MEAM Potential for the Ni-Cu system developed by Lee and Shim (2004) v002

Byeong-Joo Lee; Jae-Hyeok Shim

doi:10.25950/2a6ef3ab

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MEAM_LAMMPS_LeeShim_2004_NiCu__MO_409065472403_002

Interatomic potential for Copper (Cu), Nickel (Ni).
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Title A single sentence description.	MEAM Potential for the Ni-Cu system developed by Lee and Shim (2004) v002
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 semi-empirical interatomic potential, the MEAM, has been applied to obtain an interatomic potential for the Cu–Ni system, based on the previously developed potentials for pure Cu and Ni.
Species The supported atomic species.	Cu, Ni
Disclaimer A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.	None
Content Origin	http://cmse.postech.ac.kr/home_2nnmeam

Contributor	Hyo-Sun Jang
Maintainer	Hyo-Sun Jang
Developer	Byeong-Joo Lee Jae-Hyeok Shim
Published on KIM	2023
How to Cite	This Model originally published in [1] is archived in OpenKIM [2-5]. [1] Lee B-J, Shim J-H. A modified embedded atom method interatomic potential for the Cu–Ni system. Calphad. 2004;28(2):125–32. doi:10.1016/j.calphad.2004.06.001 — (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] Lee B-J, Shim J-H. MEAM Potential for the Ni-Cu system developed by Lee and Shim (2004) v002. OpenKIM; 2023. doi:10.25950/2a6ef3ab [3] Afshar Y, Hütter S, Rudd RE, Stukowski A, Tipton WW, Trinkle DR, et al. The modified embedded atom method (MEAM) potential v002. OpenKIM; 2023. doi:10.25950/ee5eba52 [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. 63 Citations (43 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 . 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 M. Hennes, J. Buchwald, and S. G. Mayr, “Structural properties of spherical Cu/Ni nanoparticles,” CrystEngComm. 2012. link Times cited: 6 Abstract: While Cu/Ni bulk alloys—partially in the presence of flat su… read more Abstract: While Cu/Ni bulk alloys—partially in the presence of flat surfaces—have been extensively studied, less is known about the properties of Cu/Ni nanoparticles. In the present study we employ a combined Molecular-Dynamics/Metropolis-Monte-Carlo (MD/MMC) simulation approach to analyze equilibrium segregation profiles in Cu/Ni clusters. Special emphasis is put on the relative stability of different segregation patterns and the feasibility of technically meaningful core-shell (CS) nanocrystals. We show that, although the bulk system exhibits a miscibility gap below 630 K, spherical symmetric CS nanoparticles will not form even at low temperatures, where the clusters rather adopt a highly ordered state with janus-like core structure and a Cu surface segregation monolayer atop of Ni, thereby minimizing atomic level stresses. Our simulations, performed for various particle sizes, temperatures and cross checked by using different semiempirical potentials challenge existing theoretical models and shed new light on the energy landscape of this nanoscaled system. read less J. Harvey, A. Gheribi, and P. Chartrand, “Accurate determination of the Gibbs energy of Cu-Zr melts using the thermodynamic integration method in Monte Carlo simulations.,” The Journal of chemical physics. 2011. link Times cited: 19 Abstract: The design of multicomponent alloys used in different applic… read more Abstract: The design of multicomponent alloys used in different applications based on specific thermo-physical properties determined experimentally or predicted from theoretical calculations is of major importance in many engineering applications. A procedure based on Monte Carlo simulations (MCS) and the thermodynamic integration (TI) method to improve the quality of the predicted thermodynamic properties calculated from classical thermodynamic calculations is presented in this study. The Gibbs energy function of the liquid phase of the Cu-Zr system at 1800 K has been determined based on this approach. The internal structure of Cu-Zr melts and amorphous alloys at different temperatures, as well as other physical properties were also obtained from MCS in which the phase trajectory was modeled by the modified embedded atom model formalism. A rigorous comparison between available experimental data and simulated thermo-physical properties obtained from our MCS is presented in this work. The modified quasichemical model in the pair approximation was parameterized using the internal structure data obtained from our MCS and the precise Gibbs energy function calculated at 1800 K from the TI method. The predicted activity of copper in Cu-Zr melts at 1499 K obtained from our thermodynamic optimization was corroborated by experimental data found in the literature. The validity of the amplitude of the entropy of mixing obtained from the in silico procedure presented in this work was analyzed based on the thermodynamic description of hard sphere mixtures. read less M. Wakeda and J. Saida, “Temperature-dependent effect of cooling rate on the melt-quenching process of metallic glasses,” Computational Materials Science. 2023. link Times cited: 2 G. Katakareddi and N. Yedla, “The effect of loading methods on the microstructural evolution and degree of strain localization in Cu50Zr50 metallic glass composite nanowires: A molecular dynamics simulation study.,” Journal of molecular graphics & modelling. 2022. link Times cited: 1 S. Xu, W. Wu, J. Chang, S. Sha, and B. Wei, “Duplex Solidification Mechanisms of Glass Forming Zr55Cu30Al10Ni5 Alloy During Electromagnetic Levitation Processing,” Metallurgical and Materials Transactions A. 2022. link Times cited: 3 S. Oh, X.-gang Lu, Q. Chen, and B.-J. Lee, “Pressure dependence of thermodynamic interaction parameters for binary solid solution phases: An atomistic simulation study,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2021. link Times cited: 0 Y. Guan, W. Song, Y. Wang, S. Liu, and Y. Yu, “Dynamic responses in shocked Cu-Zr nanoglasses with gradient microstructure,” International Journal of Plasticity. 2021. link Times cited: 11 Z. Jin, X. Li, and K. Lu, “Formation of Stable Schwarz Crystals in Polycrystalline Copper at the Grain Size Limit.,” Physical review letters. 2021. link Times cited: 12 Abstract: A prototype Schwarz crystal (SC) structure of dividing-space… read more Abstract: A prototype Schwarz crystal (SC) structure of dividing-space minimal grain boundaries (GBs) constrained by coherent twin boundaries (CTBs) was recently discovered in extremely fine-grained polycrystalline Cu. In this Letter, constraining effects of 3D CTB network on the formation and thermostability of SC are addressed via atomistic simulations. GB migration and evolution of CTB network trigger formation of SC diamond. CTB constraints are critical to generate GBs of zero mean curvature underlying vanishing capillary pressure, and to counterbalance the elastic driving forces of lattice. GB motion can be suppressed at temperatures close to the melting point with GB aperture down to 3 nm. read less Y.-L. Guan, L. Dai, J. Shao, and W. Song, “Molecular dynamics study on the nanovoid collapse and local deformation in shocked Cu50Zr50 metallic glasses,” Journal of Non-crystalline Solids. 2021. link Times cited: 11 M. Zhang et al., “Interfacial bonding of CuZr metallic glass via oxide: A molecular dynamics study,” Corrosion Science. 2021. link Times cited: 4 A. Agrawal and R. Mirzaeifar, “Copper-graphene composites; developing the MEAM potential and investigating their mechanical properties,” Computational Materials Science. 2021. link Times cited: 9 Y. Dou, Y. Liu, B. Huddleston, Y. Hammi, and M. Horstemeyer, “A molecular dynamics study of effects of crystal orientation, size scale, and strain rate on penetration mechanisms of monocrystalline copper subjected to impact from a nickel penetrator at very high strain rates,” Acta Mechanica. 2020. link Times cited: 6 A.-V. Pham, T. Fang, A.-S. Tran, and T.-H. Chen, “Effect of annealing and deposition of Cu atoms on Ni trench to interface formation and growth mechanisms of Cu coating,” Superlattices and Microstructures. 2020. link Times cited: 8 M. Zhang, Q. Li, J. Zhang, G. Zheng, and X. Wang, “The prominent combination of ultrahigh strength and superior tensile plasticity in Cu–Zr nanoglass connected by oxide interfaces: A molecular dynamics study,” Journal of Alloys and Compounds. 2019. link Times cited: 14 H. R. A. Ram, K. Kashyap, K. S. Sridhar, K. Venkatesh, K. Gopalakrishna, and R. Keshavamurthy, “Experimental and theoretical prediction of Copper-Nickel nano-phase diagram,” Materials Research Express. 2019. link Times cited: 1 Abstract: Copper and Nickel alloys form binary isomorphous system with… read more Abstract: Copper and Nickel alloys form binary isomorphous system with a symmetric lens shaped curve formed by solidus and liquidus. This shape and size of the solidus and liquidus curves are altered by the particle size. This effect is greatly enhanced if the particle size is less than 100 nm. In the present work, phase diagram is predicted for nanoparticles considering Copper and Nickel and is compared with the experimental results. Copper and Nickel nanoparticles were procured and were characterized for the particle morphology and size using TEM, FE-SEM and XRD. The nanoparticles were also subjected to DSC analysis to find the melting point. The nanoparticles were blended in a high energy ball-mill for various compositions. The blending was carried out for different time intervals and was characterized using XRD to find the effective alloying time. The blended nanoparticles after effective alloying were subjected to DSC analysis to experimentally determine the solidus and liquidus points for various compositions. Phase diagram was determined experimentally and was compared with the theoretical prediction. GTE model and E&E models were used to predict the phase diagram for nanoparticles and was compared with the experimental results. It was found that the E&E model acurately predicts the nano phase diagram for Cu–Ni system with an error of 2% for 89 wt% Cu-11 wt% Ni alloy. read less R. P. Leite and M. Koning, “Nonequilibrium free-energy calculations of fluids using LAMMPS,” Computational Materials Science. 2019. link Times cited: 21 Y. Wang, C. Peng, X. Li, Y. Cheng, L. Jia, and L. Wang, “Dynamical mechanical analysis of metallic glass with and without miscibility gap,” Materials Science and Engineering: A. 2018. link Times cited: 2 Y.-K. Kim, H. Kim, W. Jung, and B.-J. Lee, “Development and application of Ni-Ti and Ni-Al-Ti 2NN-MEAM interatomic potentials for Ni-base superalloys,” Computational Materials Science. 2017. link Times cited: 24 C.-jun Wu, B.-J. Lee, and X. Su, “Modified embedded-atom interatomic potential for Fe-Ni, Cr-Ni and Fe-Cr-Ni systems,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2017. link Times cited: 60 T. Kulikova, A. Maiorova, V. Bykov, and K. Shunyaev, “Chemical interaction and thermodynamic properties of (Cu,Ni)-Zr glass-forming alloys,” The European Physical Journal Special Topics. 2017. link Times cited: 6 A. P. Moore, B. Beeler, C. Deo, M. Baskes, and M. Okuniewski, “Atomistic modeling of high temperature uranium–zirconium alloy structure and thermodynamics,” Journal of Nuclear Materials. 2015. link Times cited: 41 S. Feng et al., “Atomic structure of shear bands in Cu64Zr36 metallic glasses studied by molecular dynamics simulations,” Acta Materialia. 2015. link Times cited: 98 W. Dong, Z. Chen, and B.-J. Lee, “Modified embedded-atom interatomic potential for Co–W and Al–W systems,” Transactions of Nonferrous Metals Society of China. 2015. link Times cited: 9 B.-M. Lee, J. Shim, J.-Y. Suh, and B.-J. Lee, “A semi-empirical methodology to predict hydrogen permeability in amorphous alloy membranes,” Journal of Membrane Science. 2014. link Times cited: 4 M. Trybula, N. Jakse, W. Gasior, and A. Pasturel, “Structural and physicochemical properties of liquid Al-Zn alloys: a combined study based on molecular dynamics simulations and the quasi-lattice theory.,” The Journal of chemical physics. 2014. link Times cited: 15 Abstract: Ordering phenomena have been investigated in liquid Al-Zn al… read more Abstract: Ordering phenomena have been investigated in liquid Al-Zn alloys performing molecular dynamics (MD) simulations using "empirical oscillating pair potentials." The local structural order is studied by computing two microscopic functions, namely, the concentration fluctuation function and the Warren-Cowley short-range order parameter. We also study the influence of ordering phenomena on transport properties like diffusivity and viscosity. The MD results are confronted to those determined from measurements and in the framework of the quasi-lattice theory. read less J. Harvey, A. Gheribi, and P. Chartrand, “Thermodynamic integration based on classical atomistic simulations to determine the Gibbs energy of condensed phases: Calculation of the aluminum-zirconium system,” Physical Review B. 2012. link Times cited: 17 Abstract: In this work, an in silico procedure to generate a fully coh… read more Abstract: In this work, an in silico procedure to generate a fully coherent set of thermodynamic properties obtained from classical molecular dynamics (MD) and Monte Carlo (MC) simulations is proposed. The procedure is applied to the Al-Zr system because of its importance in the development of high strength Al-Li alloys and of bulk metallic glasses. Cohesive energies of the studied condensed phases of the Al-Zr system (the liquid phase, the fcc solid solution, and various orthorhombic stoichiometric compounds) are calculated using the modified embedded atom model (MEAM) in the second-nearest-neighbor formalism (2NN). The Al-Zr MEAM-2NN potential is parameterized in this work using ab initio and experimental data found in the literature for the AlZr${}_{3}$-L1${}_{2}$ structure, while its predictive ability is confirmed for several other solid structures and for the liquid phase. The thermodynamic integration (TI) method is implemented in a general MC algorithm in order to evaluate the absolute Gibbs energy of the liquid and the fcc solutions. The entropy of mixing calculated from the TI method, combined to the enthalpy of mixing and the heat capacity data generated from MD/MC simulations performed in the isobaric-isothermal/canonical (NPT/NVT) ensembles are used to parameterize the Gibbs energy function of all the condensed phases in the Al-rich side of the Al-Zr system in a CALculation of PHAse Diagrams (CALPHAD) approach. The modified quasichemical model in the pair approximation (MQMPA) and the cluster variation method (CVM) in the tetrahedron approximation are used to define the Gibbs energy of the liquid and the fcc solid solution respectively for their entire range of composition. Thermodynamic and structural data generated from our MD/MC simulations are used as input data to parameterize these thermodynamic models. A detailed analysis of the validity and transferability of the Al-Zr MEAM-2NN potential is presented throughout our work by comparing the predicted properties obtained from this formalism with available ab initio and experimental data for both liquid and solid phases. read less W. Dong, H.-K. Kim, W. Ko, B.-M. Lee, and B.-J. Lee, “Atomistic modeling of pure Co and Co–Al system,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2012. link Times cited: 42 M. Horstemeyer, “Atomistic Modeling Methods.” 2012. link Times cited: 0 K. Park, H. Park, and E. Fleury, “Strain localization in annealed Cu50Zr50 metallic glass,” Materials Science and Engineering A-structural Materials Properties Microstructure and Processing. 2011. link Times cited: 7 Y. Zhang, N. Mattern, and J. Eckert, “Molecular dynamic simulation study of the structural anisotropy in Cu50Zr50 and Cu64.5Zr35.5 metallic glasses induced by static uniaxial loading within the elastic regime,” Journal of Alloys and Compounds. 2011. link Times cited: 7 Y. Zhang, N. Mattern, and J. Eckert, “Effect of uniaxial loading on the structural anisotropy and the dynamics of atoms of Cu50Zr50 metallic glasses within the elastic regime studied by molecular dynamics simulation,” Acta Materialia. 2011. link Times cited: 26 B.-J. Lee, W. Ko, H.-K. Kim, and E.-H. Kim, “The modified embedded-atom method interatomic potentials and recent progress in atomistic simulations,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2010. link Times cited: 137 K. Park, Y. Shibutani, M. Falk, B.-J. Lee, and J.-C. Lee, “Shear localization and the plasticity of bulk amorphous alloys,” Scripta Materialia. 2010. link Times cited: 30 Y.-M. Kim, N. Kim, and B.-J. Lee, “Atomistic Modeling of pure Mg and Mg―Al systems,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2009. link Times cited: 119 C. Lee, K. Park, B.-J. Lee, Y. Shibutani, and J.-C. Lee, “Structural disordering of amorphous alloys: A molecular dynamics analysis,” Scripta Materialia. 2009. link Times cited: 19 S.-G. Kim et al., “Semi-Empirical Potential Methods for Atomistic Simulations of Metals and Their Construction Procedures,” Journal of Engineering Materials and Technology-transactions of The Asme. 2009. link Times cited: 20 Abstract: General theory of semi-empirical potential methods including… read more Abstract: General theory of semi-empirical potential methods including embedded-atom method and modified-embedded-atom method (MEAM) is reviewed. The procedures to construct these potentials are also reviewed. A multi-objective optimization (MOO) procedure has been developed to construct MEAM potentials with minimal manual fitting. This procedure has been applied successfully to develop a new MEAM potential for magnesium. The MOO procedure is designed to optimally reproduce multiple target values that consist of important material properties obtained from experiments and first-principle calculations based on density-functional theory. The optimized target quantities include elastic constants, cohesive energies, surface energies, vacancy-formation energies, and the forces on atoms in a variety of structures. The accuracy of the present potential is assessed by computing several material properties of Mg including their thermal properties. We found that the new MEAM potential shows a significant improvement over previously published potentials, especially for the atomic forces and melting temperature calculations. read less K. Kang, I. Sa, J.-C. Lee, E. Fleury, and B.-J. Lee, “Atomistic modeling of the Cu-Zr-Ag bulk metallic glass system,” Scripta Materialia. 2009. link Times cited: 26 C. Lee, K. Park, B.-J. Lee, J. Shim, and J.-C. Lee, “Understanding the Plasticity of Amorphous Alloys Via the Interpretation of Structural Evolution Inside a Shear Band,” Korean Journal of Materials Research. 2009. link Times cited: 1 Abstract: )Abstract The effect of the initial packing structure on the… read more Abstract: )Abstract The effect of the initial packing structure on the plasticity of amorphous alloys was investigated bytracing the structural evolution of the amorphous solid inside a shear band. According to the moleculardynamics simulations, the structural evolution of the amorphous solids inside the shear band was more abruptin the alloy with a higher initial packing density. Such a difference in the structural evolution within the shearband observed from the amorphous alloys with different initial packing density is believed to cause differentdegrees of shear localization, providing an answer to the fundamental question of why amorphous alloys showdifferent plasticity. We clarify the structural origin of the plasticity of bulk amorphous alloys by exploring themicrostructural aspects in view of the structural disordering, disorder-induced softening, and shear localizationusing molecular dynamics simulations based on the recently developed MEAM (modified embedded atommethod) potential.Key wordsamorphous alloys, free volume, structural disorder, molecular dynamics. read less I. Sa and B.-J. Lee, “Modified embedded-atom method interatomic potentials for the Fe-Nb and Fe-Ti binary systems,” Scripta Materialia. 2008. link Times cited: 48 M. Lee, C. Lee, K.-R. Lee, E. Ma, and J.-C. Lee, “Networked interpenetrating connections of icosahedra: Effects on shear transformations in metallic glass,” Acta Materialia. 2011. link Times cited: 191 K. Kang, K. Park, J.-C. Lee, E. Fleury, and B.-J. Lee, “Correlation between plasticity and other materials properties of Cu–Zr bulk metallic glasses: An atomistic simulation study,” Acta Materialia. 2011. link Times cited: 29 Y.-M. Kim, Y.-H. Shin, and B.-J. Lee, “Modified embedded-atom method interatomic potentials for pure Mn and the Fe–Mn system,” Acta Materialia. 2009. link Times cited: 64 H. Mei et al., “Development of Machine Learning and Empirical Interatomic Potentials for the Binary Zr-Sn System,” Journal of Nuclear Materials. 2023. link Times cited: 0 J. Zhang, A. Quintana, E. Menéndez, M. Coll, E. Pellicer, and J. Sort, “Electrodeposited Ni-Based Magnetic Mesoporous Films as Smart Surfaces for Atomic Layer Deposition: An ‘All-Chemical’ Deposition Approach toward 3D Nanoengineered Composite Layers.,” ACS applied materials & interfaces. 2018. link Times cited: 16 Abstract: Mesoporous Ni and Cu-Ni (Cu20Ni80 and Cu45Ni55 in at. %) fil… read more Abstract: Mesoporous Ni and Cu-Ni (Cu20Ni80 and Cu45Ni55 in at. %) films, showing a three-dimensional (3D) porous structure and tunable magnetic properties, are prepared by electrodeposition from aqueous surfactant solutions using micelles of P-123 triblock copolymer as structure-directing entities. Pores between 5 and 30 nm and dissimilar space arrangements (continuous interconnected networks, circular pores, corrugated mesophases) are obtained depending on the synthetic conditions. X-ray diffraction studies reveal that the Cu-Ni films have crystallized in the face-centered cubic structure, are textured, and exhibit certain degree of phase separation, particularly those with a higher Cu content. Atomic layer deposition (ALD) is used to conformally coat the mesopores of Cu20Ni80 film with amorphous Al2O3, rendering multiphase "nano-in-meso" metal-ceramic composites without compromising the ferromagnetic response of the metallic scaffold. From a technological viewpoint, these 3D nanoengineered composite films could be appealing for applications like magnetically actuated micro/nanoelectromechanical systems (MEMS/NEMS), voltage-driven magneto-electric devices, capacitors, or as protective coatings with superior strength and tribological performance. read less D. Miracle, G. Wilks, A. Dahlman, and J. Dahlman, “The Strength of Chemical Bonds in Solids and Liquids (Preprint).” 2011. link Times cited: 13 E. Pellicer et al., “Grain boundary segregation and interdiffusion effects in nickel-copper alloys: an effective means to improve the thermal stability of nanocrystalline nickel.,” ACS applied materials & interfaces. 2011. link Times cited: 65 Abstract: Nanocrystalline (nc) Ni films show pronounced grain growth a… read more Abstract: Nanocrystalline (nc) Ni films show pronounced grain growth and suffer from concomitant deterioration of their mechanical and magnetic properties after annealing at relatively low temperatures (T(ANN) ≥ 475 K). This constitutes a drawback for their applicability as coatings or in components of miniaturized devices. This work reveals that the thermal stability of nc Ni is significantly improved by controllably alloying Ni with Cu, by means of electrodeposition, to form a Ni(1-x)Cu(x) solid solution. To tune the composition of such nc alloys, Ni(1-x)Cu(x) films are deposited galvanostatically using an electrolytic bath containing Ni and Cu sulfate salts as electroactive species, saccharine as grain-refining agent, and applying current densities ranging from -10 to -40 mA cm(-2). The enhanced thermal stability is ascribed to segregation of a Cu-rich phase at the Ni(1-x)Cu(x) grain boundaries, which acts as a shielding layer against grain growth. As a result, high values of hardness (in excess of 6 GPa) remain in nc Ni(1-x)Cu(x) for x ≥ 0.3, even after annealing at T(ANN) ≥ 575 K. From a magnetic point of view, Ni(1-x)Cu(x) films possess lower coercivity values than pure nc Ni films, both in the as-prepared and annealed states, thus offering potential advantages for certain soft magnetic applications. read less J. Li, X. Dai, S. Liang, K. Tai, Y. Kong, and B. Liu, “Interatomic potentials of the binary transition metal systems and some applications in materials physics,” Physics Reports. 2008. link Times cited: 110 O. G. Nicholls, D. Frost, V. Tuli, J. Smutná, M. Wenman, and P. Burr, “Transferability of Zr-Zr interatomic potentials,” Journal of Nuclear Materials. 2022. link Times cited: 6 S.-S. Shin, H.-K. Kim, J.-C. Lee, and I. Park, “Effect of Sub-Tg Annealing on the Corrosion Resistance of the Cu–Zr Amorphous Alloys,” Acta Metallurgica Sinica (English Letters). 2018. link Times cited: 6 B.-M. Lee and B.-J. Lee, “A Comparative Study on Hydrogen Diffusion in Amorphous and Crystalline Metals Using a Molecular Dynamics Simulation,” Metallurgical and Materials Transactions A. 2014. link Times cited: 35 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 H. Kim, M. Lee, K.-R. Lee, and J.-C. Lee, “How can a minor element added to a binary amorphous alloy simultaneously improve the plasticity and glass-forming ability?,” Acta Materialia. 2013. link Times cited: 55 B.-M. Lee and B.-J. Lee, “Probing the hydrogen movement in Zr-Cu amorphous alloys using molecular dynamics simulations,” 2011 IEEE Nanotechnology Materials and Devices Conference. 2011. link Times cited: 0 Abstract: Zr-based amorphous alloys, showing hydrogen permeance compar… read more Abstract: Zr-based amorphous alloys, showing hydrogen permeance comparable to pure crystalline Pd, are prospective candidates for replacing the current Pd-based hydrogen selective membranes. There have been a lot of theoretical studies about the diffusion mechanism in their amorphous structures. But most of them have provided only just phenomenological understanding because of staying on works with qualitative approximations. To overcome this situation and get more realistic insight about the hydrogen movement in amorphous metals, we adopted atomistic modeling which gives directly quantitative information about nanoscale phenomena. In order to perform such an atomistic simulation, interatomic potentials for the Zr-H and Cu-H binary systems had to be developed based on the second nearest-neighbor modified embedded-atom method_(2NN MEAM) formalism. A few first-principles calculations of physical properties for the Cu-H binary system were carried out to supplement data which are necessary to optimize the potential parameters. The developing potentials in this study will be able to reasonably reproduce fundamental physical properties (structural, thermodynamic, defect and diffusion properties). Finally we are going to perform diffusion simulations for each amorphous and crystalline Zr-Cu alloy of same composition, and obtain quantitative results about the difference between them. read less X. J. Han and H. Schober, “Transport properties and Stokes-Einstein relation in a computer-simulated glass-forming Cu 33 . 3 Zr 66 . 7 melt,” Physical Review B. 2011. link Times cited: 66 Abstract: Molecular dynamics simulation with a modified embedded atom … read more Abstract: Molecular dynamics simulation with a modified embedded atom potential was used to study transport properties and the Stokes-Einstein relation of a glass-forming Cu${}_{33.3}$Zr${}_{66.7}$ metallic melt. Upon cooling, at high temperatures, the self-diffusion coefficients of the two species evolve nearly parallel, whereas they diverge below 1600 K. The viscosity as function of temperature is calculated from the Green-Kubo equation. The critical temperature of mode coupling theory ${T}_{\mathrm{c}}$ is found as 1030 K, from both the transport properties and the \ensuremath{\alpha}-relaxation time. It is found that the Stokes-Einstein relation between viscosity and diffusivity breaks down at around 1600 K, far above ${T}_{\mathrm{c}}$ and even above the melting temperature. The temperature dependence of the effective diameter in the Stokes-Einstein relation correlates closely with the first derivative of the ratio of the self-diffusion coefficients of the two components. We propose that the onset of Stokes-Einstein relation breakdown could be predicted quantitatively by the divergence behavior of diffusion coefficients, and the breakdown of Stokes-Einstein relation is ascribed to the sudden increase of the dynamic heterogeneity. read less E. Lee and B.-J. Lee, “Modified embedded-atom method interatomic potential for the Fe–Al system,” Journal of Physics: Condensed Matter. 2010. link Times cited: 100 Abstract: An interatomic potential for the Fe–Al binary system has bee… read more Abstract: An interatomic potential for the Fe–Al binary system has been developed based on the modified embedded-atom method (MEAM) potential formalism. The potential can describe various fundamental physical properties of Fe–Al binary alloys—structural, elastic and thermodynamic properties, defect formation behavior and interactions between defects—in reasonable agreement with experimental data or higher-level calculations. The applicability of the potential to atomistic investigations of various defect formation behaviors and their effects on the mechanical properties of high aluminum steels as well as Fe–Al binary alloys is demonstrated. read less A. M. Nieves, V. Vitek, and T. Sinno, “Atomistic analysis of phase segregation patterning in binary thin films using applied mechanical fields,” Journal of Applied Physics. 2010. link Times cited: 5 Abstract: The patterned compositional evolution in thin films of a bin… read more Abstract: The patterned compositional evolution in thin films of a binary alloy controlled by modulated stress fields is studied by employing Monte Carlo simulations. General features of stress-patterned phase segregation are probed using a binary Lennard-Jones potential in which the lattice misfit between the two components of the alloy is varied systematically. In general, patterning of the microstructure is found to be more robust in the low-mismatch binary systems because large lattice mismatch promotes plastic, and therefore, irreversible relaxation, during annealing. It is shown that some control over the relaxation process can be achieved by careful design of the applied thermal annealing history. Additional calculations have been performed using two other potentials for binary metallic systems, an embedded-atom method (EAM) potential for Cu–Ag and a modified embedded-atom method (MEAM) potential for Cu–Ni that represent examples of high and low-mismatched systems, respectively. The results obtained with gen... read less G. Bonny, R. Pasianot, and L. Malerba, “Fitting interatomic potentials consistent with thermodynamics: Fe, Cu, Ni and their alloys,” Philosophical Magazine. 2009. link Times cited: 24 Abstract: In computational materials science, many atomistic methods h… read more Abstract: In computational materials science, many atomistic methods hinge on an interatomic potential to describe material properties. In alloys, besides a proper description of problem-specific properties, a reasonable reproduction of the experimental phase diagram by the potential is essential. In this framework, two complementary methods were developed to fit interatomic potentials to the thermodynamic properties of an alloy. The first method involves the zero Kelvin phase diagram and makes use of the concept of the configuration polyhedron. The second method involves phase boundaries at finite temperature and is based on the cluster variation method. As an example for both techniques, they are applied to the Fe–Cu, Fe–Ni and Cu–Ni systems. The resulting potentials are compared to those found in the literature and are found to reproduce the experimental phase diagram more consistently than the latter. read less E. C. Do, Y.-H. Shin, and B.-J. Lee, “Atomistic modeling of III–V nitrides: modified embedded-atom method interatomic potentials for GaN, InN and Ga1−xInxN,” Journal of Physics: Condensed Matter. 2009. link Times cited: 26 Abstract: Modified embedded-atom method (MEAM) interatomic potentials … read more Abstract: Modified embedded-atom method (MEAM) interatomic potentials for the Ga–N and In–N binary and Ga–In–N ternary systems have been developed based on the previously developed potentials for Ga, In and N. The potentials can describe various physical properties (structural, elastic and defect properties) of both zinc-blende and wurtzite-type GaN and InN as well as those of constituent elements, in good agreement with experimental data or high-level calculations. The potential can also describe the structural behavior of Ga1−xInxN ternary nitrides reasonably well. The applicability of the potentials to atomistic investigations of atomic/nanoscale structural evolution in Ga1−xInxN multi-component nitrides during the deposition of constituent element atoms is discussed. read less M. Mendelev, M. Kramer, R. Ott, D. Sordelet, D. Yagodin, and P. Popel,’ “Development of suitable interatomic potentials for simulation of liquid and amorphous Cu–Zr alloys,” Philosophical Magazine. 2009. link Times cited: 334 Abstract: We present a new semi-empirical potential suitable for molec… read more Abstract: We present a new semi-empirical potential suitable for molecular dynamics simulations of liquid and amorphous Cu–Zr alloys. To provide input data for developing the potential, new experimental measurements of the structure factors for amorphous Cu64.5Zr35.5 alloy were performed. In this work, we propose a new method to include diffraction data in the potential development procedure, which also includes fitting to first-principles and liquid density and enthalpy of mixing data. To refine the new potential, we used first-principles and liquid enthalpy of mixing data published earlier combined with the densities of liquid Cu64.5Zr35.5 measured over a range of temperatures. We show that the potential predicts a liquid-to-glass transition temperature that agrees reasonably well with experimental data. Finally, we compare the new potential with two previously developed semi-empirical potentials for Cu–Zr alloys and examine their comparative and contrasting descriptions of structure and properties for Cu64.5Zr35.5 liquids and glasses. read less S. Valone and M. Baskes, “Self-Irradiation Cascade Simulations in Plutonium Metal: Model Behavior at High Energy,” Journal of Computer-Aided Materials Design. 2007. link Times cited: 10 J.-S. Kim, Y. Koo, and B.-J. Lee, “Modified embedded-atom method interatomic potential for the Fe–Pt alloy system,” Journal of Materials Research. 2006. link Times cited: 36 Abstract: A semi-empirical interatomic potential formalism, the modifi… read more Abstract: A semi-empirical interatomic potential formalism, the modified embedded atom method (MEAM), has been applied to obtain an interatomic potential for the Fe–Pt alloy system, based on the previously developed potentials for pure Fe and Pt. The potential can describe basic physical properties of the alloys (lattice parameter, bulk modulus, stability of individual phases, and order/disorder transformations), in good agreement with experimental information. The procedure for the determination of potential parameter values and comparisons between the present calculation and experimental data or high level calculation are presented. The applicability of the potential to atomistic studies to investigate structural evolution of Fe_50Pt_50 alloy thin films during post-annealing is also discussed. read less N. Vuksic, “New Zirconium Hydrogen Second Nearest Neighbor Modified Embedded Atom Method (MEAM) Potential For Simulation of Stacking Fault Energy Along the < 011̄0 > Path Of The Hexagonal Closely Packed Lattice Basal Plane.” 2014. link Times cited: 0 Abstract: A new Modified Embedded Atom Method (MEAM) potential for zir… read more Abstract: A new Modified Embedded Atom Method (MEAM) potential for zirconium and hydrogen, called the second nearest-neighbor MEAM (2nnMEAM), was created to more effectively simulate the stacking fault energy of different zirconium hydrogen solid solutions along the < 011̄0 > path of the hexagonal closely packed (hcp) lattice basal plane. The 2nnMEAM is a binary alloy MEAM with a less severe screening function that enables the potential to include longer range interactions between atoms. The 2nnMEAM is required because the existing MEAM potential for zirconium and hydrogen, developed by Dr.M.Baskes (in the text referred to as the MEAM potential), although useful for bulk tests of basic physical properties of different zirconium hydrogen phases, was not capable to model the energetics associated with basal slip. Several previous papers outlined the process of creating binary alloy MEAM potential out of the MEAM potentials of different pure elements. Due to the fact that there is no direct method of combining pure elements MEAM data, a trial and error approach was used to gradually achieve qualitative similarity with the first principles results. This translated into physical behavior, the goal was to show that the 2nnMEAM can be fine-tuned to replicate realistic response of the material during the tests and demonstrate the power of the MEAM methodology. The quantitative agreement was not achieved due to too many unknown MEAM parameters, lack of their physical meaning and functional influence on each other. Furthermore, none of the academic papers used as the basis for this research ventured into more complex tests like stacking fault, but bulk ones, and even then stressed the approximate nature of the MEAM methodology compared to much more precise first principles simulations. As a main tool for simulating behavior of different zirconium hydrogen solid solutions and testing of different MEAM versions, Large Scale Atomic/Molecular Massively read less
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_409065472403_002
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.	MEAM_LAMMPS_LeeShim_2004_NiCu__MO_409065472403_002
DOI	10.25950/2a6ef3ab https://doi.org/10.25950/2a6ef3ab https://commons.datacite.org/doi.org/10.25950/2a6ef3ab
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 MEAM_LAMMPS__MD_249792265679_002
Driver	MEAM_LAMMPS__MD_249792265679_002
KIM API Version	2.2
Potential Type	meam

Previous Version	MEAM_LAMMPS_LeeShim_2004_NiCu__MO_409065472403_001

Verification Check Dashboard

(Click here to learn more about Verification Checks)

Grade	Name	Category	Brief Description	Full Results	Aux File(s)
P All elements claimed by model are supported in at least one of the tested configurations.	vc-species-supported-as-stated	mandatory	The model supports all species it claims to support; see full description.	Results	Files
P Periodic boundary conditions were correctly supported for all configurations that the model was able to compute.	vc-periodicity-support	mandatory	Periodic boundary conditions are handled correctly; see full description.	Results	Files
P Model energy has permutation symmetry for all configurations the model was able to compute.	vc-permutation-symmetry	mandatory	Total energy and forces are unchanged when swapping atoms of the same species; see full description.	Results	Files
A The letter grade A was assigned because the normalized error in the computation was 4.28032e-09 compared with a machine precision of 2.22045e-16. The letter grade was based on 'score=log10(error/eps)', with ranges A=[0, 7.5], B=(7.5, 10.0], C=(10.0, 12.5], D=(12.5, 15.0), F>15.0. 'A' is the best grade, and 'F' indicates failure.	vc-forces-numerical-derivative	consistency	Forces computed by the model agree with numerical derivatives of the energy; see full description.	Results	Files
F The model is C^0 continuous. This means that the model has continuous energy, but a discontinuous first derivative.	vc-dimer-continuity-c1	informational	The energy versus separation relation of a pair of atoms is C1 continuous (i.e. the function and its first derivative are continuous); see full description.	Results	Files
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: Cu

Species: Ni

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: Ni

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

Species: Ni

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: Ni

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: Ni

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

Species: Ni

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: Ni

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: Ni

Cubic Crystal Basic Properties Table

Species: Cu

Species: Ni

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	6405
Cohesive energy versus lattice constant curve for bcc Ni v004	view	6405
Cohesive energy versus lattice constant curve for diamond Cu v004	view	5749
Cohesive energy versus lattice constant curve for diamond Ni v004	view	6626
Cohesive energy versus lattice constant curve for fcc Cu v004	view	6552
Cohesive energy versus lattice constant curve for fcc Ni v004	view	6684
Cohesive energy versus lattice constant curve for sc Cu v004	view	6626
Cohesive energy versus lattice constant curve for sc Ni v004	view	6699

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	19474
Elastic constants for bcc Ni at zero temperature v006	view	20320
Elastic constants for diamond Cu at zero temperature v001	view	38356
Elastic constants for diamond Ni at zero temperature v001	view	44320
Elastic constants for fcc Cu at zero temperature v006	view	19186
Elastic constants for fcc Ni at zero temperature v006	view	37620
Elastic constants for sc Cu at zero temperature v006	view	17853
Elastic constants for sc Ni at zero temperature v006	view	43255

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	66479
Equilibrium crystal structure and energy for Cu in AFLOW crystal prototype A_cI2_229_a v001		view	66258

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 Ni in AFLOW crystal prototype A_cF4_225_a v002	view	84369
Equilibrium crystal structure and energy for Ni in AFLOW crystal prototype A_cI2_229_a v002	view	57056
Equilibrium crystal structure and energy for Ni in AFLOW crystal prototype A_hP2_194_c v002	view	69792

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	10886623
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Cu v001	view	31603345
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Ni v001	view	73334006
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Cu v001	view	15963479
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Ni v001	view	41904219
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Cu v001	view	74253255

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	12000
Equilibrium zero-temperature lattice constant for bcc Ni v007	view	8393
Equilibrium zero-temperature lattice constant for diamond Cu v007	view	11199
Equilibrium zero-temperature lattice constant for diamond Ni v007	view	10831
Equilibrium zero-temperature lattice constant for fcc Cu v007	view	13988
Equilibrium zero-temperature lattice constant for fcc Ni v007	view	10822
Equilibrium zero-temperature lattice constant for sc Cu v007	view	8614
Equilibrium zero-temperature lattice constant for sc Ni v007	view	10622

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	112050
Equilibrium lattice constants for hcp Ni v005		view	115805

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	47412044

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 Ni at 293.15 K under a pressure of 0 MPa v002		view	3022932

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	104026
Phonon dispersion relations for fcc Ni v004		view	87920

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	15482172
Stacking and twinning fault energies for fcc Ni v002		view	37394723

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	92199
Broken-bond fit of high-symmetry surface energies in fcc Ni v004		view	117363

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	295365
Monovacancy formation energy and relaxation volume for fcc Ni		view	508939

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	1595430
Vacancy formation and migration energy for fcc Ni		view	1361169

Errors

ElasticConstantsHexagonal__TD_612503193866_004

Test	Error Categories	Link to Error page
Elastic constants for hcp Cu at zero temperature v004	other	view
Elastic constants for hcp Ni at zero temperature v004	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 Ni v001	other	view
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Ni v001	other	view

PhononDispersionCurve__TD_530195868545_004

Test	Error Categories	Link to Error page
Phonon dispersion relations for fcc Cu v004	other	view
Phonon dispersion relations for fcc Ni v004	other	view

SurfaceEnergyCubicCrystalBrokenBondFit__TD_955413365818_004

Test	Error Categories	Link to Error page
Broken-bond fit of high-symmetry surface energies in fcc Cu v004	other	view
Broken-bond fit of high-symmetry surface energies in fcc Ni v004	other	view

Files

CMakeLists.txt
LICENSE
NiCu.meam
elems.meam
kimprovenance.edn
kimspec.edn
library.meam

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MEAM_LAMMPS_LeeShim_2004_NiCu__MO_409065472403_002.txz	Tar+XZ	Linux and OS X archive
MEAM_LAMMPS_LeeShim_2004_NiCu__MO_409065472403_002.zip	Zip	Windows archive

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This Model requires a Model Driver. Archives for the Model Driver MEAM_LAMMPS__MD_249792265679_002 appear below.

MEAM_LAMMPS__MD_249792265679_002.txz	Tar+XZ	Linux and OS X archive
MEAM_LAMMPS__MD_249792265679_002.zip	Zip	Windows archive

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MEAM_LAMMPS_LeeShim_2004_NiCu__MO_409065472403_002

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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

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