials for binary alloys, focusing specifically on the capability of these potentials to describe solid–liquid phase equilibria, as a pre-requisite to studies of solidification phenomena. Fitting ab initio compound data does not ensure correct reproduction of the dilute solid-solution formation energy, and explicit inclusion of this quantity in the potential development procedure does not guarantee that the potential will predict the correct solid–liquid phase diagram. Therefore, we conclude that fitting only to solid phase properties, as is done in most potential development procedures, generally is not sufficient to develop a semi-empirical potential suitable for the simulation of solidification. A method is proposed for the incorporation of data for liquid solution energies in the potential development procedure, and a new semi-empirical potential developed suitable for simulations of dilute alloys of Mg in Al. The potential correctly reproduces both zero-temperature solid properties and solidus and liquid lines on the Al-rich part of the Al–Mg phase diagram. read less D. Belashchenko, “Application of the embedded atom model to liquid metals: Liquid sodium,” High Temperature. 2009. link Times cited: 33 P. L. Williams, Y. Mishin, and J. C. Hamilton, “An embedded-atom potential for the Cu–Ag system,” Modelling and Simulation in Materials Science and Engineering. 2006. link Times cited: 430 Abstract: A new embedded-atom method (EAM) potential has been construc… read more Abstract: A new embedded-atom method (EAM) potential has been constructed for Ag by fitting to experimental and first-principles data. The potential accurately reproduces the lattice parameter, cohesive energy, elastic constants, phonon frequencies, thermal expansion, lattice-defect energies, as well as energies of alternate structures of Ag. Combining this potential with an existing EAM potential for Cu, a binary potential set for the Cu–Ag system has been constructed by fitting the cross-interaction function to first-principles energies of imaginary Cu–Ag compounds. Although properties used in the fit refer to the 0 K temperature (except for thermal expansion factors of pure Cu and Ag) and do not include liquid configurations, the potentials demonstrate good transferability to high-temperature properties. In particular, the entire Cu–Ag phase diagram calculated with the new potentials in conjunction with Monte Carlo simulations is in satisfactory agreement with experiment. This agreement suggests that EAM potentials accurately fit to 0 K properties can be capable of correctly predicting simple phase diagrams. Possible applications of the new potential set are outlined. read less D. Belashchenko, “Embedded atom model for liquid metals: Liquid iron,” Russian Journal of Physical Chemistry. 2006. link Times cited: 21 C. Becker, M. Asta, J. Hoyt, and S. Foiles, “Equilibrium adsorption at crystal-melt interfaces in Lennard-Jones alloys.,” The Journal of chemical physics. 2006. link Times cited: 29 Abstract: Although the properties of crystal-melt interfaces have been… read more Abstract: Although the properties of crystal-melt interfaces have been extensively studied in pure materials, effects of alloying on the interfacial free energy remain relatively poorly understood. In this work we make use of Monte Carlo computer simulations for model binary Lennard-Jones alloys to explore the effects which variations in atomic-size mismatch and the chemical contributions to mixing energies have upon density and composition profiles, as well as the resulting magnitudes of equilibrium adsorption coefficients in concentrated alloys. We study four different model systems covering a range of chemical and size mismatch, finding relatively small adsorption values which are nevertheless statistically different from zero. read less D. Belashchenko and O. I. Ostrovskii, “The embedded atom model for liquid metals: Liquid gallium and bismuth,” Russian Journal of Physical Chemistry. 2006. link Times cited: 23 E. Webb, J. Hoyt, G. Grest, and D. Heine, “Atomistic simulations of reactive wetting in metallic systems,” Journal of Materials Science. 2004. link Times cited: 24
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_119135752160_005
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.	EAM_Dynamo_HoytGarvinWebb_2003_PbCu__MO_119135752160_005
DOI	10.25950/f6e7d52c https://doi.org/10.25950/f6e7d52c https://commons.datacite.org/doi.org/10.25950/f6e7d52c
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 EAM_Dynamo__MD_120291908751_005
Driver	EAM_Dynamo__MD_120291908751_005
KIM API Version	2.0
Potential Type	eam

Previous Version	EAM_Dynamo_HoytGarvinWebb_2003_PbCu__MO_119135752160_004

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
B The letter grade B was assigned because the normalized error in the computation was 2.38922e-08 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: Pb

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: Pb

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: Pb

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: Pb

Species: Cu

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: Pb

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: Pb

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

Species: Pb

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: Cu

Species: Pb

Cubic Crystal Basic Properties Table

Species: Cu

Species: Pb

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	3280
Cohesive energy versus lattice constant curve for bcc Pb v004	view	2576
Cohesive energy versus lattice constant curve for diamond Cu v004	view	2506
Cohesive energy versus lattice constant curve for diamond Pb v004	view	3193
Cohesive energy versus lattice constant curve for fcc Cu v004	view	2566
Cohesive energy versus lattice constant curve for fcc Pb v004	view	2636
Cohesive energy versus lattice constant curve for sc Cu v004	view	3578
Cohesive energy versus lattice constant curve for sc Pb v004	view	2650

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	1951
Elastic constants for bcc Pb at zero temperature v006	view	5854
Elastic constants for diamond Pb at zero temperature v001	view	6910
Elastic constants for fcc Cu at zero temperature v006	view	1791
Elastic constants for fcc Pb at zero temperature v006	view	1759
Elastic constants for sc Cu at zero temperature v006	view	1791
Elastic constants for sc Pb at zero temperature v006	view	1663

ElasticConstantsHexagonal__TD_612503193866_004

Elastic constants for hexagonal crystals at zero temperature v004

Creators: Junhao Li
Contributor: jl2922
Publication Year: 2019
DOI: https://doi.org/10.25950/d794c746

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 v004		view	2101
Elastic constants for hcp Pb at zero temperature v004		view	1496

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	61252
Equilibrium crystal structure and energy for Cu in AFLOW crystal prototype A_cI2_229_a v001		view	57277

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 Pb in AFLOW crystal prototype A_cF4_225_a v002	view	57722
Equilibrium crystal structure and energy for Pb in AFLOW crystal prototype A_cI2_229_a v002	view	84075
Equilibrium crystal structure and energy for Pb in AFLOW crystal prototype A_hP2_194_c v002	view	53408

GrainBoundaryCubicCrystalSymmetricTiltRelaxedEnergyVsAngle__TD_410381120771_002

Relaxed energy as a function of tilt angle for a symmetric tilt grain boundary within a cubic crystal v002

Creators: Brandon Runnels
Contributor: brunnels
Publication Year: 2019
DOI: https://doi.org/10.25950/4723cee7

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 v000	view	2717502
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Cu v000	view	9282954
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Cu v000	view	4927990
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Cu v000	view	19392142

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 Pb v000	view	3740437
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Pb v000	view	11799378
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Pb v000	view	5725098
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Pb v000	view	23437749

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	1631
Equilibrium zero-temperature lattice constant for bcc Pb v007	view	1951
Equilibrium zero-temperature lattice constant for diamond Cu v007	view	2687
Equilibrium zero-temperature lattice constant for diamond Pb v007	view	2975
Equilibrium zero-temperature lattice constant for fcc Cu v007	view	3263
Equilibrium zero-temperature lattice constant for fcc Pb v007	view	2271
Equilibrium zero-temperature lattice constant for sc Cu v007	view	2047
Equilibrium zero-temperature lattice constant for sc Pb v007	view	2527

LatticeConstantHexagonalEnergy__TD_942334626465_005

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

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

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Equilibrium lattice constants for hcp Cu v005		view	25119
Equilibrium lattice constants for hcp Pb v005		view	16236

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	5283687

LinearThermalExpansionCoeffCubic__TD_522633393614_002

Linear thermal expansion coefficient of cubic crystal structures v002

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

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Linear thermal expansion coefficient of fcc Pb at 293.15 K under a pressure of 0 MPa v002		view	337697

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	49647
Phonon dispersion relations for fcc Pb v004		view	51566

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	7607816
Stacking and twinning fault energies for fcc Pb v002		view	3760819

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	29206
Broken-bond fit of high-symmetry surface energies in fcc Pb v004		view	21177

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	360151
Monovacancy formation energy and relaxation volume for fcc Pb		view	204444

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	2340396
Vacancy formation and migration energy for fcc Pb		view	2119608

Errors

DislocationCoreEnergyCubic__TD_452950666597_002

Test	Error Categories	Link to Error page
Dislocation core energy for fcc Pb computed at zero temperature for a set of dislocation core cutoff radii with burgers vector [0.5, 0.5, 0] along line direction [1, -1, 2] v000	other	view

ElasticConstantsCubic__TD_011862047401_006

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

GrainBoundaryCubicCrystalSymmetricTiltRelaxedEnergyVsAngle__TD_410381120771_003

Test	Error Categories	Link to Error page
Relaxed energy as a function of tilt angle for a 100 symmetric tilt grain boundary in fcc Cu v001	other	view
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Cu v001	other	view
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Cu v001	other	view
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Cu v001	other	view

LatticeConstantCubicEnergy__TD_475411767977_006

Test	Error Categories	Link to Error page
Equilibrium zero-temperature lattice constant for diamond Cu	other	view

Files

CMakeLists.txt
LICENSE.CDDL
kimprovenance.edn
kimspec.edn
pbcu.setfl

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EAM_Dynamo_HoytGarvinWebb_2003_PbCu__MO_119135752160_005.txz	Tar+XZ	Linux and OS X archive
EAM_Dynamo_HoytGarvinWebb_2003_PbCu__MO_119135752160_005.zip	Zip	Windows archive

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This Model requires a Model Driver. Archives for the Model Driver EAM_Dynamo__MD_120291908751_005 appear below.

EAM_Dynamo__MD_120291908751_005.txz	Tar+XZ	Linux and OS X archive
EAM_Dynamo__MD_120291908751_005.zip	Zip	Windows archive

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EAM_Dynamo_HoytGarvinWebb_2003_PbCu__MO_119135752160_005

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

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