Finnis-Sinclair potential (LAMMPS cubic hermite tabulation) for Cu with improved stacking fault energy developed by Mendelv and King (2013) v005

Alexander King; Mikhail I. Mendelev

doi:10.25950/34748b8d

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EAM_Dynamo_MendelevKing_2013_Cu__MO_748636486270_005

Interatomic potential for Copper (Cu).
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Title A single sentence description.	Finnis-Sinclair potential (LAMMPS cubic hermite tabulation) for Cu with improved stacking fault energy developed by Mendelv and King (2013) 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.	The same as the Cu potential in [M.I. Mendelev, M.J. Kramer, C.A. Becker and M. Asta, Phil. Mag. 88, 1723 - 1750 (2008).] except of improvement of stacking fault energy.
Species The supported atomic species.	Cu
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/Cu.html

Contributor	Mikhail I. Mendelev
Maintainer	Mikhail I. Mendelev
Developer	Alexander King Mikhail I. Mendelev
Published on KIM	2018
How to Cite	This Model originally published in [1] is archived in OpenKIM [2-5]. [1] Mendelev MI, King AH. The interactions of self-interstitials with twin boundaries. Philosophical Magazine. 2013;93(10-12):1268–78. doi:10.1080/14786435.2012.747012 — (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] King A, Mendelev MI. Finnis-Sinclair potential (LAMMPS cubic hermite tabulation) for Cu with improved stacking fault energy developed by Mendelv and King (2013) v005. OpenKIM; 2018. doi:10.25950/34748b8d [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 . N. Dubinin and R. Ryltsev, “Effective Pair Interactions and Structure in Liquid Noble Metals within Wills-Harrison and Bretonnet-Silbert Models,” Metals. 2021. link Times cited: 4 Abstract: Recently, for calculating the effective pair interactions in… read more Abstract: Recently, for calculating the effective pair interactions in liquid transition metals, we have developed an approach which includes the Wills-Harrison and Bretonnet-Silbert models as limit cases. Here, we apply this approach to noble liquid metals. The dependencies of pair potentials and corresponding MD-simulated pair correlation functions in pure liquid Cu, Ag and Au on the portion of the non-diagonal (with respect to the magnet quantum number) d-d-electron couplings in the metal under consideration are studied. The model provides a good agreement with experimental and ab initio data for pair correlation functions, structure factors and velocity autocorrelation functions. read less K. Zolnikov, D. Kryzhevich, and A. Korchuganov, “Regularities of Structural Rearrangements in Single- and Bicrystals Near the Contact Zone,” Springer Tracts in Mechanical Engineering. 2020. link Times cited: 0 V. Kulagin, A. A. Itskovich, A. Rodin, and B. Bokshteĭn, “Effect of Grain-Boundary Segregation on the Diffusion of Atoms in Grain Boundaries in Copper-Based Systems,” Russian Metallurgy (Metally). 2020. link Times cited: 1 K. V. Reddy, C. Deng, and S. Pal, “Intensification of shock damage through heterogeneous phase transition and dislocation loop formation due to presence of pre-existing line defects in single crystal Cu,” Journal of Applied Physics. 2019. link Times cited: 4 Abstract: In general, shock wave deformation studies of perfect single… read more Abstract: In general, shock wave deformation studies of perfect single crystals may cause disagreement with the experimental findings as the complete elimination of all defects in the metallic system is not possible in reality. Here, we have studied the influence of edge and screw dislocations on the intensification of damage produced during the propagation of shock at various velocities. Various analyses have been performed such as common neighbor analysis, atomic strain analysis, stress analysis, and kinetic energy mapping to investigate the underlying plastic deformation mechanisms. Results have revealed that the presence of edge dislocations has caused intensified damage through localized amorphization and phase transition. In comparison with the perfect crystal, the presence of pre-existing edge dislocations has incurred an additional damage of ∼17% to the specimen region. On the other hand, the presence of screw dislocations in the specimen causes damage through shear bands and dislocation loop formation, which is found to constitute greater than 80% of the specimen region. read less S. Hayakawa, T. Okita, M. Itakura, T. Kawabata, and K. Suzuki, “Atomistic simulations for the effects of stacking fault energy on defect formations by displacement cascades in FCC metals under Poisson’s deformation,” Journal of Materials Science. 2019. link Times cited: 10 D. Nakanishi, T. Kawabata, K. Doihara, T. Ōkita, M. Itakura, and K. Suzuki, “Effects of stacking fault energies on formation of irradiation-induced defects at various temperatures in face-centred cubic metals,” Philosophical Magazine. 2018. link Times cited: 9 Abstract: ABSTRACT By using the six sets of interatomic potentials for… read more Abstract: ABSTRACT By using the six sets of interatomic potentials for face-centred cubic metals that differ in the stacking fault energy (SFE) while most of the other material parameters are kept almost identical, we conducted molecular dynamics simulations to evaluate the effects of SFE on the defect formation process through collision cascades. The simulations were performed at 100, 300 and 600 K, with a primary knock-on atom energy of 50 keV. The number of residual defects is not dependent on the SFE at all the temperatures. For clusters of self-interstitial atoms (SIAs), their clustering behaviour does not depend on the SFE, either. However, the ratio of glissile SIA clusters tends to decrease with increasing SFE. This is because perfect loops, the edges of which split into two partial dislocations with stacking fault structures between them in most cases, prefer to form at lower SFEs. The enhanced formation of glissile SIA clusters at lower SFEs can also be observed even at increased temperature. Because most large vacancy clusters have stacking fault structures, they preferentially form at lower SFE; however, it is observed only at the lowest temperature, where the mean size increases with decreasing SFE. At higher temperatures, because of their extremely low number density, the vacancy clustering behaviour does not depend on the SFEs. read less K.-Q. Li, Z. Zhang, L.-L. Li, P. Zhang, J.-B. Yang, and Z.-F. Zhang, “Effective Stacking Fault Energy in Face-Centered Cubic Metals,” Acta Metallurgica Sinica (English Letters). 2018. link Times cited: 4 Z. Pan and T. Rupert, “Damage nucleation from repeated dislocation absorption at a grain boundary,” arXiv: Materials Science. 2014. link Times cited: 43 S. M. Handrigan and S. Nakhla, “Generation of viable nanocrystalline structures using the melt-cool method: the influence of force field selection,” Philosophical Magazine. 2023. link Times cited: 0 W. Ji, W. Jian, Y. Su, S. Xu, and I. Beyerlein, “Role of stacking fault energy in confined layer slip in nanolaminated Cu,” Journal of Materials Science. 2023. link Times cited: 0 L. Safina, E. A. Rozhnova, R. Murzaev, and J. Baimova, “Effect of Interatomic Potential on Simulation of Fracture Behavior of Cu/Graphene Composite: A Molecular Dynamics Study,” Applied Sciences. 2023. link Times cited: 4 Abstract: Interatomic interaction potentials are compared using a mole… read more Abstract: Interatomic interaction potentials are compared using a molecular dynamics modeling method to choose the simplest, but most effective, model to describe the interaction of copper nanoparticles and graphene flakes. Three potentials are considered: (1) the bond-order potential; (2) a hybrid embedded-atom-method and Morse potential; and (3) the Morse potential. The interaction is investigated for crumpled graphene filled with copper nanoparticles to determine the possibility of obtaining a composite and the mechanical properties of this material. It is observed that not all potentials can be applied to describe the graphene–copper interaction in such a system. The bond-order potential potential takes into account various characteristics of the bond (for example, the angle of rotation and bond lengths); its application increases the simulation time and results in a strong interconnection between a metal nanoparticle and a graphene flake. The hybrid embedded-atom-method/Morse potential and the Morse potential show different results and lower bonding between graphene and copper. All the potentials enable a composite structure to be obtained; however, the resulting mechanical properties, such as strength, are different. read less X. Pan et al., “Microstructure and residual stress modulation of 7075 aluminum alloy for improving fatigue performance by laser shock peening,” International Journal of Machine Tools and Manufacture. 2023. link Times cited: 22 A. B. Sivak, D. N. Demidov, and P. A. Sivak, “Diffusion Characteristics of Self-Point Defects in Copper: Molecular Dynamic Study,” Physics of Atomic Nuclei. 2022. link Times cited: 1 S. Pal, K. V. Reddy, and C. Deng, “Improving thermal stability and Hall-Petch breakdown relationship in nanocrystalline Cu: A molecular dynamics simulation study,” Materials Letters. 2022. link Times cited: 6 P. Wu and Y. Yang, “Melting characteristics and strain-based mechanical characterization of single metal nanoparticles,” Journal of Nanoparticle Research. 2022. link Times cited: 0 Y. Lin, T.-H. Yang, T.-M. Chen, and D. Pen, “Using atomic response time to explore the effect of strain rate on yielding behaviors of tensile Cu nanowire with the molecular dynamic method,” The International Journal of Advanced Manufacturing Technology. 2022. link Times cited: 1 A. Rajput and S. Paul, “Effect of void in deformation and damage mechanism of single crystal copper: a molecular dynamics study,” Modelling and Simulation in Materials Science and Engineering. 2021. link Times cited: 2 Abstract: The current study investigates the deformation and damage me… read more Abstract: The current study investigates the deformation and damage mechanism of single crystal copper in the presence of a void located at the copper cell center. Tensile and compressive deformations are conducted in two loading modes, uniaxial and triaxial. Alteration in mechanical properties is observed due to the presence of void in different deformation modes. In uniaxial deformation, a smooth gradient in stress and strain distribution are evident before dislocation nucleation, i.e. in the elastic domain. However, inhomogeneity in stress and strain distribution are noted during the plastic deformation, i.e. after dislocations emission. Stress concentration remains high near the void surface ahead of the dislocation emission. Stress and strain concentration play a substantials role in nucleating defects (i.e. dislocation and stacking fault) from the void surface. Moreover, the void growth in tension and void shrinking in compression are found due to the emission/shrink of dislocations from the void surface. Consequently, an effective rate of dislocation emission enhances the growth rate of the void, as it happens in triaxial tensile deformation. read less D. Roy, S. Pal, C. Tiwary, A. Gupta, P. N. Babu, and R. Mitra, “Stable nanocrystalline structure attainment and strength enhancement of Cu base alloy using bi-modal distributed tungsten dispersoids,” Philosophical Magazine. 2021. link Times cited: 4 Abstract: In this study, an experimental and atomic-scale simulationba… read more Abstract: In this study, an experimental and atomic-scale simulationbased investigation has been performed to investigate the possible stability of the nano-crystalline structure and thereby considerable strength at a higher temperature in the case of synthesised Cu alloy along with logical understanding. Dispersions of high melting BCC metal (1 at % W) in nanostructured Cu is achieved using conveniently scalable cryomilling followed by hot pressing (at 550 °C). The thermal stability (till 800 °C) of grain size in synthesised nano-crystalline Cu alloy has been examined through X-ray diffraction (XRD) and Transmission Electron Microscopy (TEM). The nano-sized W particles dispersed at the Cu matrix grain boundaries, restricting grain growth by Zener pinning even after annealing was carried out at 800 °C. The hot-pressed pellets of nanocrystalline Cu99W1 alloy with a nearly uniform distribution of W particles have exhibited higher hardness than pure Cu and increased in strength and strain to failure up to 10% and 46%, respectively. The improvement in mechanical properties is further rationalised by the Molecular Dynamics (MD) based simulation findings. ARTICLE HISTORY Received 6 December 2020 Accepted 26 September 2021 read less A. Rajput and S. Paul, “Bauschinger Effect Analysis in Polycrystalline Copper: an Atomistic Simulation,” Transactions of the Indian National Academy of Engineering. 2021. link Times cited: 0 A. Rajput and S. Paul, “Bauschinger Effect Analysis in Polycrystalline Copper: an Atomistic Simulation,” Transactions of the Indian National Academy of Engineering. 2021. link Times cited: 0 J. Yan et al., “Effects of pressure on the generalized stacking fault energy and twinning propensity of face-centered cubic metals,” Journal of Alloys and Compounds. 2021. link Times cited: 17 Y. Yu, “Deposited Mono-component Cu Metallic Glass: A Molecular Dynamics Study,” Materials today communications. 2021. link Times cited: 4 A. Rajput and S. Paul, “Deformation inhomogeneity at the crack tip of polycrystalline copper,” Materials today communications. 2020. link Times cited: 6 K. V. Reddy and S. Pal, “Shock velocity-dependent elastic-plastic collapse of pre-existing stacking fault tetrahedron in single crystal Cu,” Computational Materials Science. 2020. link Times cited: 11 A. Rajput and S. Paul, “Effect of different tensile loading modes on deformation behavior of nanocrystalline copper: Atomistic simulations.” 2019. link Times cited: 9 A. Korchuganov, K. Zolnikov, and D. S. Kryzhevich, “Atomic mechanisms of stacking fault propagation in copper crystallite,” Materials Letters. 2019. link Times cited: 26 B. Bokstein, A. Rodin, A. Itckovich, and L. Klinger, “Segregation and Phase Transitions in Grain Boundaries,” Diffusion Foundations. 2019. link Times cited: 1 Abstract: The paper is devoted to some properties of grain boundaries:… read more Abstract: The paper is devoted to some properties of grain boundaries: Segregation and concentration phase transitions – two important consequences of atomic interactions in grain boundaries. Except of a short description the Gibbs method of surface excesses and grain boundary segregation isotherms with the limited number of segregation sites in grain boundary, the paper concentrates on the effects of complexes formation, including thermodynamic and computer modeling, and concentration phase transition in the grain boundaries in systems with restricted solubility and intermediate compounds. read less M. Dupraz, S. Rao, and H. V. Swygenhoven, “Large Scale 3-Dimensional Atomistic Simulations of Screw Dislocations Interacting with Coherent Twin Boundaries in Al, Cu and Ni Under Uniaxial and Multiaxial Loading Conditions,” MatSciRN: Process & Device Modeling (Topic). 2019. link Times cited: 17 A. Korchuganov et al., “Nucleation of dislocations and twins in fcc nanocrystals: Dynamics of structural transformations,” Journal of Materials Science & Technology. 2019. link Times cited: 46 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 A. Itckovich, M. Mendelev, A. Rodin, and B. Bokstein, “Effect of Atomic Complexes Formation in Grain Boundaries on Grain Boundary Diffusion,” Defect and Diffusion Forum. 2018. link Times cited: 7 Abstract: The peculiarities of grain boundary diffusion in Cu connecte… read more Abstract: The peculiarities of grain boundary diffusion in Cu connected with the effect of atomic pairs formation in grain boundaries (GB) were studied using the molecular dynamics (MD) simulation. In present study Cu GB selfdiffusion was simulated with the use of semi-empirical potential. Besides, the ‘heterodiffusion’ simulation was performed with the artificially addеd energy of interaction (E) between identical atoms in arbitrary chosen pairs. To obtain reliable data on the mean square displacements (MSD) the simulation cell, consisted about three hundreds thousands atoms and two symmetrical GBs Σ5 (001)(012), was used. 70 pairs of identical Cu atoms in GBs, bonded into pairs, were chosen as initial state. Energy of interaction was varied between 0 and - 0.5eV/atomThe results obtained for selfdiffusion are in a good agreement with experimental results and other results of computer simulation. Two main effects for heterodiffusion are under discussion. The first is atomic exchange between GB zone and adjacent lattice zone, where the mobility of the atoms decreases significantly. As a result, the MSD decrease. Another effect is connected with attraction between the “marked” atoms, which leads to formation of relatively stable complexes and the MSD also decreases. The results obtained involve also dependence the number of the stable pairs on time and temperature and show the possibility of pairs to condense into ternary, quarterly and more numerous complexes. read less Y. Yang, T. Okita, M. Itakura, T. Kawabata, and K. Suzuki, “Influence of stacking fault energies on the size distribution and character of defect clusters formed by collision cascades in face-centered cubic metals,” Nuclear materials and energy. 2016. link Times cited: 11 K. Li, Z. Zhang, L. Li, P. Zhang, J. Yang, and Z. F. Zhang, “The dissociation behavior of dislocation arrays in face centered cubic metals,” Computational Materials Science. 2016. link Times cited: 2 X. Xiao, D. Song, H. Chu, J. Xue, and H. Duan, “Mechanical behaviors of irradiated FCC polycrystals with nanotwins,” International Journal of Plasticity. 2015. link Times cited: 25 L. Li et al., “Strain localization and fatigue cracking behaviors of Cu bicrystal with an inclined twin boundary,” Acta Materialia. 2014. link Times cited: 34 N. Gao, D. Perez, G. Lu, and Z. G. Wang, “Molecular dynamics study of the interaction between nanoscale interstitial dislocation loops and grain boundaries in BCC iron,” Journal of Nuclear Materials. 2018. link Times cited: 19 D. Liu, G. Wang, J. Yu, and Y. Rong, “Molecular dynamics simulation on formation mechanism of grain boundary steps in micro-cutting of polycrystalline copper,” Computational Materials Science. 2017. link Times cited: 32 T. Olugbade and J. Lu, “Literature review on the mechanical properties of materials after surface mechanical attrition treatment (SMAT).” 2020. link Times cited: 76 A. Hernandez, A. Balasubramanian, F. Yuan, S. Mason, and T. Mueller, “Fast, accurate, and transferable many-body interatomic potentials by symbolic regression,” npj Computational Materials. 2019. link Times cited: 51 J. S. Amelang, G. Venturini, and D. Kochmann, “Summation rules for a fully nonlocal energy-based quasicontinuum method,” Journal of The Mechanics and Physics of Solids. 2015. link Times cited: 53 I. Shepelev and E. Korznikova, “Dependence of the supersonic propagation of 2-crowdions on the stacking fault energy in FCC metals,” MATHEMATICS EDUCATION AND LEARNING. 2022. link Times cited: 0 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 J.-J. Tang et al., “Interactions between twin boundary and point defects in magnesium at low temperature,” Journal of Materials Research. 2021. link Times cited: 6 Abstract: The interactions between a 101¯2\documentclass[12pt]{minimal… read more Abstract: The interactions between a 101¯2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} $\begin{document}$$\left\{ {10\overline{1}2} \right\}$$\end{document}$ twin boundary and point defects including vacancies and self-interstitial atoms in magnesium were investigated by molecular dynamics simulations at low temperature. The simulation results suggest that vacancies have a softening effect on TB migration, while interstitials lead to a hardening effect. During the interactions, vacancies were observed to be not absorbed by the TB. In contrast, interstitials are able to be absorbed by TB and migrate on TB. Finally, those absorbed interstitials aggregate and form interstitial clusters, which are released from the TB. The migration energies of vacancy and interstitial are calculated through nudged elastic band method. The aforementioned observations can be well explained by the migration energies, where the energies of a vacancy in a bulk crystal and on TB are both two order in magnitude higher than those of an interstitial. The current work provides new insights into the irradiation effects in magnesium. read less W. Jiang, Y. Zhang, L. Zhang, and H. Wang, “Accurate Deep Potential model for the Al–Cu–Mg alloy in the full concentration space,” arXiv: Materials Science. 2020. link Times cited: 24 Abstract: Combining first-principles accuracy and empirical-potential … read more Abstract: Combining first-principles accuracy and empirical-potential efficiency for the description of the potential energy surface (PES) is the philosopher's stone for unraveling the nature of matter via atomistic simulation. This has been particularly challenging for multi-component alloy systems due to the complex and non-linear nature of the associated PES. In this work, we develop an accurate PES model for the Al-Cu-Mg system by employing Deep Potential (DP), a neural network based representation of the PES, and DP Generator (DP-GEN), a concurrent-learning scheme that generates a compact set of ab initio data for training. The resulting DP model gives predictions consistent with first-principles calculations for various binary and ternary systems on their fundamental energetic and mechanical properties, including formation energy, equilibrium volume, equation of state, interstitial energy, vacancy and surface formation energy, as well as elastic moduli. Extensive benchmark shows that the DP model is ready and will be useful for atomistic modeling of the Al-Cu-Mg system within the full range of concentration. read less G. Lerma, B. Verschueren, B. Gurrutxaga-Lerma, and J. Verschueren, “Generalized Kanzaki force field of extended defects in crystals with applications to the modeling of edge dislocations,” Physical Review Materials. 2019. link Times cited: 4 Abstract: The Kanzaki forces and their associated multipolar moments a… read more Abstract: The Kanzaki forces and their associated multipolar moments are standard ways of representing point defects in an atomistically informed way in the continuum. In this article, the Kanzaki force approach is extended to other crystalline defects. The article shows how the resulting Kanzaki force ﬁelds are to be computed for any general extended defect by ﬁrst computing the relaxed defect’s structure and then deﬁning an afﬁne mapping between the said defect structure and the original perfect lattice. This methodology can be employed to compute the Kanzaki force ﬁeld of any mass-conserving defect, including dislocations, grain and twin boundaries, or cracks. Particular focus is then placed on straight edge dislocation in face-centered cubic (fcc) and body-centered cubic (bcc) pure metals, which are studied along different crystallographic directions. The particular characteristics of these force ﬁelds are discussed, drawing a distinction between the slip Kanzaki force ﬁeld associated with the Volterra disregistry that characterizes the dislocation, and the core Kanzaki force ﬁeld associated with the speciﬁc topology of the dislocation’s core. The resulting force ﬁelds can be employed to create elastic models of the dislocation that, unlike other regularization procedures, offer a geometrically true representation of the core and the elastic ﬁelds in its environs, capturing all three-dimensional effects associated with the core. DOI: 10.1103/PhysRevMaterials read less Q. Lu et al., “Influence of laser shock peening on irradiation defects in austenitic stainless steels,” Journal of Nuclear Materials. 2017. link Times cited: 17 A. Korchuganov, K. Zolnikov, D. S. Kryzhevich, V. Chernov, and S. Psakhie, “MD simulation of plastic deformation nucleation in stressed crystallites under irradiation,” Physics of Atomic Nuclei. 2016. link Times cited: 34 V. Borovikov, M. Mendelev, and A. King, “Effects of stable and unstable stacking fault energy on dislocation nucleation in nano-crystalline metals,” Modelling and Simulation in Materials Science and Engineering. 2016. link Times cited: 50 Abstract: Dislocation nucleation from grain boundaries (GB) can contro… read more Abstract: Dislocation nucleation from grain boundaries (GB) can control plastic deformation in nano-crystalline metals under certain conditions, but little is known about what controls dislocation nucleation, because when data from different materials are compared, the variations of many interacting properties tend to obscure the effects of any single property. In this study, we seek clarification by applying a unique capability of semi-empirical potentials in molecular dynamics simulations: the potentials can be modified such that all significant material properties but one, are kept constant. Using a set of potentials developed to isolate the effects of stacking fault energy, we show that for a given grain boundary, loading orientation and strain rate, the yield stress depends linearly on both the stable and unstable stacking fault energies. The coefficients of proportionality depend on the GB structure and the value of the yield stress is related to the density of the E structural units in the GB. While the impact of the stable stacking fault energy is easy to understand, the unstable stacking fault energy requires more elucidation and we provide a framework for understanding how it affects the nucleation and propagation process. read less N. Admal, J. Marian, and G. Po, “The atomistic representation of first strain-gradient elastic tensors,” Journal of The Mechanics and Physics of Solids. 2016. link Times cited: 36 T. Okita, Y.-Y. Yang, J. Hirabayashi, M. Itakura, and K. Suzuki, “Effects of stacking fault energy on defect formation process in face-centered cubic metals,” Philosophical Magazine. 2016. link Times cited: 14 Abstract: To elucidate the effect of stacking fault energies (SFEs) on… read more Abstract: To elucidate the effect of stacking fault energies (SFEs) on defect formation by the collision cascade process for face-centred cubic metals, we used six sets of interatomic potentials with different SFEs while keeping the other properties almost identical. Molecular dynamic simulations of the collision cascade were carried out using these potentials with primary knock-on atom energies (EPKA) of 10 and 20 keV at 100 K. Neither the number of residual defects nor the size distributions for both self-interstitial atom (SIA) type and vacancy type clusters were affected by the difference in the SFE. In the case of EPKA = 20 keV, the ratio of glissile SIA clusters increased as the SFE decreased, which was not expected by a prediction based on the classical dislocation theory. The trend did not change after annealing at 1100 K for 100 ps. For vacancy clusters, few stacking fault tetrahedrons (SFTs) formed before the annealing. However, lower SFEs tended to increase the SFT fraction after the annealing, where large vacancy clusters formed at considerable densities. The findings of this study can be used to characterise the defect formation process in low SFE metals such as austenitic stainless steels. read less T. Lagrange, K. Arakawa, H. Yasuda, and M. Kumar, “Preferential void formation at crystallographically ordered grain boundaries in nanotwinned copper thin films,” Acta Materialia. 2015. link Times cited: 14 V. Borovikov, M. Mendelev, A. King, and R. LeSar, “Effect of stacking fault energy on mechanism of plastic deformation in nanotwinned FCC metals,” Modelling and Simulation in Materials Science and Engineering. 2015. link Times cited: 53 Abstract: Starting from a semi-empirical potential designed for Cu, we… read more Abstract: Starting from a semi-empirical potential designed for Cu, we have developed a series of potentials that provide essentially constant values of all significant (calculated) materials properties except for the intrinsic stacking fault energy, which varies over a range that encompasses the lowest and highest values observed in nature. These potentials were employed in molecular dynamics (MD) simulations to investigate how stacking fault energy affects the mechanical behavior of nanotwinned face-centered cubic (FCC) materials. The results indicate that properties such as yield strength and microstructural stability do not vary systematically with stacking fault energy, but rather fall into two distinct regimes corresponding to ‘low’ and ‘high’ stacking fault energies. read less L. Sun, X. He, and J. Lu, “Nanotwinned and hierarchical nanotwinned metals: a review of experimental, computational and theoretical efforts,” npj Computational Materials*. 2018. link Times cited: 102
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Short KIM ID The unique KIM identifier code.	MO_748636486270_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_MendelevKing_2013_Cu__MO_748636486270_005
DOI	10.25950/34748b8d https://doi.org/10.25950/34748b8d https://commons.datacite.org/doi.org/10.25950/34748b8d
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
Programming Language(s) The programming languages used in the code and the percentage of the code written in each one. "N/A" means "not applicable" and refers to model parameterizations which only include parameter tables and have no programming language.	N/A

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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 2.80179e-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
P The model is C^1 continuous. This means that the model has continuous energy and continuous first derivative.	vc-dimer-continuity-c1	informational	The energy versus separation relation of a pair of atoms is C1 continuous (i.e. the function and its first derivative are continuous); see full description.	Results	Files
P Model energy and forces are invariant with respect to rigid-body motion (translation and rotation) for all configurations the model was able to compute.	vc-objectivity	informational	Total energy is unchanged and forces transform correctly under rigid-body translation and rotation; see full description.	Results	Files
P Model energy has inversion symmetry for all configurations the model was able to compute.	vc-inversion-symmetry	informational	Total energy is unchanged and forces change sign when inverting a configuration through the origin; see full description.	Results	Files
N/A Unable to perform verification check due to an error.	vc-memory-leak	informational	The model code does not have memory leaks (i.e. it releases all allocated memory at the end); see full description.	Results	Files
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: 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: 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: 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

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

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: Cu

Cubic Crystal Basic Properties Table

Species: Cu

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	10101
Cohesive energy versus lattice constant curve for diamond Cu v004	view	8146
Cohesive energy versus lattice constant curve for fcc Cu v004	view	7778
Cohesive energy versus lattice constant curve for sc Cu v004	view	11443

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 fcc Cu at zero temperature v006	view	6174
Elastic constants for sc Cu at zero temperature v006	view	5086

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	1655

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	69939
Equilibrium crystal structure and energy for Cu in AFLOW crystal prototype A_cI2_229_a v001		view	70749

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	9670481
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Cu v001	view	19733033
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Cu v001	view	10486157
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Cu v001	view	60884595

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	2111
Equilibrium zero-temperature lattice constant for diamond Cu v007	view	3071
Equilibrium zero-temperature lattice constant for fcc Cu v007	view	3903
Equilibrium zero-temperature lattice constant for sc Cu v007	view	2335

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	35306

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	7078110

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	49999

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	7518439

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	29046

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	357648

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	1803997

Errors

ElasticConstantsCubic__TD_011862047401_006

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

No Driver

Verification Check	Error Categories	Link to Error page
MemoryLeak__VC_561022993723_004	other	view

Files

CMakeLists.txt
LICENSE.CDDL
Mendelev_Cu2_2012.eam.fs
kimprovenance.edn
kimspec.edn

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EAM_Dynamo_MendelevKing_2013_Cu__MO_748636486270_005.txz	Tar+XZ	Linux and OS X archive
EAM_Dynamo_MendelevKing_2013_Cu__MO_748636486270_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_MendelevKing_2013_Cu__MO_748636486270_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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