EAM potential (LAMMPS cubic hermite tabulation) for the FeNi system developed by Bonny, Pasianot and Malerba (2009) v005

Giovanni Bonny; Roberto C Pasianot; L. Malerba

doi:10.25950/e54b898a

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EAM_Dynamo_BonnyPasianotMalerba_2009_FeNi__MO_267721408934_005

Interatomic potential for Iron (Fe), Nickel (Ni).
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Title A single sentence description.	EAM potential (LAMMPS cubic hermite tabulation) for the FeNi system developed by Bonny, Pasianot and Malerba (2009) 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.	EAM potential to describe FeNi in the complete concentration range. The main focus was put on the description of experimentally observed intermetallic phases and point defect properties in a dilute Fe-rich matrix. The Fe and Ni potentials were taken from [Mendelev et al., Philos. Mag. 83 (2003) 3977] and [Voter and Chen, Mater. Res. Soc. Symp. Proc. 82 (1987) 175], respectively.
Species The supported atomic species.	Fe, Ni
Disclaimer A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.	The potential was not stiffened to ZBL. The Fe potential is only suitable to describe alpha-Fe.
Content Origin	http://www.ctcms.nist.gov/potentials/Fe.html

Contributor	Giovanni Bonny
Maintainer	Giovanni Bonny
Developer	Giovanni Bonny Roberto C Pasianot L. Malerba
Published on KIM	2018
How to Cite	This Model originally published in [1] is archived in OpenKIM [2-5]. [1] Bonny G, Pasianot RC, Malerba L. Fe–Ni many-body potential for metallurgical applications. Modelling and Simulation in Materials Science and Engineering. 2009;17(2):025010. doi:10.1088/0965-0393/17/2/025010 — (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] Bonny G, Pasianot RC, Malerba L. EAM potential (LAMMPS cubic hermite tabulation) for the FeNi system developed by Bonny, Pasianot and Malerba (2009) v005. OpenKIM; 2018. doi:10.25950/e54b898a [3] Foiles SM, Baskes MI, Daw MS, Plimpton SJ. EAM Model Driver for tabulated potentials with cubic Hermite spline interpolation as used in LAMMPS v005. OpenKIM; 2018. doi:10.25950/68defa36 [4] Tadmor EB, Elliott RS, Sethna JP, Miller RE, Becker CA. The potential of atomistic simulations and the Knowledgebase of Interatomic Models. JOM. 2011;63(7):17. doi:10.1007/s11837-011-0102-6 [5] Elliott RS, Tadmor EB. Knowledgebase of Interatomic Models (KIM) Application Programming Interface (API). OpenKIM; 2011. doi:10.25950/ff8f563a Click here to download the above citation in BibTeX format.
Citations This panel presents information regarding the papers that have cited the interatomic potential (IP) whose page you are on. The OpenKIM machine learning based Deep Citation framework is used to determine whether the citing article actually used the IP in computations (denoted by "USED") or only provides it as a background citation (denoted by "NOT USED"). For more details on Deep Citation and how to work with this panel, click the documentation link at the top of the panel. The word cloud to the right is generated from the abstracts of IP principle source(s) (given below in "How to Cite") and the citing articles that were determined to have used the IP in order to provide users with a quick sense of the types of physical phenomena to which this IP is applied. The bar chart shows the number of articles that cited the IP per year. Each bar is divided into green (articles that USED the IP) and blue (articles that did NOT USE the IP). Users are encouraged to correct Deep Citation errors in determination by clicking the speech icon next to a citing article and providing updated information. This will be integrated into the next Deep Citation learning cycle, which occurs on a regular basis. OpenKIM acknowledges the support of the Allen Institute for AI through the Semantic Scholar project for providing citation information and full text of articles when available, which are used to train the Deep Citation ML algorithm.	This panel provides information on past usage of this interatomic potential (IP) powered by the OpenKIM Deep Citation framework. The word cloud indicates typical applications of the potential. The bar chart shows citations per year of this IP (bars are divided into articles that used the IP (green) and those that did not (blue)). The complete list of articles that cited this IP is provided below along with the Deep Citation determination on usage. See the Deep Citation documentation for more information. 113 Citations (65 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 . V. Turlo and T. Rupert, “Discovery of a Wide Variety of Linear Complexions in Face Centered Cubic Alloys,” MatSciRN: Other Mechanical Properties & Deformation of Materials (Topic). 2019. link Times cited: 1 Abstract: Linear complexions are defect states that have been recently… read more Abstract: Linear complexions are defect states that have been recently discovered along dislocations in body centered cubic Fe-based alloys. In this work, we use atomistic simulations to extend this concept and explore segregation-driven structural transitions at dislocations in face centered cubic alloys. We discovered a variety of stable, nanoscale-size structural and chemical states, which are confined near dislocations and can be classified as linear complexions. Depending on the alloy system and thermodynamic conditions, such new states can preserve, partially modify, or completely replace the original defects they were born at. By considering different temperatures and compositions, we construct linear complexion diagrams that are similar to bulk phase diagrams, defining the important conditions for complexion formation while also specifying an expected complexion size and type. Several notable new complexion types were discovered here: (1) nanoparticle arrays comprised of L12 phases in Ni-Fe, Ni-Al, and Al-Zr, (2) replacement of stacking faults with layered complexions comprised of (111) planes from the Cu5Zr intermetallic phase in Cu-Zr, (3) platelet arrays comprised of two-dimensional Guinier-Preston zones in Al-Cu, and finally (4) coexistence of multiple linear complexions containing both Guinier-Preston zones and L12 phases in ternary Al-Cu-Zr. All of these new complexion states are expected to alter material properties and affect the stability of the dislocations themselves, offering a unique opportunity for future materials design. read less J. Zhang et al., “A Multi-Scale Multi-Physics Modeling Framework of Laser Powder Bed Fusion Additive Manufacturing Process.” 2018. link Times cited: 22 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 R. Khusnutdinoff, R. Khairullina, A. Beltyukov, V. Lad’yanov, and A. Mokshin, “Viscous properties of nickel-containing binary metal melts,” Journal of Physics: Condensed Matter. 2020. link Times cited: 0 Abstract: The paper presents the results of molecular dynamics study o… read more Abstract: The paper presents the results of molecular dynamics study of the viscosity of nickel-containing binary metal melts for a wide range of temperatures, including the region of the equilibrium liquid phase and supercooled melt. It is shown that the temperature dependencies of the viscosity of binary metal melts are described by the Kelton’s quasi-universal model. Based on the analysis of the viscosity coefficient of the binary melt composition within the framework of the Rosenfeld’s scale transformations, it has been established that to correctly describe the viscosity of binary/multicomponent metal melts within the framework of entropy models, it is necessary to use a more complex representation of the excess entropy S ex than in the approximation of pair correlation entropy S 2. read less J. Sublet et al., “Neutron-induced damage simulations: Beyond defect production cross-section, displacement per atom and iron-based metrics,” The European Physical Journal Plus. 2019. link Times cited: 22 A. Hasanzadeh, A. Hamedani, G. Alahyarizadeh, A. Minuchehr, and M. Aghaei, “The role of chromium and nickel on the thermal and mechanical properties of FeNiCr austenitic stainless steels under high pressure and temperature: a molecular dynamics study,” Molecular Simulation. 2019. link Times cited: 8 Abstract: ABSTRACT The effect of Cr and Ni content on thermo-mechanica… read more Abstract: ABSTRACT The effect of Cr and Ni content on thermo-mechanical properties of FeNiCr austenitic stainless steel under ambient and high pressure and temperature were investigated by MD simulations. The FCC structure was selected as optimum structure for FeNiCr system based on obtained MD results from Bonny EAM potential and valid experimental results. The structural and mechanical properties of pure Fe, Ni, and Cr were also estimated based on this potential, indicating good agreement with experimental results. These properties were computed for four experimental case studies which showed less than 10% error. Moreover, the elastic constants of the Fe–(8–18)Ni–(18–25)Cr systems were estimated. Results showed that bulk modulus increases by increasing the Ni and Cr contents, which can be connected to the changes in bonding electrons. The thermal properties of FeNiCr were calculated in ambient and high pressure. Although thermo-mechanical properties confirm good agreement with experimental results at the ambient condition, however, they indicate that FeNiCr Bonny potential is not applicable at high pressure. In order to tackle this issue, a hybrid potential was used at high Pressure/Temperature. The results illustrate enhanced mechanical properties, increase of melting point and reduction of LTE in high pressure and deteriorated mechanical properties at high temperature. read less V. Turlo and T. Rupert, “Linear Complexions: Metastable Phase Formation and Coexistence at Dislocations.,” Physical review letters. 2018. link Times cited: 15 Abstract: The unique three-phase coexistence of metastable B2-FeNi wit… read more Abstract: The unique three-phase coexistence of metastable B2-FeNi with stable L1_{0}-FeNi and L1_{2}-FeNi_{3} is discovered near edge dislocations in body-centered cubic Fe-Ni alloys using atomistic simulations. Stable nanoscale precipitate arrays, formed along the compression side of dislocation lines and defined as linear complexions, were observed for a wide range of compositions and temperatures. By analyzing the thermodynamics associated with these phase transitions, we are able to explain the metastable phase formation and coexistence, in the process defining new research avenues for theoretical and experimental investigations. read less V. Turlo and T. Rupert, “Dislocation-assisted linear complexion formation driven by segregation,” Scripta Materialia. 2018. link Times cited: 12 Y. Zhang, S. Zhao, W. J. Weber, K. Nordlund, F. Granberg, and F. Djurabekova, “Atomic-level heterogeneity and defect dynamics in concentrated solid-solution alloys,” Current Opinion in Solid State & Materials Science. 2017. link Times cited: 142 S. Zhao, Y. Osetsky, and Y. Zhang, “Preferential diffusion in concentrated solid solution alloys: NiFe, NiCo and NiCoCr ☆,” Acta Materialia. 2017. link Times cited: 120 S. Zhao, G. M. Stocks, and Y. Zhang, “Defect energetics of concentrated solid-solution alloys from ab initio calculations: Ni0.5Co0.5, Ni0.5Fe0.5, Ni0.8Fe0.2 and Ni0.8Cr0.2.,” Physical chemistry chemical physics : PCCP. 2016. link Times cited: 81 Abstract: It has been shown that concentrated solid solution alloys po… read more Abstract: It has been shown that concentrated solid solution alloys possess unusual electronic, magnetic, transport, mechanical and radiation-resistant properties that are directly related to underlying chemical complexity. Because every atom experiences a different local atomic environment, the formation and migration energies of vacancies and interstitials in these alloys exhibit a distribution, rather than a single value as in a pure metal or dilute alloy. Using ab initio calculations based on density functional theory and special quasirandom structures, we have characterized the distribution of defect formation energy and migration barrier in four Ni-based solid-solution alloys: Ni0.5Co0.5, Ni0.5Fe0.5, Ni0.8Fe0.2, and Ni0.8Cr0.2. As defect formation energies in finite-size models depend sensitively on the elemental chemical potential, we have developed a computationally efficient method for determining it which takes into account the global composition and the local short-range order. In addition we have compared the results of our ab initio calculations to those obtained from available embedded atom method (EAM) potentials. Our results indicate that the defect formation and migration energies are closely related to the specific atoms in the structure, which further determines the elemental diffusion properties. Different EAM potentials yield different features of defect energetics in concentrated alloys, pointing to the need for additional potential development efforts in order to allow spatial and temporal scale-up of defect and simulations, beyond those accessible to ab initio methods. read less Y. Zhang and J. Zhang, “Sintering phenomena and mechanical strength of nickel based materials in direct metal laser sintering process—a molecular dynamics study,” Journal of Materials Research. 2016. link Times cited: 35 Abstract: This paper presents an atomistic scale model on sintering of… read more Abstract: This paper presents an atomistic scale model on sintering of nickel particles in direct metal laser sintering process. Both sintering phenomena and mechanical strength of sintered particles are simulated using molecular dynamics method. A two-particle atomistic model is developed to investigate the diffusion of atoms during nickel sintering. The diffusion of particle surface is higher than the particle core, with calculated activation energy of nickel particle diffusion 6.10 kJ/mol in the particle core, and 6.24 kJ/mol on the particle surface, which are reasonably in agreement with the experimental data of 7.89 kJ/mol. The sintered model shows a 5-fold twinning structure at 1200 K, and two parallel twin boundaries at 1300 K. The mechanical properties of nickel nanoparticles sintered at various heating rates are investigated using uniaxial tensile test simulations. The results show that higher heating rate during sintering increases the mechanical strength of the sintered material. Deformation mechanism of sintered structures is illustrated from the correlation between stress and dislocation evolution. read less L. Béland, G. Samolyuk, and R. Stoller, “Differences in the accumulation of ion-beam damage in Ni and NiFe explained by atomistic simulations,” Journal of Alloys and Compounds. 2016. link Times cited: 30 K. Vörtler, N. Juslin, N. Juslin, G. Bonny, L. Malerba, and K. Nordlund, “The effect of prolonged irradiation on defect production and ordering in Fe–Cr and Fe–Ni alloys,” Journal of Physics: Condensed Matter. 2011. link Times cited: 54 Abstract: The understanding of the primary radiation damage in Fe-base… read more Abstract: The understanding of the primary radiation damage in Fe-based alloys is of interest for the use of advanced steels in future fusion and fission reactors. In this work Fe–Cr alloys (with 5, 6.25, 10 and 15% Cr content) and Fe–Ni alloys (with 10, 40, 50 and 75% Ni content) were used as model materials for studying the features of steels from a radiation damage perspective. The effect of prolonged irradiation (neglecting diffusion), i.e. the overlapping of single 5 keV displacement cascade events, was studied by molecular dynamics simulation. Up to 200 single cascades were simulated, randomly induced in sequence in one simulation cell, to study the difference between fcc and bcc lattices, as well as initially ordered and random crystals. With increasing numbers of cascades we observed a saturation of Frenkel pairs in the bcc alloys. In fcc Fe–Ni, in contrast, we saw a continuous accumulation of defects: the growth of stacking-fault tetrahedra and a larger number of self-interstitial atom clusters were seen in contrast to bcc alloys. For all simulations the defect clusters and the short range order parameter were analysed in detail depending on the number of cascades in the crystal. We also report the modification of the repulsive part of the Fe–Ni interaction potential, which was needed to study the non-equilibrium processes. read less C. Becker, F. Tavazza, and L. Levine, “Implications of the choice of interatomic potential on calculated planar faults and surface properties in nickel,” Philosophical Magazine. 2011. link Times cited: 15 Abstract: With the increasing use of molecular simulation to understan… read more Abstract: With the increasing use of molecular simulation to understand deformation mechanisms in transition metals, it is important to assess how well the simulations reproduce physical behavior both near equilibrium and under more extreme conditions. In particular, it is important to examine whether simulations predict unusual deformation paths that are competitive with those experimentally observed. In this work we compare generalized planar fault energy landscapes and surface energies for various interatomic potentials with those from density functional theory calculations to examine how well these more complicated planar faults and surface energies are captured and whether any deformations are energetically competitive with the {111}⟨112⟩ slip observed in FCC crystals. To do this we examine not just the (111) fault orientation, but also the (100), (110), (210), (211), (311), and (331) orientations to test behavior outside of the fitting range of the interatomic potentials. We find that the shape of the (111)[11 ] stacking fault energy curve varies significantly with potential, with the ratio of unstable to stable stacking fault energies ranging from 1.22 to 14.07, and some deformation paths for non-(111) orientations give activation barriers less than 50% higher than the unstable stacking fault energies. These are important considerations when choosing an interatomic potential for deformation simulations. read less M. Byshkin, B. Zhu, and M. Hou, “The effect of encapsulation in carbon nanotubes on properties of Fe–Ni nanoalloys with cubic and helical structures,” Journal of Materials Science. 2012. link Times cited: 1 T. Ye et al., “Molecular dynamics simulation of tensile deformation behavior of single-crystal Fe–Cr–Al before and after irradiation,” Journal of Materials Research. 2022. link Times cited: 1 Abstract: Fe–Cr–Al alloy is one of the candidate materials for reactor… read more Abstract: Fe–Cr–Al alloy is one of the candidate materials for reactor fuel cladding due to excellent high-temperature oxidation resistance; however, it has significant irradiation embrittlement and hardening. To understand the effect of Cr and Al and the defects (point defects, clusters, and nanocracks) produced from radiation damage on the mechanical properties, the uniaxial tensile property of single-crystal Fe–Cr–Al is investigated. The results show that, due to the presence of Cr and Al, the phase transformation from body-centered-cubic to face-centered-cubic is impeded and the formation of defects and amorphous structures is promoted, leading to the reduction of Young’s modulus and the ultimate tensile stress. Interstitials are the main factor in Frenkel pairs contributing to the reduction of mechanical properties due to the high shear stress and lattice distortion. The collapse of the nanocrack causes the increase of Young’s modulus and the decrease of the ultimate tensile strength. Graphical abstract read less R. Khusnutdinoff, R. R. Khairullina, A. L. Bel’tyukov, V. Lad’yanov, and A. Mokshin, “Viscoelastic and Quasi-Solid Properties of Ni-Containing Binary Metal Melts,” High Temperature. 2022. link Times cited: 0 V. Drozd, M. Asadikiya, S. Yang, and Y. Zhong, “Energy and Mechanical Properties Predictions in Fe-Ni Binary System by ab initio Calculations,” Materials Today Communications. 2022. link Times cited: 3 X. Li, Y. Shi, T.-Y. Chen, S. Wang, and K. Fan, “Study on Sintering Mechanism and Mechanical Properties of Fe–Ni Elastocaloric Refrigeration Alloy through Molecular Dynamics Simulation,” Materials Today Communications. 2022. link Times cited: 4 Y. Ma et al., “Atomic diffusion behavior near the bond interface during the explosive welding process based on molecular dynamics simulations,” Materials Today Communications. 2022. link Times cited: 6 Y.-chao Liang et al., “Influence of cluster correlation on nanoclusters in Fe-Ni amorphous alloys,” Journal of Alloys and Compounds. 2022. link Times cited: 10 N. Ren, L. Hu, B. Wang, K. Song, and P. Guan, “Structural topological signature of high-temperature non-Arrhenius crossover in metallic glass-forming liquids,” Scripta Materialia. 2021. link Times cited: 5 F. Baras, Q. Bizot, A. Fourmont, S. L. Gallet, and O. Politano, “Mechanical activation of metallic powders and reactivity of activated nanocomposites: a molecular dynamics approach,” Applied Physics A. 2021. link Times cited: 1 S. Zhao, “Influence of temperature and alloying elements on the threshold displacement energies in concentrated Ni–Fe–Cr alloys,” Chinese Physics B. 2021. link Times cited: 3 A. Maulana, A. Arkundato, Sutisna, and H. Trilaksana, “Mechanical properties of Fe, Ni and Fe-Ni alloy: Strength and stiffness of materials using lammps molecular dynamics simulation.” 2020. link Times cited: 2 Abstract: The mechanical properties of pure metals and alloy Fe-Ni wit… read more Abstract: The mechanical properties of pure metals and alloy Fe-Ni with various compositions have been simulated. The lammps molecular dynamics code was used to compute those physical properties: Ultimate Tensile Strength (UTS) and modulus of elasticity. At temperature 300K the UTS of iron is 8.173 GPa and for nickel is 11.645 GPa. At temperature 300K the elastic modulus of iron is 133.984 GPa and 122.321 GPa for nickel. From the simulation it known that the higher of Ni content, the lower the Ultimate Tensile Strength (UTS) of FeNi alloy and modulus of elasticity. The highest UTS and modulus of elasticity were found in the Fe-5% Ni alloy at the value of 7.960 GPa and 114.978 GPa respectively. read less V. Turlo and T. Rupert, “Interdependent Linear Complexion Structure and Dislocation Mechanics in Fe-Ni,” Crystals. 2020. link Times cited: 4 Abstract: Using large-scale atomistic simulations, dislocation mechani… read more Abstract: Using large-scale atomistic simulations, dislocation mechanics in the presence of linear complexions are investigated in an Fe-Ni alloy, where the complexions appear as nanoparticle arrays along edge dislocation lines. When mechanical shear stress is applied to drive dislocation motion, a strong pinning effect is observed where the defects are restricted by their own linear complexion structures. This pinning effect becomes weaker after the first dislocation break-away event, leading to a stress-strain curve with a profound initial yield point, similar to the static strain aging behavior observed experimentally for Fe-Mn alloys with the same type of linear complexions. The existence of such a response can be explained by local diffusion-less and lattice distortive transformations corresponding to L10-to-B2 phase transitions within the linear complexion nanoparticles. As such, an interdependence between a linear complexion structure and dislocation mechanics is found. read less G. Zhang, Y. Kang, M. Wang, H. Xu, and H.-Z. Jia, “Atomic diffusion behavior and diffusion mechanism in Fe–Cu bimetal casting process studied by molecular dynamics simulation and experiment,” Materials Research Express. 2020. link Times cited: 9 Abstract: A molecular dynamics (MD) method with an embedded atomic met… read more Abstract: A molecular dynamics (MD) method with an embedded atomic method (EAM) was proposed to study the atomic diffusion behavior and diffusion mechanism in the Fe–Cu bimetal casting process. The results indicated that the diffusion coefficient of the Cu atoms was larger than that of the Fe atoms at the same temperature, but the Fe atoms predominantly diffused into the Cu side in the process of diffusion bonding. Moreover, the relationship between diffusion distance and temperature was predicted by the established model, and the optimal temperature for interface diffusion bonding of Fe–Cu bimetal ranged from 1473K to 1753 K. The diffusion behavior was mainly due to vacancies, which played a key role in the formation of the Cu cluster, and the accumulation of Cu atoms decreased the system energy. Finally, FeAcknowledgmentsCu bimetal casting was prepared to validate the simulated results of the diffusion behavior and diffusion distance, and the simulated results were consistent with the experimental ones. read less Q. Jiang, H. Liu, J. Li, D. Yang, Y. Zhang, and W. Yang, “Atomic-level understanding of crystallization in the selective laser melting of Fe50Ni50 amorphous alloy,” Additive manufacturing. 2020. link Times cited: 21 N. Anento and A. Serra, “Interaction of a mobile 1 1 2 grain boundary with radiation induced defects in α-Fe: Transformation of defects and impact on the shear-coupled grain boundary migration,” Computational Materials Science. 2020. link Times cited: 14 B. Yu et al., “MD simulation on crystallization mechanisms of rapidly supercooled Fe-Ni alloys,” Journal of Crystal Growth. 2020. link Times cited: 10 H. Luu and N. Gunkelmann, “Pressure-induced phase transformations in Fe-C: Molecular dynamics approach,” Computational Materials Science. 2019. link Times cited: 24 L. Belkacemi, E. Meslin, B. Décamps, B. Radiguet, and J. Henry, “Radiation-induced bcc-fcc phase transformation in a Fe 3%Ni alloy,” Acta Materialia. 2018. link Times cited: 28 A. Mangla, G. Deo, and P. A. Apte, “NiFe local ordering in segregated Ni3Fe alloys: A simulation study using angular dependent potential,” Computational Materials Science. 2018. link Times cited: 8 A. Bakaev, D. Terentyev, and E. Zhurkin, “Effect of Segregation of Ni and Cr at Dislocation Loops on Their Interaction with Gliding Dislocations in Irradiated Fe−Ni−Cr BCC Alloys,” Journal of Surface Investigation: X-ray, Synchrotron and Neutron Techniques. 2018. link Times cited: 1 Y. Dou et al., “Effect of Ni and Mn on the Interaction of an Edge Dislocation with Cu-rich Precipitates in Bcc Fe,” High-Performance Computing Applications in Numerical Simulation and Edge Computing. 2018. link Times cited: 1 X. He, S. Wu, L. Jia, D. Wang, Y. Dou, and W. Yang, “Grain Boundary Segregation of Substitutional Solutes/Impurities and Grain Boundary Decohesion in BCC Fe,” Energy Procedia. 2017. link Times cited: 5 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 G. Lv and Y. Su, “Molecular dynamics simulation and first principles calculations of radiation-induced Cu clusters in Fe-3 at.% Cu alloy,” Comput. Phys. Commun.* 2017. link Times cited: 5 G. Bonny, A. Bakaev, P. Olsson, C. Domain, E. Zhurkin, and M. Posselt, “Interatomic potential to study the formation of NiCr clusters in high Cr ferritic steels,” Journal of Nuclear Materials. 2017. link Times cited: 17 N. Lopanitsyna and A. Kuksin, “Nucleation and the spall strength of liquid metals,” Journal of Physics: Conference Series. 2016. link Times cited: 2 Abstract: This article presents calculation of the nucleation rate for… read more Abstract: This article presents calculation of the nucleation rate for liquid metals (Al, Fe, Mo) based on molecular dynamic simulation for embedded atom method (EAM) potentials. The dependence of nucleation rate on pressure and temperature could be approximated accurately in the form of classical nucleation theory taking into account surface tension dependency on pore radius σ = σ0/(1 + 2δ/r), where σ—surface tension, δ—the Tolman length. Basing on the results of the calculations, we have developed a model allowing calculating the spall strength of liquid metals under tension using such parameters as surface tension, viscosity, which could be measured experimentally. The obtained results for Mo and Al are consistent with experimental data and direct MD calculations at strain rates approx. 1010-1011 s-1. read less D. Terentyev, A. Zinovev, and G. Bonny, “Displacement cascades in FeNiMnCu alloys: RVP model alloys,” Journal of Nuclear Materials. 2016. link Times cited: 7 L. You, L. Hu, Y. Xie, and S. Zhao, “Influence of Cu precipitation on tensile properties of Fe–Cu–Ni ternary alloy at different temperatures by molecular dynamics simulation,” Computational Materials Science. 2016. link Times cited: 14 G. Lv, H. Zhang, X. He, W. Yang, and Y. Su, “Vacancy enhanced formation and phase transition of Cu-rich precipitates in α - iron under neutron irradiation,” AIP Advances. 2016. link Times cited: 2 Abstract: In this paper, we employed both molecular statics and molecu… read more Abstract: In this paper, we employed both molecular statics and molecular dynamics simulation methods to investigate the role of vacancies in the formation and phase transition of Cu-rich precipitates in α-iron. The results indicated that vacancies promoted the diffusion of Cu atoms to form Cu-rich precipitates. After Cu-rich precipitates formed, they further trapped vacancies. The supersaturated vacancy concentration in the Cu-rich precipitate induced a shear strain, which triggered the phase transition from bcc to fcc structure by transforming the initial bcc (110) plane into fcc (111) plane. In addition, the formation of the fcc-twin structure and the stacking fault structure in the Cu-rich precipitates was observed in dynamics simulations. read less K. Xiong, X. Liu, and J. Gu, “Multiscale modeling of nanoindentation-induced instability in FeNi3 crystal,” Computational Materials Science. 2015. link Times cited: 6 D. Terentyev, X. He, G. Bonny, A. Bakaev, E. Zhurkin, and L. Malerba, “Hardening due to dislocation loop damage in RPV model alloys: Role of Mn segregation,” Journal of Nuclear Materials. 2015. link Times cited: 36 G. Bonny, D. Terentyev, E. Zhurkin, and L. Malerba, “Monte Carlo study of decorated dislocation loops in FeNiMnCu model alloys,” Journal of Nuclear Materials. 2014. link Times cited: 45 C.-B. Wang, W. Zhang, C. Ren, P. Huai, and Z. Zhu, “The effect of temperature on primary defect formation in Ni–Fe alloy,” Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms. 2014. link Times cited: 16 G. Bonny et al., “On the thermal stability of late blooming phases in reactor pressure vessel steels: An atomistic study,” Journal of Nuclear Materials. 2013. link Times cited: 77 T. Fang, L. Wang, and Y. Qi, “Structural, Thermodynamics and Dynamics Properties of Fe-Ni Melts with Different EAM Models,” Advanced Materials Research. 2013. link Times cited: 1 Abstract: Molecular dynamics (MD) simulation has been performed to exp… read more Abstract: Molecular dynamics (MD) simulation has been performed to explore the microstructure, thermodynamics and dynamics properties of liquid Fe-Ni alloy based upon two different embedded atom method (EAM) models. The calculated PCFs with two EAM models are good agreement with the experimental values. While the calculated Scc (q) of Bhatia-Thornton (B-T) structure factor (SF) shows different behavior: a sharp increasing and a small one at lower q from G. Bonnys model and Zhous model respectively. The mixing of enthalpy with G. Bonnys EAM is positive in the whole concentration range. While the different mixing behavior with a slightly negative mixing of enthalpy based on Zhous model, which is consistent with the experimental results, is observed. Density and diffusion coefficients of liquid Fe-Ni as a function of composition show the same tendency based on both G. Bonnys model and Zhous model. In this work, Fe-Ni melts show different mixing behavior based on the two different EAM models. read less X. Shu et al., “Fe self-diffusion and Cu and Ni diffusion in bulk and grain boundary of Fe: A molecular dynamics study,” Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms. 2013. link Times cited: 10 T. Fang, L. Wang, and Y. Qi, “Molecular Dynamics Simulation of Liquid Cu-Ni Alloy Using Embedded Atom Method,” Advanced Materials Research. 2013. link Times cited: 0 Abstract: Molecular dynamics simulation has been performed to explore … read more Abstract: Molecular dynamics simulation has been performed to explore the thermodynamics and dynamics properties of liquid Cu-Ni alloy based upon developed embedded atom methods (EAM), namely due to G. Bonny. The calculated liquid density shows that the potential underestimates the measured atomic density for Ni-rich composition. The calculated mixing enthalpy predicts the potential underestimates the mixing enthalpy when the concentration of Ni is increased beyond roughly 30 at. %. We make a conclusion from the fact that the G. Bonny’s model is not full perfect in describing the density and mixing enthalpy of Cu-Ni melts at the Ni-rich composition. read less R. Idczak, R. Konieczny, and J. Chojcan, “Thermodynamic properties of Fe–Ni solid solutions studied by 57Fe Mössbauer spectroscopy,” Physica B-condensed Matter. 2012. link Times cited: 5 D. Terentyev, L. Malerba, G. Bonny, A. Al-Motasem, and M. Posselt, “Interaction of an edge dislocation with Cu–Ni-vacancy clusters in bcc iron,” Journal of Nuclear Materials. 2011. link Times cited: 24 A. Al-Motasem, M. Posselt, and F. Bergner, “Nanoclusters in bcc-Fe containing vacancies, copper and nickel: Structure and energetics,” Journal of Nuclear Materials. 2011. link Times cited: 25 R. Anders and F. Haider, “Calculation of phase diagrams and simulation of segregation using Monte Carlo with lattice relaxation,” Journal of Nuclear Materials. 2010. link Times cited: 0 L. Sandoval, H. Urbassek, and P. Entel, “Solid-solid phase transitions and phonon softening in an embedded-atom method model for iron,” Physical Review B. 2009. link Times cited: 36 N. Castin, L. Malerba, G. Bonny, M. I. Pascuet, and M. Hou, “Modelling radiation-induced phase changes in binary FeCu and ternary FeCuNi alloys using an artificial intelligence-based atomistic kinetic Monte Carlo approach,” Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms. 2009. link Times cited: 24 Y. Zhang, Y. G. Jung, and J. Zhang, “Molecular dynamics modeling of sintering phenomena and mechanical strength of metal particles.” 2020. link Times cited: 0 H. Zheng, B. Li, Y. Tan, G. Li, X. Shu, and P. Peng, “Derivative effect of laser cladding on interface stability of YSZ@Ni coating on GH4169 alloy: An experimental and theoretical study,” Applied Surface Science. 2018. link Times cited: 8 S. Paul, Nagahanumaiah, S. Mitra, and D. Roy, “Molecular Dynamics Simulation Study of Neck Growth in Micro-selective Laser Sintering of Copper Nanoparticles.” 2018. link Times cited: 6 Y. Zhang, L. Wu, H. El-Mounayri, K. Brand, and J. Zhang, “Molecular Dynamics Study of the Strength of Laser Sintered Iron Nanoparticles,” Procedia Manufacturing. 2015. link Times cited: 28 D. Molnár, P. Binkele, A. Mora, R. Mukherjee, B. Nestler, and S. Schmauder, “Molecular Dynamics virtual testing of thermally aged Fe–Cu microstructures obtained from multiscale simulations,” Computational Materials Science. 2014. link Times cited: 9 R. Khanna and V. Sahajwalla, “Atomistic Simulations of Properties and Phenomena at High Temperatures.” 2014. link Times cited: 3 D. Li, H. Zbib, X. Sun, and M. Khaleel, “Predicting plastic flow and irradiation hardening of iron single crystal with mechanism-based continuum dislocation dynamics,” International Journal of Plasticity. 2014. link Times cited: 107 Y. Xu, G. Wang, J. Shen, P. Qian, and Y. Su, “Structural features, thermal stability and catalytic implication of Fe–Ni nanoparticles,” Journal of Solid State Chemistry. 2023. link Times cited: 0 A. Mangla, G. Deo, and P. A. Apte, “Cooperative freezing of the L12 ordered domains at the critical cooling temperature of Ni3Fe alloy,” Journal of Statistical Mechanics: Theory and Experiment. 2022. link Times cited: 0 Abstract: It is well known that Ni3Fe transforms from a disordered sol… read more Abstract: It is well known that Ni3Fe transforms from a disordered solid solution to an ordered intermetallic with L12 superstructure when the alloy is cooled slowly. Here we elucidate the underlying cooperative phenomenon and the atomistic mechanism of this ordering process based on simulations using embedded atom potentials. As the simulated alloy is cooled from the disordered state to the critical cooling temperature (T c), Ni atoms with L12 order [denoted as Ni(L12 ⩾ 1) atoms] increase significantly along with Ni atoms having the least deviation from L12 local order (denoted as Ni([IP]3) atoms). The ordering (up to T c) occurs predominantly through random increase in Ni(L12 ⩾ 1) atoms throughout the system, as indicated by absence of long-range order. At T c, L12 ordered domains formed by Ni(L12 ⩾ 1) atoms ‘freeze’, i.e. these domains, collectively, achieve a threshold strength against thermal fluctuations. This is indicated by (i) dissipation of large-scale fluctuations of Ni(L12 ⩾ 1) atoms at T c and (ii) the growth of the L12 domains through propagation (at the expense of atoms with non-L12 local environment) as the alloy is cooled below T c. The stability threshold of the L12 ordered domains at T c is qualitatively consistent with (i) the critical slowing down, i.e. a significant increase in annealing time (to about 41 days) at 497 °C close to T c (∼500 °C) and (ii) sharp changes in bulk properties (due to loss of stability of the domains) when the alloy is heated across T c to about 550 °C. Further, the experimental long-range order parameter values as a function of reduced temperature are in reasonable agreement with the corresponding values of the simulated alloys. The contribution of Ni([IP]3) atoms to ordering in the actual alloy is potentially significant since such atoms together with nearest neighbours constitute about 75% of the total atoms in the simulated alloys at T c. read less W.-Z. L. S.-Z. Yu et al., “Machine‐learning‐based interatomic potentials for advanced manufacturing,” International Journal of Mechanical System Dynamics. 2021. link Times cited: 2 Abstract: This paper summarizes the progress of machine‐learning‐based… read more Abstract: This paper summarizes the progress of machine‐learning‐based interatomic potentials and their applications in advanced manufacturing. Interatomic potential is essential for classical molecular dynamics. The advancements made in machine learning (ML) have enabled the development of fast interatomic potential with ab initio accuracy. The accelerated atomic simulation can greatly transform the design principle of manufacturing technology. The most widely used supervised and unsupervised ML methods are summarized and compared. Then, the emerging interatomic models based on ML are discussed: Gaussian approximation potential, spectral neighbor analysis potential, deep potential molecular dynamics, SCHNET, hierarchically interacting particle neural network, and fast learning of atomistic rare events. read less E. Meshkov, I. Novoselov, A. Shapeev, and A. Yanilkin, “Sublattice formation in CoCrFeNi high-entropy alloy,” Intermetallics. 2019. link Times cited: 17 V. Turlo and T. Rupert, “Prediction of a wide variety of linear complexions in face centered cubic alloys,” Acta Materialia. 2019. link Times cited: 11 N. Ren, B. Shang, P. Guan, and L. Hu, “General structural and dynamic characteristics beneficial to glass-forming ability of Fe-based glass-forming liquids,” Journal of Non-crystalline Solids. 2018. link Times cited: 7 L. Béland et al., “Accurate classical short-range forces for the study of collision cascades in Fe-Ni-Cr,” Comput. Phys. Commun. 2017. link Times cited: 34 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 K. Xiong and J. Gu, “Understanding pop-in phenomena in FeNi3 nanoindentation,” Intermetallics. 2015. link Times cited: 19 C. P. Chui, W. Liu, Y. Xu, and Y. Zhou, “Molecular Dynamics Simulation of Iron — A Review.” 2015. link Times cited: 3 Abstract: Molecular dynamics (MD) is a technique of atomistic simulati… read more Abstract: Molecular dynamics (MD) is a technique of atomistic simulation which has facilitated scientific discovery of interactions among particles since its advent in the late 1950s. Its merit lies in incorporating statistical mechanics to allow for examination of varying atomic configurations at finite temperatures. Its contributions to materials science from modeling pure metal properties to designing nanowires is also remarkable. This review paper focuses on the progress of MD in understanding the behavior of iron — in pure metal form, in alloys, and in composite nanomaterials. It also discusses the interatomic potentials and the integration algorithms used for simulating iron in the literature. Furthermore, it reveals the current progress of MD in simulating iron by exhibiting some results in the literature. Finally, the review paper briefly mentions the development of the hardware and software tools for such large-scale computations. read less Z. Trautt, F. Tavazza, and C. Becker, “Facilitating the selection and creation of accurate interatomic potentials with robust tools and characterization,” Modelling and Simulation in Materials Science and Engineering. 2015. link Times cited: 14 Abstract: The Materials Genome Initiative seeks to significantly decre… read more Abstract: The Materials Genome Initiative seeks to significantly decrease the cost and time of development and integration of new materials. Within the domain of atomistic simulations, several roadblocks stand in the way of reaching this goal. While the NIST Interatomic Potentials Repository hosts numerous interatomic potentials (force fields), researchers cannot immediately determine the best choice(s) for their use case. Researchers developing new potentials, specifically those in restricted environments, lack a comprehensive portfolio of efficient tools capable of calculating and archiving the properties of their potentials. This paper elucidates one solution to these problems, which uses Python-based scripts that are suitable for rapid property evaluation and human knowledge transfer. Calculation results are visible on the repository website, which reduces the time required to select an interatomic potential for a specific use case. Furthermore, property evaluation scripts are being integrated with modern platforms to improve discoverability and access of materials property data. To demonstrate these scripts and features, we will discuss the automation of stacking fault energy calculations and their application to additional elements. While the calculation methodology was developed previously, we are using it here as a case study in simulation automation and property calculations. We demonstrate how the use of Python scripts allows for rapid calculation in a more easily managed way where the calculations can be modified, and the results presented in user-friendly and concise ways. Additionally, the methods can be incorporated into other efforts, such as openKIM. read less Y. Osetsky, N. Anento, A. Serra, and D. Terentyev, “The role of nickel in radiation damage of ferritic alloys,” Acta Materialia. 2015. link Times cited: 18 W. Cui, C. Peng, L. Wang, Y. Qi, and T. Fang, “Structure and dynamics of undercooled FeNi,” Physics and Chemistry of Liquids. 2014. link Times cited: 2 Abstract: Molecular dynamics simulation has been performed to explore … read more Abstract: Molecular dynamics simulation has been performed to explore the structural and dynamical properties of undercooled FeNi melt based on the embedded atom method (EAM), namely due to G. Bonny. The simulated partial pair correlation function (PPCF) and coordination number (CN) of liquid FeNi indicate that no stronger interaction of heterogenic atom pairs than those of the same atom pairs happen in melts. FeNi melt is close to an ideal mixing system without chemical short-range order (CSRO). The undercooled FeNi exhibits icosahedral short-range order (ISRO) that is reflected directly as a large number of 1551, 1541 bonded pairs as well as snapshot of icosahedron clusters. The mean squared displacement (MSD) and self diffusion coefficient of Fe and Ni is quite similar, which is consistent with the strong glass formation liquid of Ni36Zr64. Our work gives the detailed structure and dynamics information of undercooled FeNi melt. read less N. Gunkelmann, H. Ledbetter, and H. Urbassek, “Experimental and atomistic study of the elastic properties of α′ Fe–C martensite,” Acta Materialia. 2012. link Times cited: 38 L. Malerba et al., “Comparison of empirical interatomic potentials for iron applied to radiation damage studies,” Journal of Nuclear Materials. 2010. link Times cited: 210 G. Ackland and G. Bonny, “Interatomic Potential Development,” Comprehensive Nuclear Materials. 2020. link Times cited: 4 L. Malerba, “Multi-scale modelling of irradiation effects in nuclear power plant materials.” 2010. link Times cited: 3 Abstract: Abstract: This chapter surveys the computer-based multi-scal… read more Abstract: Abstract: This chapter surveys the computer-based multi-scale modelling approaches currently being used to develop physical models of the effects of radiation on nuclear materials. The focus is on the problem of radiation-induced hardening (and embrittlement) in steels, limited to the scales ranging from the nucleus to the single crystal. First, the multi-scale nature of radiation effects is illustrated, including examples of microstructural and mechanical property changes observed in steels used in nuclear reactors. Then the chapter discusses the fundamental ideas upon which the multi-scale modelling approach is based. Next, an overview of the techniques of use in a multi-scale modelling framework is given, with an example of how these can be integrated. A discussion of the state-of-the-art and other general remarks conclude the chapter. read less P. Yu, L. Zhang, and L. Du, “Atomic Simulations for Packing Changes of Nano-Sized Cu Clusters Embedded in the Febulk on Heating,” Metals. 2021. link Times cited: 3 Abstract: Understanding of the defect evolution mechanism under irradi… read more Abstract: Understanding of the defect evolution mechanism under irradiation is very important for the research of pressure vessel steel embrittlement. In this paper, the embedded atom method (EAM) based canonical ensemble molecular dynamics (MD) method was used to study the evolution of the stacking structure of different nano-sized Cun (n = 13, 43 and 87) clusters in an Febulk embedded with BCC lattice structure during continuous heating. The mean square displacement, pair distribution functions and atomic structures of Cu atom clusters at the nanometer scale were calculated at different temperatures. The structural changes present apparent differences, for the Febulks contain nano-sized Cu clusters with different atom numbers during heating. For the Febulk–Cu13 system, since the ability to accommodate the atomic Cu in the Fe substrate is lesser, a small number of Cu atoms in BCC lattice positions cannot influence the whole structure of the Fe-Cu system. For the Febulk–Cu43 system, with an increase in temperature, a Cu atomic pile structural change happened, and the strain areas decreased significantly in the Febulk, but a single strain area grew large. For the Febulk–Cu87 system, when the Cu atoms are constrained by the Fe atoms in bulk, only a few of the Cu atoms adjust their positions. With the increase in temperature, strain in the Fe eased. read less K. Li and C. Fu, “Ground-state properties and lattice-vibration effects of disordered Fe-Ni systems for phase stability predictions,” Physical Review Materials. 2020. link Times cited: 6 Abstract: By means of density functional theory, we perform a focused … read more Abstract: By means of density functional theory, we perform a focused study of both body-centered-cubic (bcc) and face-centered-cubic (fcc) Fe-Ni random solid solutions, represented by special quasirandom structures. The whole concentration range and various magnetic configurations are considered. Excellent agreement on the concentration dependence of magnetization is found between our results and experimental data, except in the Invar region. Some locally antiferromagnetic fcc structures are proposed to approach experimental values of magnetization. Vibrational entropies of ordered and disordered systems are calculated for various concentrations, showing an overall good agreement with available experimental data. The vibrational entropy systematically contributes to stabilize disordered rather than ordered structures and is not negligible compared to the configurational entropy. Free energy of mixing is estimated by including the vibrational and ideal configurational entropies. From them, low- and intermediate-temperature Fe-Ni phase diagrams are constructed, showing a better agreement with experimental data than the one from a recent thermodynamic assessment for some phase boundaries below 700 K. The determined order-disorder transition temperatures for the $\mathrm{L}{1}_{0}$ and $\mathrm{L}{1}_{2}$ phases are in good agreement with the experimental values, suggesting an important contribution of vibrational entropy. read less J.-B. Wang, R. Huang, and Y. Wen, “Thermally activated phase transitions in Fe-Ni core-shell nanoparticles,” Frontiers of Physics. 2019. link Times cited: 0 T. M. Whiting, P. Burr, D. King, and M. Wenman, “Understanding the importance of the energetics of Mn, Ni, Cu, Si and vacancy triplet clusters in bcc Fe,” Journal of Applied Physics. 2019. link Times cited: 11 Abstract: Numerous experimental studies have found the presence of (Cu… read more Abstract: Numerous experimental studies have found the presence of (Cu)-Ni-Mn-Si clusters in neutron irradiated reactor pressure vessel steels, prompting concerns that these clusters could lead to larger than expected increases in hardening, especially at high fluences late in life. The mechanics governing clustering for the Fe-Mn-Ni-Si system are not well-known; state-of-the-art methods use kinetic Monte Carlo (KMC) parameterized by density functional theory (DFT) and thermodynamic data to model the time evolution of clusters. However, DFT-based KMC studies have so far been limited to only pairwise interactions due to lack of DFT data. Here, we explicitly calculate the binding energy of triplet clusters of Mn, Ni, Cu, Si, and vacancies in bcc Fe using DFT to show that the presence of vacancies, Si, or Cu stabilizes cluster formation, as clusters containing exclusively Mn and/or Ni are not energetically stable in the absence of interstitials. We further identify which clusters may be reasonably approximated as a sum of pairwise interactions and which instead require an explicit treatment of the three-body interaction, showing that the three-body term can account for as much as 0.3 eV, especially for clusters containing vacancies. read less S. Zhi-peng, D. Fuzhi, X. Ben, and Z. Wen-zheng, “Three-Dimensional Growth of Coherent Ferrite in Austenite: A Molecular Dynamics Study,” Acta Metallurgica Sinica (english Letters). 2019. link Times cited: 1 Z. Sun, F. Z. Dai, B. Xu, and W.-Z. Zhang, “Three-Dimensional Growth of Coherent Ferrite in Austenite: A Molecular Dynamics Study,” Acta Metallurgica Sinica (English Letters). 2019. link Times cited: 5 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 N. Anento, A. Serra, and Y. Osetsky, “Effect of nickel on point defects diffusion in Fe – Ni alloys,” Acta Materialia. 2017. link Times cited: 30 A. Bakaev, A. Bakaev, D. Terentyev, and E. Zhurkin, “Atomistic simulation of the segregation of alloying elements close to radiation-induced defects in irradiated Fe–Cr–Ni BCC alloys,” Journal of Surface Investigation: X-ray, Synchrotron and Neutron Techniques. 2017. link Times cited: 4 L. Béland, Y. Osetsky, and R. Stoller, “The effect of alloying nickel with iron on the supersonic ballistic stage of high energy displacement cascades,” Acta Materialia. 2016. link Times cited: 28 Y. Osetsky, L. Béland, and R. Stoller, “Specific features of defect and mass transport in concentrated fcc alloys,” Acta Materialia. 2016. link Times cited: 67 Y. Zhang et al., “Influence of chemical disorder on energy dissipation and defect evolution in advanced alloys,” Journal of Materials Research. 2016. link Times cited: 103 Abstract: Historically, alloy development with better radiation perfor… read more Abstract: Historically, alloy development with better radiation performance has been focused on traditional alloys with one or two principal element(s) and minor alloying elements, where enhanced radiation resistance depends on microstructural or nanoscale features to mitigate displacement damage. In sharp contrast to traditional alloys, recent advances of single-phase concentrated solid solution alloys (SP-CSAs) have opened up new frontiers in materials research. In these alloys, a random arrangement of multiple elemental species on a crystalline lattice results in disordered local chemical environments and unique site-to-site lattice distortions. Based on closely integrated computational and experimental studies using a novel set of SP-CSAs in a face-centered cubic structure, we have explicitly demonstrated that increasing chemical disorder can lead to a substantial reduction in electron mean free paths, as well as electrical and thermal conductivity, which results in slower heat dissipation in SP-CSAs. The chemical disorder also has a significant impact on defect evolution under ion irradiation. Considerable improvement in radiation resistance is observed with increasing chemical disorder at electronic and atomic levels. The insights into defect dynamics may provide a basis for understanding elemental effects on evolution of radiation damage in irradiated materials and may inspire new design principles of radiation-tolerant structural alloys for advanced energy systems. read less K. Tong, F. Ye, M. Gao, M. Lei, and C. Zhang, “Interatomic potential for Fe–Cr–Ni–N system based on the second nearest-neighbor modified embedded-atom method,” Molecular Simulation. 2016. link Times cited: 7 Abstract: The interatomic potential for Fe–Cr–Ni–N system based on the… read more Abstract: The interatomic potential for Fe–Cr–Ni–N system based on the second nearest-neighbour modified embedded-atom method has been developed in this work. The potential is based on those for the corresponding lower order systems. The potential parameters for the binary systems, Cr–N, Ni–N, Ni–Fe and Ni–Cr, were determined by fitting the lattice constants, elastic properties, heat of solution and defect binding energies. The potential parameters for the ternary systems were calculated based on the corresponding binary systems. Then, all of them were applied to the quaternary system Fe–Cr–Ni–N to confirm their validity by a simulation of the lattice constants of AISI 316 austenitic stainless steel with a range of nitrogen content. The results were in good agreement with the previous observations and calculations. read less L. Béland et al., “Features of primary damage by high energy displacement cascades in concentrated Ni-based alloys,” Journal of Applied Physics. 2016. link Times cited: 53 Abstract: Alloying of Ni with Fe or Co has been shown to reduce primar… read more Abstract: Alloying of Ni with Fe or Co has been shown to reduce primary damage production under ion irradiation. Similar results have been obtained from classical molecular dynamics simulations of 1, 10, 20, and 40 keV collision cascades in Ni, NiFe, and NiCo. In all cases, a mix of imperfect stacking fault tetrahedra, faulted loops with a 1/3⟨111⟩ Burgers vector, and glissile interstitial loops with a 1/2⟨110⟩ Burgers vector were formed, along with small sessile point defect complexes and clusters. Primary damage reduction occurs by three mechanisms. First, Ni-Co, Ni-Fe, Co-Co, and Fe-Fe short-distance repulsive interactions are stiffer than Ni-Ni interactions, which lead to a decrease in damage formation during the transition from the supersonic ballistic regime to the sonic regime. This largely controls final defect production. Second, alloying decreases thermal conductivity, leading to a longer thermal spike lifetime. The associated annealing reduces final damage production. These two mechanisms are especially ... read less E. Sak-Saracino and H. Urbassek, “Temperature-induced phase transformation of Fe1-xNix alloys: molecular-dynamics approach,” The European Physical Journal B. 2015. link Times cited: 17 A. Ojha, H. Sehitoglu, L. Patriarca, and H. Maier, “Twin nucleation in Fe-based bcc alloys—modeling and experiments,” Modelling and Simulation in Materials Science and Engineering. 2014. link Times cited: 43 Abstract: We develop an analytical expression for twin nucleation stre… read more Abstract: We develop an analytical expression for twin nucleation stress in bcc metal and alloys considering generalized planar fault energy and the dislocations bounding the twin nucleus. We minimize the total energy to predict the twinning stress relying only on parameters that are obtained through atomistic calculations, thus excluding the need for any empirical constants. We validate the present approach by means of precise measurements of the onset of twinning in bcc Fe–50at% Cr single crystals showing excellent agreement. The experimental observations of the three activated slip systems of symmetric configuration in relation to the twinning mechanism are demonstrated via transmission electron microscopy techniques along with digital image correlation. We then confirm the validity of the model for Fe, Fe–25at% Ni and Fe–3at% V alloys compared with experiments from the literature to show general applicability. read less M. Lavrentiev, J. Wróbel, D. Nguyen-Manh, and S. Dudarev, “Magnetic and thermodynamic properties of face-centered cubic Fe-Ni alloys.,” Physical chemistry chemical physics : PCCP. 2014. link Times cited: 48 Abstract: A model lattice ab initio parameterized Heisenberg-Landau ma… read more Abstract: A model lattice ab initio parameterized Heisenberg-Landau magnetic cluster expansion Hamiltonian spanning a broad range of alloy compositions and a large variety of chemical and magnetic configurations has been developed for face-centered cubic Fe-Ni alloys. The thermodynamic and magnetic properties of the alloys are explored using configuration and magnetic Monte Carlo simulations over a temperature range extending well over 1000 K. The predicted face-centered cubic-body-centered cubic coexistence curve, the phase stability of ordered Fe3Ni, FeNi, and FeNi3 intermetallic compounds, and the predicted temperatures of magnetic transitions simulated as functions of alloy composition agree well with experimental observations. Simulations show that magnetic interactions stabilize the face-centered cubic phase of Fe-Ni alloys. Both the model Hamiltonian simulations and ab initio data exhibit a particularly large number of magnetic configurations in a relatively narrow range of alloy compositions corresponding to the occurrence of the Invar effect. read less G. Bonny, N. Castin, and D. Terentyev, “Interatomic potential for studying ageing under irradiation in stainless steels: the FeNiCr model alloy,” Modelling and Simulation in Materials Science and Engineering. 2013. link Times cited: 215 Abstract: The degradation of austenitic stainless steels in a radiatio… read more Abstract: The degradation of austenitic stainless steels in a radiation environment is a known problem for the in-core components of nuclear light water reactors. For a better understanding of the prevailing mechanisms responsible for the materials' degradation, large-scale atomistic simulations are desirable. In this framework and as a follow-up on Bonny et al (2011 Modelling Simul. Mater. Sci. Eng. 19 085008), we developed an embedded atom method type interatomic potential for the ternary FeNiCr system to model the production and evolution of radiation defects. Special attention has been drawn to the Fe10Ni20Cr alloy, whose properties were ensured to be close to those of 316L austenitic stainless steels. The potential is extensively benchmarked against density functional theory calculations and the potential developed in our earlier work. As a first validation, the potential is used in AKMC simulations to simulate thermal annealing experiments in order to determine the self-diffusion coefficients of the components in FeNiCr alloys around the Fe10Ni20Cr composition. The results from these simulations are consistent with experiments, i.e., DCr > DNi > DFe. read less E. Barker, D. Li, H. Zbib, and X. Sun, “Gradient Plasticity Model and its Implementation into MARMOT.” 2013. link Times cited: 0 Abstract: The influence of strain gradient on deformation behavior of … read more Abstract: The influence of strain gradient on deformation behavior of nuclear structural materials, such as boby centered cubic (bcc) iron alloys has been investigated. We have developed and implemented a dislocation based strain gradient crystal plasticity material model. A mesoscale crystal plasticity model for inelastic deformation of metallic material, bcc steel, has been developed and implemented numerically. Continuum Dislocation Dynamics (CDD) with a novel constitutive law based on dislocation density evolution mechanisms was developed to investigate the deformation behaviors of single crystals, as well as polycrystalline materials by coupling CDD and crystal plasticity (CP). The dislocation density evolution law in this model is mechanism-based, with parameters measured from experiments or simulated with lower-length scale models, not an empirical law with parameters back-fitted from the flow curves. read less S. G. Mayr and A. Arabi-Hashemi, “Structural defects in Fe–Pd-based ferromagnetic shape memory alloys: tuning transformation properties by ion irradiation and severe plastic deformation,” New Journal of Physics. 2012. link Times cited: 8 Abstract: Fe–Pd-based ferromagnetic shape memory alloys constitute an … read more Abstract: Fe–Pd-based ferromagnetic shape memory alloys constitute an exciting class of magnetically switchable smart materials that reveal excellent mechanical properties and biocompatibility. However, their application is severely hampered by a lack of understanding of the physics at the atomic scale. A many-body potential is presented that matched ab inito calculations and can account for the energetics of martensite austenite transition along the Bain path and relative phase stabilities in the ordered and disordered phases of Fe–Pd. Employed in massively parallel classical molecular dynamics simulations, the impact of order/disorder, point defects and severe plastic deformation in the presence of single- and polycrystalline microstructures are explored as a function of temperature. The model predictions are in agreement with experiments on phase changes induced by ion irradiation, cold rolling and hammering, which are also presented. read less H. Zbib, D. Li, X. Sun, and M. Khaleel, “Large Scale DD Simulation Results for Crystal Plasticity Parameters in Fe-Cr And Fe-Ni Systems.” 2012. link Times cited: 1 Abstract: The development of viable nuclear energy source depends on e… read more Abstract: The development of viable nuclear energy source depends on ensuring structural materials integrity. Structural materials in nuclear reactors will operate in harsh radiation conditions coupled with high level hydrogen and helium production, as well as formation of high density of point defects and defect clusters, and thus will experience severe degradation of mechanical properties. Therefore, the main objective of this work is to develop a capability that predicts aging behavior and in-service lifetime of nuclear reactor components and, thus provide an instrumental tool for tailoring materials design and development for application in future nuclear reactor technologies. Towards this end goal, the long term effort is to develop a physically based multiscale modeling hierarchy, validated and verified, to address outstanding questions regarding the effects of irradiation on materials microstructure and mechanical properties during extended service in the fission and fusion environments. The focus of the current investigation is on modern steels for use in nuclear reactors including high strength ferritic-martensitic steels (Fe-Cr-Ni alloys). The effort is to develop a predicative capability for the influence of irradiation on mechanical behavior. Irradiation hardening is related to structural information crossing different length scales, such as composition, dislocation, and crystal orientation distribution. To predict effectivemore » hardening, the influence factors along different length scales should be considered. Therefore, a hierarchical upscaling methodology is implemented in this work in which relevant information is passed between models at three scales, namely, from molecular dynamics to dislocation dynamics to dislocation-based crystal plasticity. The molecular dynamics (MD) was used to predict the dislocation mobility in body centered cubic (bcc) Fe and its Ni and Cr alloys. The results are then passed on to dislocation dynamics to predict the critical resolved shear stress (CRSS) from the evolution of local dislocation and defects. In this report the focus is on the results obtained from large scale dislocation dynamics simulations. The effect of defect density, materials structure was investigated, and evolution laws are obtained. These results will form the bases for the development of evolution and hardening laws for a dislocation-based crystal plasticity framework. The hierarchical upscaling method being developed in this project can provide a guidance tool to evaluate performance of structural materials for next-generation nuclear reactors. Combined with other tools developed in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the models developed will have more impact in improving the reliability of current reactors and affordability of new reactors.« less read less M. Byshkin and M. Hou, “Phase transformations and segregation in Fe–Ni alloys and nanoalloys,” Journal of Materials Science. 2012. link Times cited: 16 G. Bonny, D. Terentyev, R. Pasianot, S. Poncé, and A. Bakaev, “Interatomic potential to study plasticity in stainless steels: the FeNiCr model alloy,” Modelling and Simulation in Materials Science and Engineering. 2011. link Times cited: 180 Abstract: Austenitic stainless steels are commonly used materials for … read more Abstract: Austenitic stainless steels are commonly used materials for in-core components of nuclear light water reactors. In service, such components are exposed to harsh conditions: intense neutron irradiation, mechanical and thermal stresses, and aggressive corrosion environment which all contribute to the components' degradation. For a better understanding of the prevailing mechanisms responsible for the materials degradation, large-scale atomistic simulations are desirable. In this framework we developed an embedded atom method type interatomic potential for the ternary FeNiCr system to model movement of dislocations and their interaction with radiation defects. Special attention has been drawn to the Fe–10Ni–20Cr alloy, whose properties were ensured to be close to those of 316L austenitic stainless steel. In particular, the stacking fault energy and elastic constants are well reproduced. The fcc phase for the Fe–10Ni–20Cr random alloy was proven to be stable in the temperature range 0–900 K and under shear strain up to 5%. For the same alloy the stable glide of screw dislocations and stability of Frank loops was confirmed. read less G. Ackland, T. P. C. Klaver, and D. Hepburn, “First Principles Calculations of Defects in Unstable Crystals: Austenitic Iron,” arXiv: Materials Science. 2011. link Times cited: 0 Abstract: First principles calculations have given a new insight into … read more Abstract: First principles calculations have given a new insight into the energies of point defects in many different materials, information which cannot be readily obtained from experiment. Most such calculation are done at zero Kelvin, with the assumption that finite temperature effects on defect energies and barriers are small. In some materials, however, the stable crystal structre of interest is mechanically unstable at 0K. In such cases, alternate approaches are needed. Here we present results of first principles calculations of austenitic iron using the VASP code. We determine an appropriate reference state for collinear magnetism to be the antiferromagnetic double-layer (AFM-d) which is both stable and lower in energy than other possible models for the low temperature limit of paramagnetic fcc iron. We then consider the energetics of dissolving typical alloying impurities (Ni, Cr) in the materials, and their interaction with point defects typical of the irradiated environment. We show that using standard methods there is a very strong dependence of calculated defect formation energies on the reference state chosen. Furthermore, there is a correlation between local free volume magnetism and energetics. The effect of substitutional Ni and Cr on defect properties is weak, rarely more than tenths of eV, so it is unlikely that small amounts of Ni and Cr will have a significant effect on the radiation damage in austenitic iron at high temperatures. read less S. Bokoch and V. Tatarenko, “Interatomic Interactions in F.C.C.-Ni–Fe Alloys.” 2010. link Times cited: 5 Abstract: The authors express their appreciation to Dr. H. M. Zapolsky… read more Abstract: The authors express their appreciation to Dr. H. M. Zapolsky, Prof. D. Blavette and Prof. D. Ledue (GPM, UMR 6634 CNRS, Universite de Rouen, France) for very constructive discussion of the results obtained in the course of a given work. One of the authors (S. M. B.) acknowledges the partial financial assistance he has received from GPM (Rouen, France) as well as Nanoscience Foundation (Grenoble, France). We thank Prof. M. S. Blanter (Moscow State Academy of Instrumental Engineering and Information Science, Russia), Dr. R. V. Chepulskii (Duke University, U.S.A.), Prof. B. Schonfeld (ETH, Laboratory of Metal Physics and Technology, Switzerland), Dr. G. E. Ice (Oak Ridge National Laboratory, U.S.A.) and Mr. D. Pavlyuchkov (Forschungszentrum Jьlich GmbH, Germany) for kindly providing their publications and communicating important references. We apologize to other researchers, which have actively worked on the various problems related with our work, whose relevant publications are not referenced and discussed in a given paper because of volume limitations. This work has been inspired by discussions at the several congresses and conferences, primarily, European Congress on Advanced Materials and Processes ‘EUROMAT2007’ (10—13 Sept. 2007, Nurnberg, FRG), ‘Contemporary Problems of Metal Physics’ (7—9 Oct. 2008, Kyyiv, Ukraine), etc. read less L. Malerba et al., “Ab initio calculations and interatomic potentials for iron and iron alloys : Achievements within the Perfect Project,” Journal of Nuclear Materials. 2010. link Times cited: 65 E. Beamish, C. Campañá, and T. Woo, “Grain boundary sliding in irradiated stressed Fe–Ni bicrystals: a molecular dynamics study,” Journal of Physics: Condensed Matter. 2010. link Times cited: 5 Abstract: Molecular dynamics simulations were used to model grain boun… read more Abstract: Molecular dynamics simulations were used to model grain boundary sliding in stressed Fe–Ni bicrystals exposed to low energy neutron irradiation. We studied how sliding stress thresholds and sliding mechanisms changed with variations in the Ni boundary morphology and boundary geometry. Simulations corresponding to ordered boundary Ni distributions and coincident-site lattice (CSL) geometries relaxed stress through a dislocation-mediated sliding mechanism. Such a mechanism was found to follow Orowan’s law, in which the stress relaxation rate is proportional to the dislocation velocity. Alternatively, simulations of disordered Ni distributions and non-CSL boundary geometries were described by a random shuffling process with time-dependent stress relaxation rate. Nevertheless, irrespective of the stress relaxation process followed by the bicrystals, after reaching equilibrium, the amounts of boundary displacement and stress relaxation were always found to be proportionally related. These observations might prove useful to groups working on building continuum (macroscopic) models of deformations in irradiated materials. read less G. Bonny and R. Pasianot, “Gauge transformations to combine multi-component many-body interatomic potentials,” Philosophical Magazine Letters. 2010. link Times cited: 19 Abstract: Many-body interatomic potentials play an important role in a… read more Abstract: Many-body interatomic potentials play an important role in atomistic modelling of materials. For pure elements it is known that there exist gauge transformations that can change the form of the potential functions without modifying its properties. These same transformations, however, fail when applied to alloys. Even though different research groups may use the same potentials to describe pure elements, the gauges employed for fitting alloys will generally be different. In this scenario, it is a priori impossible to merge them into one potential describing the combined system, and thus no advantage is taken from state-of-the-art developments in the literature. Here, we generalise the gauge transformations applied to pure species in order to leave the properties of alloys invariant. Based on these transformations, a strategy to merge potentials developed within different gauges is presented, aiming at the description of the combined system. Advantage of existing state-of-the-art potentials is so taken, thus focusing the efforts on fitting only the missing interactions. Such a procedure constitutes a helpful tool for the development of potentials targeted to alloys of increased complexity, while maintaining the description quality of their constituents. read less N. Castin and L. Malerba, “Calculation of proper energy barriers for atomistic kinetic Monte Carlo simulations on rigid lattice with chemical and strain field long-range effects using artificial neural networks.,” The Journal of chemical physics. 2010. link Times cited: 49 Abstract: In this paper we take a few steps further in the development… read more Abstract: In this paper we take a few steps further in the development of an approach based on the use of an artificial neural network (ANN) to introduce long-range chemical effects and zero temperature relaxation (elastic strain) effects in a rigid lattice atomistic kinetic Monte Carlo (AKMC) model. The ANN is trained to predict the vacancy migration energies as calculated given an interatomic potential with the nudged elastic band method, as functions of the local atomic environment. The kinetics of a single-vacancy migration is thus predicted as accurately as possible, within the limits of the given interatomic potential. The detailed procedure to apply this method is described and analyzed in detail. A novel ANN training algorithm is proposed to deal with the necessarily large number of input variables to be taken into account in the mathematical regression of the migration energies. The application of the ANN-based AKMC method to the simulation of a thermal annealing experiment in Fe-20%Cr alloy is reported. The results obtained are found to be in better agreement with experiments, as compared to already published simulations, where no atomic relaxation was taken into account and chemical effects were only heuristically allowed for. read less G. Bonny, R. Pasianot, N. Castin, and L. Malerba, “Ternary Fe–Cu–Ni many-body potential to model reactor pressure vessel steels: First validation by simulated thermal annealing,” Philosophical Magazine. 2009. link Times cited: 206 Abstract: In recent years, the development of atomistic models dealing… read more Abstract: In recent years, the development of atomistic models dealing with microstructure evolution and subsequent mechanical property change in reactor pressure vessel steels has been recognised as an important complement to experiments. In this framework, a literature study has shown the necessity of many-body interatomic potentials for multi-component alloys. In this paper, we develop a ternary many-body Fe–Cu–Ni potential for this purpose. As a first validation, we used it to perform a simulated thermal annealing study of the Fe–Cu and Fe–Cu–Ni alloys. Good qualitative agreement with experiments is found, although fully quantitative comparison proved impossible, due to limitations in the used simulation techniques. These limitations are also briefly discussed. 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
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_267721408934_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_BonnyPasianotMalerba_2009_FeNi__MO_267721408934_005
DOI	10.25950/e54b898a https://doi.org/10.25950/e54b898a https://commons.datacite.org/doi.org/10.25950/e54b898a
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_BonnyPasianotMalerba_2009_FeNi__MO_267721408934_004

Verification Check Dashboard

(Click here to learn more about Verification Checks)

Grade	Name	Category	Brief Description	Full Results	Aux File(s)
P All elements claimed by model are supported in at least one of the tested configurations.	vc-species-supported-as-stated	mandatory	The model supports all species it claims to support; see full description.	Results	Files
P Periodic boundary conditions were correctly supported for all configurations that the model was able to compute.	vc-periodicity-support	mandatory	Periodic boundary conditions are handled correctly; see full description.	Results	Files
P Model energy has permutation symmetry for all configurations the model was able to compute.	vc-permutation-symmetry	mandatory	Total energy and forces are unchanged when swapping atoms of the same species; see full description.	Results	Files
B The letter grade B was assigned because the normalized error in the computation was 4.24503e-08 compared with a machine precision of 2.22045e-16. The letter grade was based on 'score=log10(error/eps)', with ranges A=[0, 7.5], B=(7.5, 10.0], C=(10.0, 12.5], D=(12.5, 15.0), F>15.0. 'A' is the best grade, and 'F' indicates failure.	vc-forces-numerical-derivative	consistency	Forces computed by the model agree with numerical derivatives of the energy; see full description.	Results	Files
F The model is C^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: Ni

Species: Fe

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: Fe

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: Fe

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: Fe

Species: Ni

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: Fe

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

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: 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: Ni

Species: Fe

Cubic Crystal Basic Properties Table

Species: Fe

Species: Ni

Tests

Disclaimer From Model Developer

The potential was not stiffened to ZBL. The Fe potential is only suitable to describe alpha-Fe.

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 Fe v004	view	10846
Cohesive energy versus lattice constant curve for bcc Ni v004	view	6714
Cohesive energy versus lattice constant curve for diamond Fe v004	view	7022
Cohesive energy versus lattice constant curve for diamond Ni v004	view	9803
Cohesive energy versus lattice constant curve for fcc Fe v004	view	6455
Cohesive energy versus lattice constant curve for fcc Ni v004	view	6674
Cohesive energy versus lattice constant curve for sc Fe v004	view	9952
Cohesive energy versus lattice constant curve for sc Ni v004	view	6873

ElasticConstantsCrystal__TD_034002468289_000

Elastic constants for arbitrary crystals at zero temperature and pressure v000

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

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Elastic constants for FeNi in AFLOW crystal prototype A2B_cF24_227_c_b at zero temperature and pressure v000		view	94360

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 Fe at zero temperature v006	view	1695
Elastic constants for bcc Ni at zero temperature v006	view	1663
Elastic constants for fcc Fe at zero temperature v006	view	1951
Elastic constants for fcc Ni at zero temperature v006	view	1631
Elastic constants for sc Fe at zero temperature v006	view	3839
Elastic constants for sc Ni at zero temperature v006	view	1408

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 Fe at zero temperature v004		view	1496
Elastic constants for hcp Ni at zero temperature v004		view	1942

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 FeNi in AFLOW crystal prototype A2B_cF24_227_c_b v002	view	326433
Equilibrium crystal structure and energy for FeNi in AFLOW crystal prototype A3B_cF16_225_ac_b v002	view	105054
Equilibrium crystal structure and energy for FeNi in AFLOW crystal prototype A3B_cP4_221_c_a v002	view	67687
Equilibrium crystal structure and energy for FeNi in AFLOW crystal prototype A3B_tI8_139_ad_b v002	view	80762
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_cF4_225_a v002	view	126775
Equilibrium crystal structure and energy for Ni in AFLOW crystal prototype A_cF4_225_a v002	view	52861
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_cI2_229_a v002	view	48122
Equilibrium crystal structure and energy for Ni in AFLOW crystal prototype A_cI2_229_a v002	view	57114
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_hP2_194_c v002	view	81130
Equilibrium crystal structure and energy for Ni in AFLOW crystal prototype A_hP2_194_c v002	view	52314
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_tP28_136_f2ij v002	view	61611
Equilibrium crystal structure and energy for FeNi in AFLOW crystal prototype AB2_cF24_227_a_d v002	view	279095
Equilibrium crystal structure and energy for FeNi in AFLOW crystal prototype AB3_cF16_225_a_bc v002	view	78137
Equilibrium crystal structure and energy for FeNi in AFLOW crystal prototype AB3_cP4_221_a_c v002	view	84590
Equilibrium crystal structure and energy for FeNi in AFLOW crystal prototype AB3_tI8_139_a_bd v002	view	45509
Equilibrium crystal structure and energy for FeNi in AFLOW crystal prototype AB_tP2_123_a_d v002	view	42897

GrainBoundaryCubicCrystalSymmetricTiltRelaxedEnergyVsAngle__TD_410381120771_002

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

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

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

Test	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)
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Ni v000		view	20810545

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 bcc Fe v001	view	6268405
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in bcc Fe v001	view	14700636
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in bcc Fe v001	view	4762672
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in bcc Fe v001	view	28108194
Relaxed energy as a function of tilt angle for a 100 symmetric tilt grain boundary in fcc Fe v001	view	24629412
Relaxed energy as a function of tilt angle for a 100 symmetric tilt grain boundary in fcc Ni v001	view	6840421
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Fe v001	view	184271948
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Ni v001	view	38178045
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Fe v001	view	81868283
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Ni v001	view	22905359
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Fe v001	view	308855807

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 Fe v007	view	1951
Equilibrium zero-temperature lattice constant for bcc Ni v007	view	2335
Equilibrium zero-temperature lattice constant for diamond Fe v007	view	3231
Equilibrium zero-temperature lattice constant for diamond Ni v007	view	2975
Equilibrium zero-temperature lattice constant for fcc Fe v007	view	4031
Equilibrium zero-temperature lattice constant for fcc Ni v007	view	3711
Equilibrium zero-temperature lattice constant for sc Fe v007	view	2655
Equilibrium zero-temperature lattice constant for sc Ni v007	view	2271

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 Fe v005		view	28079
Equilibrium lattice constants for hcp Ni v005		view	19515

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 bcc Fe at 293.15 K under a pressure of 0 MPa v002		view	481404
Linear thermal expansion coefficient of fcc Ni at 293.15 K under a pressure of 0 MPa v002		view	919888

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 Ni v004		view	49615

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 Ni v002		view	6393737

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 bcc Fe v004		view	17914
Broken-bond fit of high-symmetry surface energies in fcc Ni v004		view	31477

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 bcc Fe		view	382679
Monovacancy formation energy and relaxation volume for fcc Ni		view	382311

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 bcc Fe		view	3717835
Vacancy formation and migration energy for fcc Ni		view	1878722

Errors

ElasticConstantsCubic__TD_011862047401_006

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

EquilibriumCrystalStructure__TD_457028483760_002

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_tP1_123_a v002	other	view

LatticeConstantCubicEnergy__TD_475411767977_006

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

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Verification Check	Error Categories	Link to Error page
MemoryLeak__VC_561022993723_004	other	view

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Wiki

The Fe-Fe interactions in this potential are based upon those of  [EAM_Dynamo_MendelevHanSrolovitz_2003Potential2_Fe__MO_769582363439_005](https://openkim.org/cite/MO_769582363439_005) and are identical to those of [EAM_Dynamo_BonnyPasianotCastin_2009_FeCuNi__MO_469343973171_005](https://openkim.org/cite/MO_469343973171_005).  However, as Bonny *et al.* point out, there are two transformations in the EAM paradigm that leave the total energy invariant:

$$
\begin{align}
\hat{T_1} &= \begin{cases}
                         \varphi(r) \rightarrow S \varphi(r)\\
                         F(\rho) \rightarrow F(\rho/S)
                     \end{cases}\\
\hat{T_2} &= \begin{cases}
                         F(\rho) \rightarrow F(\rho) + C \rho\\
                         V(r) \rightarrow V(r) - 2 C \varphi(r)\\
                     \end{cases}
\end{align}
$$

where $$C$$ and $$S$$ are arbitrary constants.  Therefore, the final EAM functions used by the authors is obtained by the following modifications to arrive at an "effective" set of interactions (denoted with the superscript 'eff'):

$$
\begin{align}
V^\mathrm{eff}(r) &= V(r) - 2 C \varphi(r)\\
\varphi^\mathrm{eff} &= S \varphi(r)\\
F^\mathrm{eff} &= F(\rho/S) + C/S\rho
\end{align}
$$

The values of these constants used by the authors to modify EAM_Dynamo_MendelevHanSrolovitz_2003Potential2_Fe__MO_769582363439_005 to describe interactions in pure Fe are $$C$$ = 0.116093429 and $$S$$ = 0.0380008812.  For pure Ni interactions, the authors modify the Voter--Chen potential [1] using the above transformations with $$C$$ = −24.3575774 and $$S$$ = 2.84007616.  For details on how the cross-interactions (Fe/Ni) were fit, please see the source article.

[1] Voter A F and Chen S P, *Mater. Res. Soc. Symp. Proc.* 82 (1987), pp. 175.

EAM_Dynamo_BonnyPasianotMalerba_2009_FeNi__MO_267721408934_005

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FCC Lattice Constant

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SC Lattice Constant

Cubic Crystal Basic Properties Table

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