EAM potential (LAMMPS cubic hermite tabulation) for Cu-Ni alloys developed by Onat and Durukanoğlu (2014) v005

Yuri Mishin; Papaconstantopoulos, D. A.; Mehl, M. J.

doi:10.25950/e2733dc9

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EAM_Dynamo_OnatDurukanoglu_2014_CuNi__MO_592013496703_005

There is a newer version of this item. See EAM_Dynamo_OnatDurukanoglu_2014_CuNi__MO_592013496703_006

Interatomic potential for Copper (Cu), Nickel (Ni).
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Title A single sentence description.	EAM potential (LAMMPS cubic hermite tabulation) for Cu-Ni alloys developed by Onat and Durukanoğlu (2014) 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.	An optimized EAM potential for Cu-Ni alloys. The potential is determined by fitting to experimental and first-principles data for Cu, Ni and Cu-Ni binary compounds, such as lattice constants, cohesive energies, bulk modulus, elastic constants, diatomic bond lengths and bond energies. The generated potentials were tested by computing a variety of properties of pure elements and the alloy of Cu, Ni: the melting points, alloy mixing enthalpy, lattice specific heat, equilibrium lattice structures, vacancy formation and interstitial formation energies, and various diffusion barriers on the (100) and (111) surfaces of Cu and Ni. The details of the fitting procedure and the predictions of the potential are published at http://dx.doi.org/10.1088/0953-8984/26/3/035404. Using the developed potential, the vibrational thermodynamic functions of Cu-Ni alloys are also investigated and the results are published at http://epjb.epj.org/articles/epjb/abs/2014/11/b140315/b140315.html. This model uses parameter file 'CuNi_v2.eam.alloy', which is a newer version of the parameter file 'CuNi.eam.alloy' distributed with the LAMMPS simulation package.
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.	This potential is tabulated using more spline points to provide smoother cutoff and better accuracy for simulations.

Contributor	Berk Onat
Maintainer	Berk Onat
Developer	Yuri Mishin Papaconstantopoulos, D. A. Mehl, M. J.
Published on KIM	2018
How to Cite	Click here to download this 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. 80 Citations (63 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 J. Qi, C. Oberdorfer, W. Windl, and E. Marquis, “Ab initio simulation of field evaporation,” Physical Review Materials. 2022. link Times cited: 5 Abstract: A new simulation approach of field evaporation is presented.… read more Abstract: A new simulation approach of field evaporation is presented. The model combines classical electrostatics with molecular dynamics (MD) simulations. Unlike previous atomic-level simulation approaches, our method does not rely on an evaporation criterion based on thermal activation theory, instead, electric-field-induced forces on atoms are explicitly calculated and added to the interatomic forces. Atoms then simply move according to the laws of classical molecular dynamics and are"evaporated"when the external force overcomes interatomic bonding. This approach thus makes no ad-hoc assumptions concerning evaporation fields and criteria, which makes the simulation fully physics-based and"ab-initio"apart from the interatomic potential. As proof of principle, we perform simulations to determine material dependent critical voltages which allow assessing the evaporation fields and the corresponding steady-state tip shapes in different metals. We also extract critical evaporation fields in elemental metals and sublimation energies in a high entropy alloy to have a more direct comparison with tabulated values. In contrast to previous approaches, we show that our method is able to successfully reproduce the enhanced zone lines observed in experimental field desorption patterns. We also demonstrate the need for careful selection of the interatomic potential by a comparative study for the example of Cu-Ni alloys. read less X. Chen, “Effect of phase interface atomic coherency on dynamics of dislocations,” Journal of Materials Research. 2021. link Times cited: 0 Abstract: Coarse-grained atomistic simulations are conducted to study … read more Abstract: Coarse-grained atomistic simulations are conducted to study the effect of phase interface atomic coherency on the dynamics of dislocations in both metallic and non-metallic multilayers under compression. Results show that the Cu/Ni bimaterial with a coherent interface has a yield point of almost twice higher than the one with a semi-coherent interface. An increased number of semi-coherent interfaces provides richer sources for dislocation nucleation, giving rise to a lower yield point. The intersection of the deposited dislocations is shown as an effective facilitator of dislocation transmission and emission across the semi-coherent interfaces. In contrast to Cu/Ni, the Si/Ge bimaterial with coherent and semi-coherent interfaces exhibit yield strengths of only a 13% discrepancy. The dramatic difference is shown to be determined by the disparate deformation mechanisms of the interface dislocations. read less R. Gutierrez, I. Matanovic, M. Polak, R. Johnson, D. Morgan, and E. Schamiloglu, “First principles inelastic mean free paths coupled with Monte Carlo simulation of secondary electron yield of Cu-Ni, Cu-Zn, and Mo-Li,” Journal of Applied Physics. 2021. link Times cited: 6 Abstract: Secondary electron yield (SEY) is relevant for widely used c… read more Abstract: Secondary electron yield (SEY) is relevant for widely used characterization methods (e.g., secondary electron spectroscopy and electron microscopy) and materials applications (e.g., multipactor effect). Key quantities necessary for understanding the physics of electron transport in materials and simulation of SEY are electron mean free paths (MFPs). This paper explores the impact of alloying on MFPs and SEY for Cu-Ni, Cu-Zn, and Mo-Li alloys relative to their component metals Cu, Ni, Zn, Mo, and Li. Density functional theory calculations yield density of states, Fermi energy, work function, and frequency- and momentum-dependent energy loss function. These material properties were used to calculate MFPs and Monte Carlo simulations were performed to obtain energy dependent SEY for the alloys as well for the component metals. The results show that MFPs and SEYs of the studied alloys lie between those of component pure elements but are not a simple composition weighted average. Detailed analysis of the secondary electron generation and emission process shows that the changes in the SEY of alloys relative to the SEY of their component metals depend on the changes in both electronic structure and dielectric properties of the material. read less A. Selimov, S. Xu, Y. Chen, and D. McDowell, “Lattice dislocation induced misfit dislocation evolution in semi-coherent 111 bimetal interfaces,” Journal of Materials Research. 2021. link Times cited: 5 Abstract: The study of dislocation plasticity mediated by semi-coheren… read more Abstract: The study of dislocation plasticity mediated by semi-coherent interfaces can aid in the design of certain heterostructured materials, such as nanolaminates. The evolution of interface misfit patterns under complex stress fields arising from dislocation pileups can influence local dislocation/interface interactions, including effects of multiple incoming dislocations. This work utilizes the Concurrent Atomistic-Continuum modeling framework to probe the evolution of misfit structures at semi-coherent Ni/Cu and Cu/Ag interfaces impinged by dislocation pileups generated via nanoindentation. A continuum microrotation metric is computed at various stages of the indentation process and used to visualize the evolution of the interface misfit dislocation pattern. The stress state from approaching dislocations induces mixed contraction and expansion of misfit dislocation structures at the interface. A lower number of misfit nodes per unit interface area coincides with greater localized deformation with regard to atoms near misfit nodes for Ni/Cu. The decreased misfit node spacing for Cu/Ag alternatively distributes the restructuring associated with plastic deformation over a larger percentage of atoms at the interface. Interface sliding facilitated by misfit dislocation motion is found to facilitate deformation extending into the bulk lattices centered on misfit nodes. The depth of penetration of those fields is found to be greater for Ni/Cu than for Cu/Ag. The study of dislocation plasticity mediated by semi-coherent interfaces can aid in the design of certain heterostructured materials, such as nanolaminates. The evolution of interface misfit patterns under complex stress fields arising from dislocation pileups can influence local dislocation/interface interactions, including effects of multiple incoming dislocations. This work utilizes the Concurrent Atomistic-Continuum modeling framework to probe the evolution of misfit structures at semi-coherent Ni/Cu and Cu/Ag interfaces impinged by dislocation pileups generated via nanoindentation. A continuum microrotation metric is computed at various stages of the indentation process and used to visualize the evolution of the interface misfit dislocation pattern. The stress state from approaching dislocations induces mixed contraction and expansion of misfit dislocation structures at the interface. A lower number of misfit nodes per unit interface area coincides with greater localized deformation with regard to atoms near misfit nodes for Ni/Cu. The decreased misfit node spacing for Cu/Ag alternatively distributes the restructuring associated with plastic deformation over a larger percentage of atoms at the interface. Interface sliding facilitated by misfit dislocation motion is found to facilitate deformation extending into the bulk lattices centered on misfit nodes. The depth of penetration of those fields is found to be greater for Ni/Cu than for Cu/Ag. read less M. Wagih, P. M. Larsen, and C. Schuh, “Learning grain boundary segregation energy spectra in polycrystals,” Nature Communications. 2020. link Times cited: 62 Z. Mao et al., “The Obstruction Effect of Ni Layer on the Interdiffusion of Cu Substrate and Sn Solder: A Theoretical Investigation,” Journal of Electronic Materials. 2020. link Times cited: 6 M. M. Rahman, M. Islam, and N. Anjum, “Investigation on mechanical behaviors of Cu-Ni binary alloy nanopillars: a molecular dynamics study,” Journal of Molecular Modeling. 2020. link Times cited: 3 Y.-C. Hu, K. Zhang, S. A. Kube, J. Schroers, M. Shattuck, and C. O’Hern, “Glass formation in binary alloys with different atomic symmetries,” arXiv: Materials Science. 2020. link Times cited: 4 Abstract: Prediction of the glass forming ability (GFA) of alloys rema… read more Abstract: Prediction of the glass forming ability (GFA) of alloys remains a major challenge. We are not able to predict the composition dependence of the GFA of even binary alloys. To investigate the effect of each element's propensity to form particular crystal structures on glass formation, we focus on binary alloys composed of elements with the same size, but different atomic symmetries using the patchy-particle model. For mixtures with atomic symmetries that promote different crystal structures, the minimum critical cooling rate $R_c$ is only a factor of $5$ lower than that for the pure substances. For mixtures with different atomic symmetries that promote local crystalline and icosahedral order, the minimum $R_c$ is more than $3$ orders of magnitude lower than that for pure substances. Results for $R_c$ for the patchy-particle model are in agreement with those from embedded atom method simulations and sputtering experiments of NiCu, TiAl, and high entropy alloys. read less S. Mahmoud and N. Mousseau, “Long-time point defect diffusion in ordered nickel-based binary alloys: How small kinetic differences can lead to completely long-time structural evolution,” Materialia. 2018. link Times cited: 15 E. Ilker, M. Madran, M. Konuk, and S. Durukanoğlu, “Growth and shape stability of Cu-Ni core-shell nanoparticles: an atomistic perspective.,” Chemical communications. 2018. link Times cited: 5 Abstract: The growth and shape stability of bi-metallic cubic Cu-Ni na… read more Abstract: The growth and shape stability of bi-metallic cubic Cu-Ni nanoparticles are studied using atomic-level simulations. Cubic nano-crystals coated with an ultra-thin Cu layer can be readily obtained when Ni cubic nanoparticles are used as the seeds. At elevated temperatures, the Cu seed with extending Ni branches preserves its shape compared to the Ni seed with extending Cu branches. read less W. Nöhring and W. Curtin, “Cross-slip of long dislocations in FCC solid solutions,” Acta Materialia. 2018. link Times cited: 37 C. Wu, T. Fang, Y.-J. Lin, and Y.-D. Jie, “Nanowelding of nickel and copper investigated using quasi-continuum simulations,” Multiscale and Multidisciplinary Modeling, Experiments and Design. 2018. link Times cited: 1 X. Liu, H. Zhang, and X. Cheng, “Effect of nickel segregation on CuΣ9 grain boundary undergone shear deformations,” Chinese Physics B. 2018. link Times cited: 3 Abstract: Impurity segregation at grain boundary (GB) can significantl… read more Abstract: Impurity segregation at grain boundary (GB) can significantly affect the mechanical behaviors of polycrystalline metal. The effect of nickel impurity segregated at Cu GB on the deformation mechanism relating to loading direction is comprehensively studied by atomic simulation. The atomic structures and shear responses of Cu Σ9(114) 110 and Σ9(221) 110 symmetrical tilt grain boundary with different quantities of nickel segregation are analyzed. The results show that multiple accommodative evolutions involving GB gliding, GB shear-coupling migration, and dislocation gliding can be at play, where for the shear of Σ9(114) 110 the segregated GBs tend to maintain their initial configurations and a segregated GB with a higher impurity concentration is more inclined to be a dislocation emission source while maintaining the high mechanical strength undergone plastic deformation for the shear of Σ9(221) 110. It is found that the nickel segregated GB exerts a cohesion enhancement effect on Cu under deformation: strong nickel segregation increases the work of separation of GB, which is proved by the first-principles calculations. read less T. Swinburne, “Coarse-Graining and Forecasting Atomic Material Simulations with Descriptors,” Physical Review Letters. 2023. link Times cited: 0 E. Ilker, M. Konuk, M. Madran, M. Gökçen, İ. Göksal, and S. Durukanoğlu, “The role of atomistic processes in growth of Cu–Ni metallic/bimetallic nanoparticles,” Computational Materials Science. 2023. link Times cited: 0 A. Kartamyshev, A. Lipnitskii, V. Maksimenko, A. V. Vyazmin, I. Nelasov, and D. Poletaev, “N-body potential for simulating lattice defects and diffusion in copper,” Computational Materials Science. 2023. link Times cited: 1 Y.-chun Liu, Y.-chao Liang, L.-li Zhou, T. Gao, Q. Chen, and Z. Tian, “Strengthening mechanism of Ni–Cu nanotwins with void under different tensile directions based on Molecular Dynamics simulation,” Physica B: Condensed Matter. 2023. link Times cited: 0 B. Yao, Z. R. Liu, D. Legut, and R. F. Zhang, “Hybrid potential model with high feasibility and flexibility for metallic and covalent solids,” Physical Review B. 2023. link Times cited: 0 Z. Zhang and C. Deng, “Solid solution softening in single crystalline metal nanowires studied by atomistic simulations,” Physical Review Materials. 2023. link Times cited: 0 S. Dong, X.-Y. Liu, Y. Chen, and C. Zhou, “Atomistic analysis of plastic deformation and shear band formation in FCC/FCC metallic nanolayered composites,” Journal of Materials Research. 2023. link Times cited: 1 Abstract: Atomistic simulations were used to explore the plastic defor… read more Abstract: Atomistic simulations were used to explore the plastic deformation and shear band (SB) formation in Cu/Au, Cu/Ag, Cu/Al and Cu/Ni metallic nanolayered composites (MNCs). The analysis reveals that interface dislocation structures in all four MNCs are composed of three sets of edge Shockley partial dislocations. Under external loading, dislocations firstly nucleated from the phase with lower stacking fault energy (SFE) in FCC/FCC MNCs. The SBs formed in Cu/Au and Cu/Ag MNCs and the onset strain of SB increases with the increasing layer thicknesses. While in Cu/Al and Cu/Ni MNCs, the deformation is relatively uniform and each slip plane contains similar amounts of dislocations. The formation of SBs in Cu/Au and Cu/Ag MNCs is induced by the nucleation and growth of deformation twinning in the phase with low SFE. After the formation of SBs, the interface sliding accommodates most plastic strains during the deformation. Graphical abstract read less M. Jain et al., “Strengthening of 3D printed Cu micropillar in Cu-Ni core-shell structure,” Materials & Design. 2023. link Times cited: 2 Y. Tian, F. Chen, Z. Cui, and X. Tian, “Effects of atomic size misfit on dislocation mobility in FCC dense solid solution: Atomic simulations and phenomenological modeling,” International Journal of Plasticity. 2022. link Times cited: 4 A. Abu-Odeh, T. Allaparti, and M. Asta, “Structure and glide of Lomer and Lomer-Cottrell dislocations: Atomistic simulations for model concentrated alloy solid solutions,” Physical Review Materials. 2022. link Times cited: 0 S. Lian, J. Wang, H. Swart, and J. J. Terblans, “Molecular dynamics simulation and thermodynamics calculation on surface segregation in Ni-Cu nano-films under stress,” Physica Scripta. 2022. link Times cited: 0 Abstract: The surface segregation of Cu atoms in a Ni-Cu system was in… read more Abstract: The surface segregation of Cu atoms in a Ni-Cu system was investigated using molecular dynamics simulations. Thermodynamic calculations were performed to verify the results of the molecular dynamics simulations. For the thermodynamic calculations, a model for evaluating the influence of stress on surface segregation was developed using the modified Darken model in combination with the broken-bond model. Using molecular dynamics simulations, it was found that the enrichment of Cu atoms occurred for a free-standing Ni-10 at.% Cu film consisting of 20 layers. Simultaneously, the stress distribution across the Ni-Cu thin film is obtained. The thermodynamic calculation results show that the influence of stress on the surface segregation cannot be ignored because of the considerable surface stress. Surface tension stress promotes the surface segregation of copper in Cu-Ni alloys due to the larger lattice parameter of copper than nickel, which leads to the reduction of surface strain energy. When the thickness is greater than 31 nm (or the number of layers exceeds 89), the size effect disappears, i.e., the surface concentration doesn’t increase with the increase of thickness. The calculation results obtained by the Bragg-William equation used for the surface segregation in equilibrium are in good agreement with the thermodynamic calculation and molecular dynamics simulation results. read less T.-N. Vu, V.-T. Pham, and T. Fang, “Deformation mechanisms and mechanical properties of nanocrystalline CuxNi100-x alloys during indentation using molecular dynamics,” Materials Today Communications. 2022. link Times cited: 9 A. Selimov, K. Chu, and D. McDowell, “Effects of interdiffusion on shear response of semi-coherent 111 interfaces in Ni/Cu,” International Journal of Plasticity. 2022. link Times cited: 3 M. Settem, P. Kumar, I. Adlakha, and A. Kanjarla, “Surface reconstruction in core@shell nanoalloys: interplay between size and strain,” Acta Materialia. 2022. link Times cited: 3 Y. Wang, K. Niu, L. Wang, and W. Xia, “A molecular dynamics study of mechanical properties of bioinspired functionally graded Cu-Ni alloy,” Molecular Simulation. 2022. link Times cited: 2 Abstract: ABSTRACT Inspired from natural materials, functionally grade… read more Abstract: ABSTRACT Inspired from natural materials, functionally graded materials (FGMs) with gradual variations in their compositions and microstructures have drawn considerable attention in structural materials design to achieve superior stiffness, strength, and toughness. Taking Cu-Ni alloy as a representative model system, herein, we systematically explore the mechanical properties of Cu-Ni FGMs with varying Ni distributions and Ni contents, respectively, where the lattice constant of Cu-Ni FGMs is found to decrease with increasing Ni content. By carrying out uniaxial tension and compression, it is observed that Young’s modulus of Cu-Ni FGMs is nearly independent of the atomic distribution profile but sensitive to the Ni content. Yield stress also shows the strong dependency of Ni content; under the same Ni content, however, due to the sharpness of the interface and different deformation mechanisms, the yield stress becomes sensitive to the Ni distribution. Remarkably, there exists a tension-compression (T-C) asymmetry in Cu-Ni FGMs – the T-C asymmetry of yield stress is more heavily influenced by Ni distribution and content compared to Young’s modulus. Our study provides fundamental insights into the mechanical response of Cu-Ni FGMs with varying Ni distribution profiles and contents from an atomic perspective, aiding in the computational design of FGMs. read less C. Kondur and K. Stephani, “A semi-classical phonon-induced desorption model for carbon surfaces,” AIAA SCITECH 2022 Forum. 2022. link Times cited: 0 I. Bryukhanov and V. Emelyanov, “Shear stress relaxation through the motion of edge dislocations in Cu and Cu–Ni solid solution: A molecular dynamics and discrete dislocation study,” Computational Materials Science. 2022. link Times cited: 8 S. Wei et al., “Molecular dynamics simulation of compression induced phase transformation in Cu1Ni3 alloy,” Ferroelectrics. 2021. link Times cited: 0 Abstract: The phase transformation mechanism and transformation path o… read more Abstract: The phase transformation mechanism and transformation path of Cu-Ni alloys is very important to study for their applications in excellent electrical properties and chemical catalysis. In this paper, the effect of compressive strain on the transformation path and mechanism of Cu1Ni3 alloy is studied by molecular dynamics simulations. The simulation results reveal that the transformation path of alloys is from Fcc-Bcc-Hcp phase to other phase (amorphous state). The simulations not only revealed the processes of atomic displacements and pair correlation function during the transformation, but also elucidated the underlying mechanism of the transformation at the atomic level. The mechanism of phase transformation could be the lattice reconstruction caused by lattice sliding and stretching. The simulation results provide a clear landscape on the transformation mechanism, facilitating our comprehensive understanding on the phase transition in the Cu-Ni system. read less X. Shen, B. Yao, Z. R. Liu, D. Legut, H. J. Zhang, and R. Zhang, “Mechanistic insights into interface-facilitated dislocation nucleation and phase transformation at semicoherent bimetal interfaces,” International Journal of Plasticity. 2021. link Times cited: 11 B. Yao, Z. Liu, and R. Zhang, “EAPOTs: An integrated empirical interatomic potential optimization platform for single elemental solids,” Computational Materials Science. 2021. link Times cited: 3 B. Yao et al., “Cooperative roles of stacking fault energies on dislocation nucleation at bimetal interface through tunable potentials,” Computational Materials Science. 2021. link Times cited: 5 M. Rahman, E. Chowdhury, and S. Hong, “Nature of creep deformation in nanocrystalline cupronickel alloy: A Molecular Dynamics study.” 2021. link Times cited: 10 A. Galashev, K. Ivanichkina, A. Vorob’ev, O. Rakhmanova, K. Katin, and M. Maslov, “Improved lithium-ion batteries and their communication with hydrogen power,” International Journal of Hydrogen Energy. 2021. link Times cited: 9 I. Bryukhanov, “Dynamics of edge dislocation in Cu–Ni solid solution alloys at atomic scale,” International Journal of Plasticity. 2020. link Times cited: 25 J. Li, H.-W. Chen, Q. Fang, C. Jiang, Y. Liu, and P. Liaw, “Unraveling the dislocation–precipitate interactions in high-entropy alloys,” International Journal of Plasticity. 2020. link Times cited: 68 N. Kaur, C. Deng, and O. Ojo, “Effect of solute segregation on diffusion induced grain boundary migration studied by molecular dynamics simulations,” Computational Materials Science. 2020. link Times cited: 12 Z. R. Liu et al., “Mechanistic understanding of the size effect on shock facilitated dislocation nucleation at semicoherent interfaces,” Scripta Materialia. 2020. link Times cited: 9 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 Y. Yang et al., “Cooperative Atom Motion in Ni–Cu Nanoparticles during the Structural Evolution and the Implication in the High-Temperature Catalyst Design,” ACS Applied Energy Materials. 2019. link Times cited: 15 Abstract: Bimetallic nanoparticles (NPs) are widely used in catalysis … read more Abstract: Bimetallic nanoparticles (NPs) are widely used in catalysis for a wide range of applications. Like other catalysts, their catalytic performance may also degrade during reactions. The structural evolution and the interfacial segregation of one constituting element are among the many degradation mechanisms. Understanding the atomic motions during this dynamics process promises to serve as a reference in designing a better catalyst. In this work, we used molecular dynamics simulation to examine the interfacial dynamics during the surface enrichment of Cu in an ∼4 nm Ni–Cu bimetallic NP. The Ni/Cu ratio on the surface after segregation was quantified and plotted as a function of the nominal composition in the bulk. Interestingly, the “outward” migration of Cu atoms and the “inward” migration of Ni were not all independent; rather, it showed the simultaneous motion by consecutive atoms along a string. Such collective motion comprised of two elements facilitated the surface segregation, intensified the shape re... read less J. Méndez and M. Ponga, “MXE: A package for simulating long-term diffusive mass transport phenomena in nanoscale systems,” Comput. Phys. Commun. 2019. link Times cited: 8 F. Fischer, G. Schmitz, and S. Eich, “A systematic study of grain boundary segregation and grain boundary formation energy using a new copper–nickel embedded-atom potential,” Acta Materialia. 2019. link Times cited: 32 F. Fischer, G. Schmitz, and S. Eich, “A Systematic Study of Grain Boundary Segregation and Grain Boundary Formation Energy Using a New Copper-Nickel Embedded-Atom Potential,” Computational Materials Science eJournal. 2019. link Times cited: 0 Abstract: In this atomistic study on the copper–nickel system, a new e… read more Abstract: In this atomistic study on the copper–nickel system, a new embedded-atom alloy potential between copper and nickel is fitted to experimental data on the mixing enthalpy, taking available potentials for the pure components from literature. The resulting phase boundaries of the new potential are in very good agreement with a recent CALPHAD prediction. Using this new potential, a high angle symmetrical tiltΣ5 and a coherent Σ3 twin grain boundary (GB) are chosen for a systematic investigation of equilibriumGB segregation in the semi-grandcanonical ensemble at temperatures from 400 K to 800 K. Applying thermodynamically accurate integration techniques, the GB formation energies are calculated exactly and as an absolute value for every temperature and composition, which also enables the evaluation of GB excess entropies. The thorough thermodynamic model of GBs developed by Frolov and Mishin is excellently confirmed by the simulations quantitatively, if the impact of both segregation and GB tension on the change in GB formation energy is accounted for. In the case of the Σ3 coherent GB, it turns out that the change in GB formation energy at low temperatures is for the most part attributed to the GB tension, while segregation only has a small influence. This demonstrated effect of GB tensions should also be taken into account in the interpretation of experiments. read less M. Dodaran, J. Wang, Y. Chen, W. Meng, and S. Shao, “Energetic, Structural and Mechanical Properties of Terraced Interfaces,” MatSciRN: Other Computational Materials Science (Topic). 2019. link Times cited: 14 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 Y. Long, B. He, W. Cui, X. Zhuang, and J. Twiefel, “Molecular Dynamics Simulation of Microwelds Formation and Breakage During Ultrasonic Copper Wire Bonding,” 2018 IEEE 68th Electronic Components and Technology Conference (ECTC). 2018. link Times cited: 3 Abstract: Nowadays ultrasonic (US) copper wire bonding gests more requ… read more Abstract: Nowadays ultrasonic (US) copper wire bonding gests more required and applied in power electronics. Despite its large amounts of usage, the underlying bonding mechanisms are still unclear. Among them, the dynamic changes of microwelds are essential to the bonding process as the bonding quality and reliability are greatly influenced by the formed microwelds. In this work, the formation and breakage of microwelds during US copper wire bonding are analyzed by molecular dynamics simulation. Due to the limit of the computational expense, a small local interface consisting of ~40000 atoms is simulated. In the model, the copper substrate is fixed while the movement of the copper wire is imposed. Microwelds are first formed during the downwards moving of the wire and get enlarged with further vertical displacement. The formed microwelds can be broken due to the vibration while new microwelds can be formed in the meantime. Because of the formation, deformation and breakage of the microwelds, the surface roughness can be significantly changed and the vertical displacement is the most influential factor. Defects caused by the microwelds formation and breakage can be clearly observed in the simulation results. The achieved information has a high potential to enhance the bonding quality and reliability. read less D. Kryzhevich, K. Zolnikov, A. Korchuganov, and S. Psakhie, “Structure of bicomponent particles synthesized from colliding metal clusters.” 2017. link Times cited: 0 M. Kozłowski, D. Scopece, J. Janczak-Rusch, L. Jeurgens, R. Abdank-Kozubski, and D. Passerone, “Validation of an Embedded-Atom Copper Classical Potential via Bulk and Nanostructure Simulations,” Diffusion Foundations. 2017. link Times cited: 0 Abstract: The validation of classical potentials for describing multic… read more Abstract: The validation of classical potentials for describing multicomponent materials in complex geometries and their high temperature structural modifications (disordering and melting) requires to verify both a faithful description of the individual phases and a convincing scheme for the mixed interactions, like it is the case of the embedded atom scheme. The present paper addresses the former task for an embedded atom potential for copper, namely the widely adopted parametrization by Zhou, through application to bulk, surface and nanocluster systems. It is found that the melting point is underestimated by 200 degrees with respect to experiment, but structural and temperature-dependent properties are otherwise faithfully reproduced. read less K. Duan, L. Li, Y. Hu, and X. Wang, “Enhanced interfacial strength of carbon nanotube/copper nanocomposites via Ni-coating: Molecular-dynamics insights,” Physica E-low-dimensional Systems & Nanostructures. 2017. link Times cited: 31 A. Dmitriev, A. Nikonov, and W. Österle, “Molecular dynamics sliding simulations of amorphous Ni, Ni-P and nanocrystalline Ni films,” Computational Materials Science. 2017. link Times cited: 35 I. Bustamante-Romero, O. D. L. Pena-Seaman, R. Heid, and K. Bohnen, “Effect of magnetism on lattice dynamical properties in the Ni–Cu alloy from first principles,” Journal of Magnetism and Magnetic Materials. 2016. link Times cited: 4 D. Kryzhevich, A. Korchuganov, K. Zolnikov, and S. Psakhie, “Plastic deformation nucleation in elastically loaded CuNi alloy during nanoindentation.” 2016. link Times cited: 0 Abstract: The molecular dynamics simulation of the behavior of elastic… read more Abstract: The molecular dynamics simulation of the behavior of elastically loaded CuNi alloy at nanoindentation is carried out. It is shown that the stoichiometric composition and the preliminary elastic deformation influence characteristics of the nucleation of plastic deformation. Under tension of specimens with a low concentration of nickel, the nucleation of plastic deformation is determined by the formation of stacking faults. The formation of nanotwins makes a significant contribution to the nucleation of plasticity at high concentrations of nickel. The increase of the degree of preliminary elastic deformation of the crystallites leads to a decrease in the depth of indentation at which structural defects start to form. read less T. Fu et al., “Molecular dynamics simulation of nanoindentation on Cu/Ni nanotwinned multilayer films using a spherical indenter,” Scientific Reports. 2016. link Times cited: 118 S. M. Rassoulinejad-Mousavi, Y. Mao, and Y. Zhang, “Evaluation of Copper, Aluminum and Nickel Interatomic Potentials on Predicting the Elastic Properties,” arXiv: Computational Physics. 2016. link Times cited: 63 Abstract: Choice of appropriate force field is one of the main concern… read more Abstract: Choice of appropriate force field is one of the main concerns of any atomistic simulation that needs to be seriously considered in order to yield reliable results. Since, investigations on mechanical behavior of materials at micro/nanoscale has been becoming much more widespread, it is necessary to determine an adequate potential which accurately models the interaction of the atoms for desired applications. In this framework, reliability of multiple embedded atom method based interatomic potentials for predicting the elastic properties was investigated. Assessments were carried out for different copper, aluminum and nickel interatomic potentials at room temperature which is considered as the most applicable case. Examined force fields for the three species were taken from online repositories of National Institute of Standards and Technology (NIST), as well as the Sandia National Laboratories, the LAMMPS database. Using molecular dynamic simulations, the three independent elastic constants, C11, C12 and C44 were found for Cu, Al and Ni cubic single crystals. Voigt-Reuss-Hill approximation was then implemented to convert elastic constants of the single crystals into isotropic polycrystalline elastic moduli including Bulk, Shear and Young's modulus as well as Poisson's ratio. Simulation results from massive molecular dynamic were compared with available experimental data in the literature to justify the robustness of each potential for each species. Eventually, accurate interatomic potentials have been recommended for finding each of the elastic properties of the pure species. Exactitude of the elastic properties was found to be sensitive to the choice of the force fields. Those potentials were fitted for a specific compound may not necessarily work accurately for all the existing pure species. read less M. Zaenudin, Kasum, A. Gamayel, and M. N. Mohammed, “Molecular dynamics simulation on the effect of grading function on mechanical properties of Cu-Ni functionally graded material alloy,” THE 11TH INTERNATIONAL CONFERENCE ON THEORETICAL AND APPLIED PHYSICS: The Spirit of Research and Collaboration Facing the COVID-19 Pandemic. 2023. link Times cited: 0 A. Nikonov, A. Dmitriev, and A. Smolin, “Selection of the potential for MD-modeling of phase martensitic transformations in Al-Cu-Ni alloy,” PROCEEDINGS OF THE INTERNATIONAL CONFERENCE “PHYSICAL MESOMECHANICS. MATERIALS WITH MULTILEVEL HIERARCHICAL STRUCTURE AND INTELLIGENT MANUFACTURING TECHNOLOGY.” 2022. link Times cited: 1 Y. Wang, J. Zuo, N. Jiang, K. Niu, and Y. Wu, “Uniaxial tension deformation study of copper/nickel laminated composites: Effects of lamella number and interlamellar spacing,” Computational Materials Science. 2020. link Times cited: 10 A. Esfandiarpour and M. N. Nasrabadi, “Investigation of the effect of composing elements of CuNiCoFeV high entropy alloy on thermal-elastic properties: An ab initio study,” Intermetallics. 2019. link Times cited: 8 W. Nöhring, “Dislocation Cross-Slip in Face-Centered Cubic Solid Solution Alloys.” 2018. link Times cited: 2 Abstract: The mechanical strength of metals depends on their resistanc… read more Abstract: The mechanical strength of metals depends on their resistance against various microscopic deformation processes. In ductile metals, the most important process is shearing of the crystal lattice by dislocations. One of the fundamental aspects of dislocation motion is cross-slip of screw dislocations, the process by which they change their glide plane. In Face-Centered Cubic (FCC) metals, cross-slip is supposed to play a role in dislocation structuring, work hardening, recovery, fatigue, etc. Most prior studies on cross-slip in FCC metals focused on pure metals. There have been few studies of solute effects on cross-slip, which are important for engineering alloys. Here, the effects of substitutional solutes are studied using atomistic simulations and statistical modeling. In the first part of the thesis, the mechanism and energy of cross-slip of short (40 Burgers vectors long) dislocations in Ni-Al, Al-Mg and Cu-Ni alloys are determined using atomistic calculations. These calculations are carried out with real random alloys and with “average” alloys, where the real atom types are replaced by a single average type. By comparison, it is shown that cross-slip is controlled by fluctuations in the solute concentration, i.e. the activation energy for cross-slip is a distributed variable with a large variance around the mean value. The latter changes only little with concentration. Most importantly, activation energies that are significantly lower than the mean value can be observed in random alloys. A linear correlation between the activation energy and the energy difference between the state of the dislocation before and after cross-slip is observed. An analytical, parameter-free model of this energy difference is developed, which takes random changes in solute-dislocation and solute-solute binding energies into account. Thus, it is possible to predict the distribution of activation energies for nucleation of cross-slip. In the second part, cross-slip of long (102–103 Burgers vectors) dislocations is studied using a random walk model. Cross-slip is seen as a discrete process, where one Burgers vector long subsegments of the dislocation cross-slip one after another. Associated with each step is a random energy due to random changes in solute binding energies, as well as a deterministic energy change due to constriction formation and stress effects. The random walk model allows the calculation of the activation energy distribution for arbitrary dislocation lengths and stresses. Cross-slip of long dislocations is unlikely at zero stress, due to increasing frequency of high activation energies with increasing length. However, an external stress eliminates these high barriers. Cross-slip then becomes a weakest-link problem. Like in the case of short dislocations, activation energies that are significantly lower than average-alloy estimates can be observed in real random alloys. read less D. Kryzhevich, K. Zolnikov, A. Korchuganov, and S. Psakhie, “Nanopowder synthesis based on electric explosion technology.” 2017. link Times cited: 2 A. Hernandez and T. Mueller, “Generalizability of Functional Forms for Interatomic Potential Models Discovered by Symbolic Regression,” ArXiv. 2022. link Times cited: 0 Abstract: In recent years there has been great progress in the use of … read more Abstract: In recent years there has been great progress in the use of machine learning algorithms to develop interatomic potential models. Machine-learned potential models are typically orders of magnitude faster than density functional theory but also orders of magnitude slower than physics-derived models such as the embedded atom method. In our previous work, we used symbolic regression to develop fast, accurate and transferrable interatomic potential models for copper with novel functional forms that resemble those of the embedded atom method. To determine the extent to which the success of these forms was specific to copper, here we explore the generalizability of these models to other face-centered cubic transition metals and analyze their out-of-sample performance on several material properties. We found that these forms work particularly well on elements that are chemically similar to copper. When compared to optimized Sutton-Chen models, which have similar complexity, the functional forms discovered using symbolic regression perform better across all elements considered except gold where they have a similar performance. They perform similarly to a moderately more complex embedded atom form on properties on which they were trained, and they are more accurate on average on other properties. We attribute this improved generalized accuracy to the relative simplicity of the models discovered using symbolic regression. The genetic programming models are found to outperform other models from the literature about 50% of the time in a variety of property predictions, with about 1/10th the model complexity on average. We discuss the implications of these results to the broader application of symbolic regression to the development of new potentials and highlight how models discovered for one element can be used to seed new searches for different elements. read less B. Yao, Z. R. Liu, and R. F. Zhang, “EAPOTc: An integrated empirical interatomic potential optimization platform for compound solids,” Computational Materials Science. 2022. link Times cited: 1 Z. R. Liu, B. Yao, and R. F. Zhang, “SPaMD studio: An integrated platform for atomistic modeling, simulation, analysis, and visualization,” Computational Materials Science. 2021. link Times cited: 7 K. Moldosanov et al., “Terahertz-to-infrared converters for imaging the human skin cancer: challenges and feasibility,” Journal of Medical Imaging. 2023. link Times cited: 2 Abstract: Abstract. Purpose Terahertz (THz) medical imaging is a promi… read more Abstract: Abstract. Purpose Terahertz (THz) medical imaging is a promising noninvasive technique for monitoring the skin’s conditions, early detection of the human skin cancer, and recovery from burns and wounds. It can be applied for visualization of the healing process directly through clinical dressings and restorative ointments, minimizing the frequency of dressing changes. The THz imaging technique is cost effective, as compared to the magnetic resonance method. Our aim was to develop an approach capable of providing better image resolution than the commercially available THz imaging cameras. Approach The terahertz-to-infrared (THz-to-IR) converters can visualize the human skin cancer by converting the latter’s specific contrast patterns recognizable in THz radiation range into IR patterns, detectable by a standard IR imaging camera. At the core of suggested THz-to-IR converters are flat matrices transparent both in the THz range to be visualized and in the operating range of the IR camera, these matrices contain embedded metal nanoparticles (NPs), which, when irradiated with THz rays, convert the energy of THz photons into heat and become nanosources of IR radiation detectable by an IR camera. Results The ways of creating the simplest converter, as well as a more complex converter with wider capabilities, are considered. The first converter is a gelatin matrix with gold 8.5-nm diameter NPs, and the second is a polystyrene matrix with 2-nm diameter NPs from copper–nickel MONEL® alloy 404. Conclusions An approach with a THz-to-IR converter equipped with an IR camera is promising in that it could provide a better image of oncological pathology than the commercially available THz imaging cameras do. read less L. Xu, L. Casillas-Trujillo, Y. Gao, and H. Xu, “Compositional effects on stacking fault energies in Ni-based alloys using first-principles and atomistic simulations,” Computational Materials Science. 2021. link Times cited: 5 K. Kasum, F. Mulyana, M. Zaenudin, A. Gamayel, and M. Mohammed, “Molecular Dynamics Simulation on Creep Mechanism of Nanocrystalline Cu-Ni Alloy.” 2021. link Times cited: 3 Abstract: Creep mechanism is an essential mechanism for material when … read more Abstract: Creep mechanism is an essential mechanism for material when subjected to a high temperature and high pressure. It shows material ability during an extreme application to maintain its structure and properties, especially high pressure and temperature. This test is already done experimentally in many materials such as metallic alloys, various stainless steel, and composites. However, understanding the creep mechanism at the atomic level is challenging due to the instruments limitation. Still, the improvement of mechanical properties is expected can be done in such a group. In this work, the creep mechanism of the nanocrystalline Cu-Ni alloy is demonstrated in terms of molecular dynamics simulation. The result shows a significant impact on both temperature and pressure. The deformation supports the mechanisms as a result of the grain boundary diffusion. Quantitative analysis shows a more substantial difference in creep-rate at a higher temperature and pressure parameters. This study has successfully demonstrated the mechanism of creep at the atomic scale and may be used for improving the mechanical properties of the material. read less J. Alberdi-Rodriguez, S. Acharya, T. Rahman, A. Arnau, and M. Gosálvez, “Dominant contributions to the apparent activation energy in two-dimensional submonolayer growth: comparison between Cu/Ni(111) and Ni/Cu(111),” Journal of Physics: Condensed Matter. 2020. link Times cited: 0 Abstract: For surface-mediated processes in general, such as epitaxial… read more Abstract: For surface-mediated processes in general, such as epitaxial growth and heterogeneous catalysis, a constant slope in the Arrhenius diagram of the rate of interest, R, against inverse temperature, log R vs 1/T, is traditionally interpreted as the existence of a bottleneck elementary reaction (or rate-determining step), whereby the constant slope (or apparent activation energy, EappR) reflects the value of the energy barrier for that elementary reaction. In this study, we express EappR as a weighted average, where every term contains the traditional energy barrier for the corresponding elementary reaction plus an additional configurational term, while identifying each weight as the probability of executing the corresponding elementary reaction. Accordingly, the change in the leading (most probable) elementary reaction with the experimental conditions (e.g. temperature) is automatically captured and it is shown that a constant value of EappR is possible even if control shifts from one elementary reaction to another. To aid the presentation, we consider kinetic Monte Carlo simulations of submonolayer growth of Cu on Ni(111) and Ni on Cu(111) at constant deposition flux, including a large variety of single-atom, multi-atom and complete-island diffusion events. In addition to analysing the dominant contributions to the diffusion constant of the complete adparticle system (or tracer diffusivity) and its apparent activation energy as a function of both coverage and temperature for the two heteroepitaxial systems, their surface morphologies and island densities are also compared. read less A. Markidonov, M. Starostenkov, P. Zakharov, D. Lubyanoi, and V. N. Lipunov, “Emission of Dislocation Loops from Nanovoids in an FCC Crystal Subjected to Shear Deformation under Post-Cascade Shock Waves,” Journal of Experimental and Theoretical Physics. 2019. link Times cited: 3 M. Islam, M. S. H. Thakur, S. Mojumder, A. A. Amin, and M. M. Islam, “Mechanical and vibrational characteristics of functionally graded Cu–Ni nanowire: A molecular dynamics study,” Composites Part B-engineering. 2019. link Times cited: 27 C. Wu, T. Fang, and Y.-J. Lin, “Quasi-continuum simulations of side-to-side nanowelding of metals,” Journal of Molecular Modeling. 2018. link Times cited: 2 Q. Zhang et al., “Microstructure and nanoindentation behavior of Cu composites reinforced with graphene nanoplatelets by electroless co-deposition technique,” Scientific Reports. 2017. link Times cited: 54 W. Nöhring and W. Curtin, “Dislocation cross-slip in fcc solid solution alloys,” Acta Materialia. 2017. link Times cited: 65 H. Mu, B. Xu, C. Ouyang, and X. Lei, “Highly optimized embedding atom method potential for Pt-Cu alloys,” Journal of Alloys and Compounds. 2017. link Times cited: 6 B. Onat and S. Durukanoğlu, “The role of vibrations in thermodynamic properties of Cu-Ni alloys,” The European Physical Journal B. 2014. link Times cited: 8 C. Galvin, R. Grimes, and P. Burr, “A molecular dynamics method to identify the liquidus and solidus in a binary phase diagram,” Computational Materials Science. 2021. link Times cited: 6 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 “Fast, accurate, and transferable many-body interatomic potentials by genetic programming,” ArXiv. 2019. link Times cited: 0 Abstract: The length and time scales of atomistic simulations are limi… read more Abstract: The length and time scales of atomistic simulations are limited by the computational cost of the methods used to predict material properties. In recent years there has been great progress in the use of machine learning algorithms to develop fast and accurate interatomic potential models, but it remains a challenge to develop models that generalize well and are fast enough to be used at extreme time and length scales. To address this challenge, we have developed a machine learning algorithm based on genetic programming that is capable of discovering accurate, computationally efficient many-body potential models. The key to our approach is to explore a hypothesis space of models based on fundamental physical principles and select models within this hypothesis space based on their accuracy, speed, and simplicity. The focus on simplicity reduces the risk of overfitting the training data and increases the chances of discovering a model that generalizes well. Our algorithm was validated by rediscovering an exact Lennard Jones potential and a Sutton Chen embedded atom method potential from training data generated using these models. By using training data generated from density functional theory calculations, we found potential models for elemental copper that are simple, as fast as embedded atom models, and capable of accurately predicting properties outside of their training set. Our approach requires relatively small sets of training data, making it possible to generate training data using highly accurate methods at a reasonable computational cost. We present our approach, the forms of the discovered models, and assessments of their transferability, accuracy and speed. read less
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_592013496703_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_OnatDurukanoglu_2014_CuNi__MO_592013496703_005
DOI	10.25950/e2733dc9 https://doi.org/10.25950/e2733dc9 https://commons.datacite.org/doi.org/10.25950/e2733dc9
KIM Item Type Specifies whether this is a Portable Model (software implementation of an interatomic model); Portable Model with parameter file (parameter file to be read in by a Model Driver); Model Driver (software implementation of an interatomic model that reads in parameters).	Portable Model using Model Driver EAM_Dynamo__MD_120291908751_005
Driver	EAM_Dynamo__MD_120291908751_005
KIM API Version	2.0
Potential Type	eam

Previous Version	EAM_Dynamo_OnatDurukanoglu_2014_CuNi__MO_592013496703_004

Verification Check Dashboard

(Click here to learn more about Verification Checks)

Grade	Name	Category	Brief Description	Full Results	Aux File(s)
P All elements claimed by model are supported in at least one of the tested configurations.	vc-species-supported-as-stated	mandatory	The model supports all species it claims to support; see full description.	Results	Files
P Periodic boundary conditions were correctly supported for all configurations that the model was able to compute.	vc-periodicity-support	mandatory	Periodic boundary conditions are handled correctly; see full description.	Results	Files
P Model energy has permutation symmetry for all configurations the model was able to compute.	vc-permutation-symmetry	mandatory	Total energy and forces are unchanged when swapping atoms of the same species; see full description.	Results	Files
A The letter grade A was assigned because the normalized error in the computation was 3.84639e-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: Cu

Species: Ni

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: Ni

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: 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: Ni

Species: Cu

FCC Surface Energies

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

Species: Cu

Species: 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

Disclaimer From Model Developer

This potential is tabulated using more spline points to provide smoother cutoff and better accuracy for simulations.

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	12074
Cohesive energy versus lattice constant curve for bcc Ni v004	view	11876
Cohesive energy versus lattice constant curve for diamond Cu v004	view	12134
Cohesive energy versus lattice constant curve for diamond Ni v004	view	11866
Cohesive energy versus lattice constant curve for fcc Cu v004	view	11816
Cohesive energy versus lattice constant curve for fcc Ni v004	view	18785
Cohesive energy versus lattice constant curve for sc Cu v004	view	15952
Cohesive energy versus lattice constant curve for sc Ni v004	view	22065

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	6846
Elastic constants for bcc Ni at zero temperature v006	view	5918
Elastic constants for fcc Cu at zero temperature v006	view	1887
Elastic constants for fcc Ni at zero temperature v006	view	2431
Elastic constants for sc Cu at zero temperature v006	view	1823
Elastic constants for sc Ni at zero temperature v006	view	1887

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	1592
Elastic constants for hcp Ni at zero temperature v004		view	2006

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	83338
Equilibrium crystal structure and energy for Cu in AFLOW crystal prototype A_cI2_229_a v001		view	78406

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	56811
Equilibrium crystal structure and energy for Ni in AFLOW crystal prototype A_cI2_229_a v002	view	55352
Equilibrium crystal structure and energy for Ni in AFLOW crystal prototype A_hP2_194_c v002	view	62209

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	7457262
Relaxed energy as a function of tilt angle for a 100 symmetric tilt grain boundary in fcc Ni v001	view	7710786
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Cu v001	view	23923114
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Ni v001	view	24830418
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Cu v001	view	24394673
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Ni v001	view	24848534
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Cu v001	view	81256165
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Ni v001	view	85027570

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	2335
Equilibrium zero-temperature lattice constant for bcc Ni v007	view	2687
Equilibrium zero-temperature lattice constant for diamond Cu v007	view	3487
Equilibrium zero-temperature lattice constant for diamond Ni v007	view	3391
Equilibrium zero-temperature lattice constant for fcc Cu v007	view	3999
Equilibrium zero-temperature lattice constant for fcc Ni v007	view	3167
Equilibrium zero-temperature lattice constant for sc Cu v007	view	2399
Equilibrium zero-temperature lattice constant for sc Ni v007	view	2463

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	38331
Equilibrium lattice constants for hcp Ni v005		view	32186

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	10602978

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	1327157

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	46480
Phonon dispersion relations for fcc Ni v004		view	50607

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	9463914
Stacking and twinning fault energies for fcc Ni v002		view	8938046

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	31829
Broken-bond fit of high-symmetry surface energies in fcc Ni v004		view	29462

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	482067
Monovacancy formation energy and relaxation volume for fcc Ni		view	564669

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	1891016
Vacancy formation and migration energy for fcc Ni		view	1099964

Errors

ElasticConstantsCubic__TD_011862047401_006

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

No Driver

Verification Check	Error Categories	Link to Error page
MemoryLeak__VC_561022993723_004	other	view

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CuNi_v2.eam.alloy
LICENSE.CDDL
kimprovenance.edn
kimspec.edn

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EAM_Dynamo_OnatDurukanoglu_2014_CuNi__MO_592013496703_005

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BCC Lattice Constant

Cohesive Energy Graph

Diamond Lattice Constant

Dislocation Core Energies

FCC Elastic Constants

FCC Lattice Constant

FCC Stacking Fault Energies

FCC Surface Energies

SC Lattice Constant

Cubic Crystal Basic Properties Table

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