MEAM Potential for the Cr-Mn system developed by Choi et al. (2017) v002

Won-Mi Choi; Yongmin Kim; Donghyuk Seol; Byeong-Joo Lee

doi:10.25950/45ea3b75

Jump to: Tests | Visualizers | Files | Wiki

MEAM_LAMMPS_ChoiKimSeol_2017_CrMn__MO_671124822359_002

Interatomic potential for Chromium (Cr), Manganese (Mn).
Use this Potential

Title A single sentence description.	MEAM Potential for the Cr-Mn system developed by Choi et al. (2017) v002
Description A short description of the Model describing its key features including for example: type of model (pair potential, 3-body potential, EAM, etc.), modeled species (Ac, Ag, ..., Zr), intended purpose, origin, and so on.	Interatomic potentials for the Cr-Mn binary system has been developed in the framework of the second nearest-neighbor modified embedded-atom method (2NN MEAM) formalism. The potential describes various fundamental alloy behaviors (structural, elastic and thermodynamic behavior of solution and compound phases), mostly in reasonable agreements with experimental data or first-principles calculations.
Species The supported atomic species.	Cr, Mn
Disclaimer A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.	None
Content Origin	http://cmse.postech.ac.kr/home_2nnmeam

Contributor	Yongmin Kim
Maintainer	Yongmin Kim
Developer	Won-Mi Choi Yongmin Kim Donghyuk Seol Byeong-Joo Lee
Published on KIM	2023
How to Cite	This Model originally published in [1] is archived in OpenKIM [2-5]. [1] Choi W-M, Kim Y, Seol D, Lee B-J. Modified embedded-atom method interatomic potentials for the Co-Cr, Co-Fe, Co-Mn, Cr-Mn and Mn-Ni binary systems. Computational Materials Science. 2017;130:121–9. doi:10.1016/j.commatsci.2017.01.002 — (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] Choi W-M, Kim Y, Seol D, Lee B-J. MEAM Potential for the Cr-Mn system developed by Choi et al. (2017) v002. OpenKIM; 2023. doi:10.25950/45ea3b75 [3] Afshar Y, Hütter S, Rudd RE, Stukowski A, Tipton WW, Trinkle DR, et al. The modified embedded atom method (MEAM) potential v002. OpenKIM; 2023. doi:10.25950/ee5eba52 [4] Tadmor EB, Elliott RS, Sethna JP, Miller RE, Becker CA. The potential of atomistic simulations and the Knowledgebase of Interatomic Models. JOM. 2011;63(7):17. doi:10.1007/s11837-011-0102-6 [5] Elliott RS, Tadmor EB. Knowledgebase of Interatomic Models (KIM) Application Programming Interface (API). OpenKIM; 2011. doi:10.25950/ff8f563a Click here to download the above citation in BibTeX format.
Citations This panel presents information regarding the papers that have cited the interatomic potential (IP) whose page you are on. The OpenKIM machine learning based Deep Citation framework is used to determine whether the citing article actually used the IP in computations (denoted by "USED") or only provides it as a background citation (denoted by "NOT USED"). For more details on Deep Citation and how to work with this panel, click the documentation link at the top of the panel. The word cloud to the right is generated from the abstracts of IP principle source(s) (given below in "How to Cite") and the citing articles that were determined to have used the IP in order to provide users with a quick sense of the types of physical phenomena to which this IP is applied. The bar chart shows the number of articles that cited the IP per year. Each bar is divided into green (articles that USED the IP) and blue (articles that did NOT USE the IP). Users are encouraged to correct Deep Citation errors in determination by clicking the speech icon next to a citing article and providing updated information. This will be integrated into the next Deep Citation learning cycle, which occurs on a regular basis. OpenKIM acknowledges the support of the Allen Institute for AI through the Semantic Scholar project for providing citation information and full text of articles when available, which are used to train the Deep Citation ML algorithm.	This panel provides information on past usage of this interatomic potential (IP) powered by the OpenKIM Deep Citation framework. The word cloud indicates typical applications of the potential. The bar chart shows citations per year of this IP (bars are divided into articles that used the IP (green) and those that did not (blue)). The complete list of articles that cited this IP is provided below along with the Deep Citation determination on usage. See the Deep Citation documentation for more information. 59 Citations (49 used) Show Model Used Show All Help us to determine which of the papers that cite this potential actually used it to perform calculations. If you know, click the . B. Waters, D. S. Karls, I. Nikiforov, R. Elliott, E. Tadmor, and B. Runnels, “Automated determination of grain boundary energy and potential-dependence using the OpenKIM framework,” Computational Materials Science. 2022. link Times cited: 5 A. Egorov, A. Subramanyam, Z. Yuan, R. Drautz, and T. Hammerschmidt, “Magnetic bond-order potential for iron-cobalt alloys,” Physical Review Materials. 2022. link Times cited: 0 Abstract: For large-scale atomistic simulations of magnetic materials,… read more Abstract: For large-scale atomistic simulations of magnetic materials, the interplay of atomic and magnetic degrees of freedom needs to be described with high computational efficiency. Here we present an analytic bond-order potential (BOP) for iron-cobalt, an interatomic potential based on a coarse-grained description of the electronic structure. We fitted BOP parameters to magnetic and non-magnetic density-functional theory (DFT) calculations of Fe, Co, and Fe-Co bulk phases. Our BOP captures the electronic structure of magnetic and non-magnetic Fe-Co phases. It provides accurate predictions of structural stability, elastic constants, phonons, point and planar defects, and structural transformations. It also reproduces the DFT-predicted sequence of stable ordered phases peculiar to Fe-Co and the stabilization of B2 against disordered phases by magnetism. Our Fe-Co BOP is suitable for atomistic simulations with thousands and millions of atoms. read less M. Muralles, J. T. Oh, and Z. Chen, “Modified embedded atom method interatomic potentials for the Fe-Al, Fe-Cu, Fe-Nb, Fe-W, and Co-Nb binary alloys,” Computational Materials Science. 2023. link Times cited: 0 Y. Deng, H. Li, H. Zong, X. Ding, and J. Sun, “MD simulation of primary radiation damage in fcc multi-principal element alloys: Effect of compositional undulation,” Journal of Nuclear Materials. 2023. link Times cited: 0 S. Kuzovchikov, I. Bajenova, A. Khvan, and V. Cheverikin, “Investigation of the hardness and enthalpy of formation of the Sigma phase and the phase equilibria in the Cr-Co-Mn system,” Journal of Alloys and Compounds. 2023. link Times cited: 1 O. Klimanova, T. Miryashkin, and A. Shapeev, “Accurate melting point prediction through autonomous physics-informed learning,” Physical Review B. 2023. link Times cited: 0 Abstract: We present an algorithm for computing melting points by auto… read more Abstract: We present an algorithm for computing melting points by autonomously learning from coexistence simulations in the NPT ensemble. Given the interatomic interaction model, the method makes decisions regarding the number of atoms and temperature at which to conduct simulations, and based on the collected data predicts the melting point along with the uncertainty, which can be systematically improved with more data. We demonstrate how incorporating physical models of the solid-liquid coexistence evolution enhances the algorithm's accuracy and enables optimal decision-making to effectively reduce predictive uncertainty. To validate our approach, we compare the results of 20 melting point calculations from the literature to the results of our calculations, all conducted with same interatomic potentials. Remarkably, we observe significant deviations in about one-third of the cases, underscoring the need for accurate and reliable algorithms for materials property calculations. read less I. A. Alhafez, O. Deluigi, D. Tramontina, C. Ruestes, E. Bringa, and H. Urbassek, “Simulated nanoindentation into single-phase fcc Fe\documentclass[12pt]minimal \usepackageamsmath \usepackagewasysym \usepackageamsfonts \usepackageamssymb \usepackageamsbsy \usepackagemathrsfs \usepackageupgreek \setlength\oddsidemargin-69pt \begindocument$_x$\enddocument,” Scientific Reports. 2023. link Times cited: 1 T. Li et al., “Molecular Dynamics Investigation on Micro-Friction Behavior of Cylinder Liner-Piston Ring Assembly,” Tribology Letters. 2023. link Times cited: 0 S. Guo et al., “Simultaneously optimizing the strength and ductility of high-entropy alloys by magnetic field-assisted additive manufacturing,” Journal of Alloys and Compounds. 2023. link Times cited: 3 K. Gan, D. Yan, and Y. Zhang, “Probing the atomic-scale deformation mechanism of single-crystal nanowires coated with a multi-component alloyed shell,” Computational Materials Science. 2023. link Times cited: 1 J. Ji and B.-J. Lee, “Analyzing the effect of Li/Ni intermixing on Ni-rich layered cathode structures using atomistic simulation of the Li–Ni–Mn–Co–O quinary system,” Journal of Power Sources. 2023. link Times cited: 1 F. Tan, L. Li, J. Li, B. Liu, P. Liaw, and Q. Fang, “Multiscale modelling of irradiation damage behavior in high entropy alloys,” Advanced Powder Materials. 2023. link Times cited: 3 Z. Chen et al., “The interactions between dislocations and displacement cascades in FeCoCrNi concentrated solid-solution alloy and pure Ni,” Journal of Nuclear Materials. 2023. link Times cited: 0 Y. Zhou et al., “Influence of icosahedron and icosahedron-like on plastic deformation of Co50Mn50 alloy under compressive conditions,” Journal of Non-Crystalline Solids. 2022. link Times cited: 3 A. Babushkin and A. N. Kupriyanov, “Molecular Dynamics Study on Mechanical Stress Formation during Polycrystalline Cr-Film Growth,” Journal of Surface Investigation: X-ray, Synchrotron and Neutron Techniques. 2022. link Times cited: 0 M. Muralles, J. Oh, and Z. Chen, “Influence of V addition on the mechanical properties of FeCo alloys: a molecular dynamics study,” Materialia. 2022. link Times cited: 1 S. Guo et al., “Overcoming strength-ductility trade-off in high-entropy alloys by tuning chemical short-range order and grain size,” Intermetallics. 2022. link Times cited: 7 L. Wei, F. Zhou, S. Wang, W. Hao, Y. Liu, and J. Zhu, “Description of crystal defect properties in BCC Cr with extended Finnis–Sinclair potential,” Multidiscipline Modeling in Materials and Structures. 2022. link Times cited: 0 Abstract: PurposeThe purpose of this study is to propose extended pote… read more Abstract: PurposeThe purpose of this study is to propose extended potentials and investigate the applicability of extended Finnis–Sinclair (FS) potential to Cr with the unit cell structure of body-centered cubic (BCC Cr).Design/methodology/approachThe parameters of each potential are determined by fitting the elastic constants, cohesive energy and mono-vacancy formation energy. Furthermore, the ability of the extended FS potential to describe the crystal defect properties is tested. Finally, the applicability of reproducing the thermal properties of Cr is discussed.FindingsThe internal relationship between physical properties and potential function is revealed. The mathematical relationship between physical properties and potential function is derived in detail. The extended FS potential performs well in reproducing physical properties of BCC Cr, such as elastic constants, cohesive energy, surface energy and the properties of vacancy et al. Moreover, good agreement is obtained with the experimental data for predicting the melting point, specific heat and coefficient of thermal expansion.Originality/valueIn this study, new extended potentials are proposed. The extended FS potential is able to reproduce the physical and thermal properties of BCC Cr. Therefore, the new extended potential can be used to describe the crystal defect properties of BCC Cr. read less R. Fereidonnejad, A. O. Moghaddam, and M. Moaddeli, “Modified embedded-atom method interatomic potentials for Al-Ti, Al-Ta, Al-Zr, Al-Nb and Al-Hf binary intermetallic systems,” Computational Materials Science. 2022. link Times cited: 5 Y. Li, D. Yang, and W. Qiang, “First-principles study of the effects of solutes on long-range order degree, self-diffusions and antiphase boundary energies in ordered FeCo alloy,” Journal of Magnetism and Magnetic Materials. 2022. link Times cited: 6 F. Wu et al., “Lattice inversion potential with neural network corrections for metallic systems,” Computational Materials Science. 2022. link Times cited: 0 M. Muralles, J. Oh, and Z. Chen, “Molecular Dynamics Study of Feco Phase Transitions and Thermal Properties Based on an Improved 2nn Meam Potential,” SSRN Electronic Journal. 2022. link Times cited: 3 Y. Cui, Z. Chen, S. Gu, W. Yang, and Y. Ju, “Investigating size dependence in nanovoid-embedded high-entropy-alloy films under biaxial tension,” Archive of Applied Mechanics. 2022. link Times cited: 4 S. Oh, X.-gang Lu, Q. Chen, and B.-J. Lee, “Pressure dependence of thermodynamic interaction parameters for binary solid solution phases: An atomistic simulation study,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2021. link Times cited: 0 S. Chen, Z. Aitken, V. Sorkin, Z. Yu, Z. Wu, and Y.-W. Zhang, “Modified Embedded‐Atom Method Potentials for the Plasticity and Fracture Behaviors of Unary HCP Metals,” Advanced Theory and Simulations. 2021. link Times cited: 3 Abstract: Modified embedded‐atom method (MEAM) potentials have been wi… read more Abstract: Modified embedded‐atom method (MEAM) potentials have been widely used in molecular dynamics (MD) simulations to describe the interatomic interactions in metallic systems. However, conventional MEAM potentials are almost exclusively fit to a limited number of key single‐value properties, limiting the predictability of MD simulations, especially for complex hexagonal‐close‐packed (HCP) metals with multiple slip systems. Here, three MEAM potentials for unary HCP metals (Mg, Co, and Ti) are fit to conventional target properties, as well as continuous‐energy curves and their gradients obtained from density‐functional theory calculations. These targets include the lattice parameters, cohesive energy, elastic constants, and surface energies as well as the cohesive energy curve, basal plane decohesion energy curve, and generalized stacking fault energy curves for basal, prismatic, pyramidal I, and pyramidal II planes. These interatomic potentials demonstrate excellent reproduction of relevant properties and enable accurate MD simulations of volumetric and plastic deformations, as well as fracture in Mg, Co, and Ti HCP metals. Importantly, the interatomic potentials demonstrate better performance than all existing EAM/MEAM potentials readily available from the literature. read less N. Dhariwal, A. S. M. Miraz, W. Meng, B. Ramachandran, and C. Wick, “Impact of metal/ceramic interactions on interfacial shear strength: Study of Cr/TiN using a new modified embedded-atom potential,” Materials & Design. 2021. link Times cited: 4 S. Paul, M. Muralles, D. Schwen, M. Short, and K. Momeni, “A Modified Embedded-Atom Potential for Fe-Cr-Si Alloys,” The Journal of Physical Chemistry C. 2021. link Times cited: 5 Y. L. Li, X. Cheng, W. Duan, and W. Qiang, “Improved ductility by coupled motion of grain boundaries in nanocrystalline B2-FeCo alloys,” Computational Materials Science. 2021. link Times cited: 7 M. Meesa, K. Gupta, and K. R. Mangipudi, “A molecular dynamics study of the influence of nucleation conditions on the phase selection in Fe50Mn30Cr10Co10 high entropy alloy,” Materialia. 2021. link Times cited: 1 W. Choi et al., “Computational design of V-CoCrFeMnNi high-entropy alloys: An atomistic simulation study,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2021. link Times cited: 12 S.-feng Yang et al., “Microstructure and strengthening mechanisms in FCC-structured single-phase TiC–CoCrFeCuNiAl0.3 HEACs with deformation twinning,” Materials Science and Engineering A-structural Materials Properties Microstructure and Processing. 2021. link Times cited: 5 Z. Aitken, V. Sorkin, Z. Yu, S. Chen, Z. Wu, and Y.-W. Zhang, “Modified embedded-atom method potentials for the plasticity and fracture behaviors of unary fcc metals,” Physical Review B. 2021. link Times cited: 5 S. Guo, H. Chen, and M. Wang, “Research on the dislocation differences of CoCrFeMnNi with different local chemical orders during room temperature tensile test,” Journal of Alloys and Compounds. 2021. link Times cited: 12 K. Hsieh, Y.-Y. Lin, C.-H. Lu, J. Yang, P. Liaw, and C.-L. Kuo, “Atomistic simulations of the face-centered-cubic-to-hexagonal-close-packed phase transformation in the equiatomic CoCrFeMnNi high entropy alloy under high compression,” Computational Materials Science. 2020. link Times cited: 21 Abstract: We performed the modified-embedded-atom-method (MEAM) based … read more Abstract: We performed the modified-embedded-atom-method (MEAM) based molecular dynamics (MD) simulations to investigate the plastic deformation and phase transformation behaviors in the CoCrFeMnNi HEA under high compression at room temperature. Our MD simulations revealed that the stress-induced phase transformations in the CoCrFeMnNi HEA are strongly crystal orientation-dependent. The [0 0 1] uniaxial compression can induce the significant face-centered-cubic (fcc) -to-hexagonal-close-packed (hcp) phase transformation via successive emissions of partial dislocations from the extended stacking faults, twin boundaries and hcp-lamellas created during the early stage of deformation. As for the [1 1 0] and [1 1 1] uniaxial compressions, however, the transformed hcp atoms can simply form the intrinsic/extrinsic stacking faults. Although the [0 0 1] uniaxial compression produced a much lower dislocation density than the other two systems, it induced much more constituents transformed into the hcp atoms at the end of phase transformation. Our results clearly indicated that the deformation twin boundaries and extended hcp-lamellas play a critical role in facilitating the stress-induced fcc-to-hcp phase transformation in the CoCrFeMnNi HEA. Furthermore, it was found that the phase transformation in the CoCrFeMnNi HEA can be effectively facilitated by a large deviatoric compressive stress while it may tend to be significantly retarded by a hydrostatic compression. Our results also showed that the plastic deformation behaviors in Ni under high compression are very similar to those occurred in the CoCrFeMnNi HEA though nearly all the hcp atoms can simply constitute the intrinsic/extrinsic stacking faults without the formation of any bulk hcp phase in the fcc lattice. The main discrepancy in the phase transformation behaviors between the Ni and CoCrFeMnNi HEA can be largely attributed to the much lower stacking fault energy of the CoCrFeMnNi HEA than other fcc metals. read less J. Li et al., “Unveiling the atomic-scale origins of high damage tolerance of single-crystal high entropy alloys,” Physical Review Materials. 2020. link Times cited: 13 Abstract: High entropy alloys (HEAs) exhibit an unusual combination of… read more Abstract: High entropy alloys (HEAs) exhibit an unusual combination of high fracture strength and ductility. However, atomic mechanisms responsible for crack propagation in HEAs are still not clear, which limits further improving the damage tolerance. Here we investigate effect of crystal orientation on the crack-tip behaviors in single-crystal HEA CrMnFeCoNi using atomic simulations to explore fracture micromechanism. The formation of deformation twinning and activation of multislip systems are observed during the propagation crack with the $(001)\ensuremath{\langle}110\ensuremath{\rangle}$ orientation, consistent with the previous experiments. Under the $(\overline{1}10)\ensuremath{\langle}110\ensuremath{\rangle}$ orientation, the amorphous region takes place throughout the crack growth, and is difficult to occur in traditional metal materials. Dissimilarly, for the $(1\overline{1}\overline{1})\ensuremath{\langle}110\ensuremath{\rangle}$ orientation, the blunting and slip bands occur at the front of the crack tip by switching the slip mode from the planar to wavy slip, observed in recent transmission electron microscopy experiments. The chemical disorder leads to the obvious fluctuation of flow stress, but hardly affects the deformation mechanism at the crack tip. Compared to traditional metals and alloys, the high local stress concentration induced by coupling effect of severe lattice distortion and tension strain leads to the structure transformation from crystallization to amorphization at the crack tip in HEA. While the presented atomic simulations and the associated conclusions are based on CrMnFeCoNi HEA, it is believed that the current deformation mechanism at crack tip could also be applied to other face-centered-cubic HEA. read less Y. Cui, Y. Toku, Y. Kimura, and Y. Ju, “High-strain-rate void growth in high entropy alloys: Suppressed dislocation emission = suppressed void growth,” Scripta Materialia. 2020. link Times cited: 16 Y. Cui, Z. Chen, and Y. Ju, “Fracture of Void-Embedded High-Entropy-Alloy Films: A Comprehensive Atomistic Study,” EngRN: Electrochemical Energy Engineering (EngRN) (Topic). 2020. link Times cited: 10 Abstract: Comprehensive molecular dynamics (MD) simulations are perfor… read more Abstract: Comprehensive molecular dynamics (MD) simulations are performed to study the stress response and deformation mechanism in void-embedded, single-crystal and polycrystalline, high-entropy-alloy (HEA) films under uniaxial tensile loading. Our results reveal that certain void-embedded HEA films can be, by far, superior to pure Ni in terms of tensile ductility and the resistance to crack propagation. The fracture strain of the 10%Co CoCrFeMnNi and the equiatomic CoFeMnNi, respectively, doubles or triples that of the equiatomic CoCrFeMnNi, which still doubles that of pure Ni. Regarding the deformation mechanism, high tensile ductility of HEAs can be attributed to the formation of partial dislocations, nanotwinning and the impediment of the otherwise glissile dislocations due to the lattice distortion effect. The ultimate tensile strength of HEA film shows better resistance against stress deterioration due to elliptical voids. The stress response of the void-embedded, polycrystalline Ni films obeys the reverse Hall–Petch effect, while the void-embedded, polycrystalline HEA films do not. read less D. Foley et al., “Simultaneous Twinning and Microband Formation Under Dynamic Compression in a High Entropy Alloy with a Complex Energetic Landscape,” ChemRN: Metals & Alloys (Topic). 2020. link Times cited: 47 Abstract: High entropy alloys (HEAs) have been the subject of signific… read more Abstract: High entropy alloys (HEAs) have been the subject of significant research in recent years due in part to their excellent mechanical properties and unique microstructure. Chemical disorder in these alloys is thought to lead to a complex energetic environment that affects the nucleation and movement of dislocations. In this study the development of deformation substructures is assessed in the Cantor HEA (CoCrFeMnNi) due to quasistatic and dynamic compression. Scanning and transmission electron microscopy (SEM/TEM) techniques are used to image and quantify dislocation density. When increasing the strain rate from 10−3 s−1 to 5000 s−1 we observe an increase in the overall dislocation density which leads to the formation of deformation twins. Further at a rate of 8000 s−1, both deformation twins and microbands become operative plasticity modes, which are usually associated with different extremes of stacking fault energy. To relate this plastic response to chemical disorder, atomistic calculations are used to compute the generalized stacking fault energy curve and approximate the temperature dependence of the intrinsic stacking fault energy for the Cantor alloy, which reveals significant local variation in these critical energetic parameters associated with dislocation and twinning behaviors. read less A. Korchuganov, I. Lutsenko, and K. Zolnikov, “Influence of chemical composition of the surface layer on the nucleation of plasticity in CoCrFeMnNi high-entropy alloys,” Journal of Physics: Conference Series. 2020. link Times cited: 2 Abstract: The role of segregation of chemical elements upon free surfa… read more Abstract: The role of segregation of chemical elements upon free surfaces in the peculiarities of the plastic deformation mechanisms of thin films of the high-entropy CoCrFeMnNi alloy was clarified using a combined simulation of the Metropolis Monte Carlo and molecular dynamics. Irrespectively of surface orientation and stoichiometric composition of alloy Mn escapes to free surface and Fe goes to the bulk of the films. Ni also enriches the (111) surface while Co content is reduced. It is shown that for different compositions segregation reduces or decreases the elastic limit of the samples. In Co10Cr10Fe30Mn30Ni20 for all considered free surfaces, segregation equally influences the type and volume fraction of the formed defects. In Co30Cr30Fe10Mn10Ni20, they may remain the same or the mechanism of plastic deformation may change drastically in samples with segregation depending on the orientation of the free surface. Despite the redistribution of the volume fractions of various type defects, in general, the main mechanism for the development of plasticity in samples both before and after segregation is the growth of the hcp-bands. Change of defect structure in samples with surface segregation compared to samples with random distribution of elements is not necessary related to change of elastic limit. read less Y. Lin et al., “Enhanced Radiation Tolerance of the Ni-Co-Cr-Fe High-Entropy Alloy as Revealed from Primary Damage,” MatSciRN: Other Mechanical Properties & Deformation of Materials (Topic). 2020. link Times cited: 93 Abstract: High-entropy alloys (HEAs) have received much attention for … read more Abstract: High-entropy alloys (HEAs) have received much attention for the development of nuclear materials because of their excellent irradiation tolerance. In the present study, the generation and evolution of irradiation-induced defects in the NiCoCrFe HEA were investigated by molecular dynamics (MD) simulations to understand the mechanisms of its irradiation tolerance compared with bulk Ni. The displacement cascades were simulated for the energies of primary knock-on atoms (PKA) ranging from 10 to 50 keV to understand the irradiation resistance in HEAs. In general, there are more displaced atoms produced in the thermal spike phase, but fewer defects survived at the end of the cascades in the NiCoCrFe alloy than in Ni. Both interstitial and vacancy clusters increase in size or number with increasing PKA energy in both materials, but they do so more slowly in the NiCoCrFe HEA. The delayed damage accumulations in the NiCoCrFe HEA are attributed to the high defect recombination caused by the following two mechanisms. First, the enhanced thermal spike and the low thermal conductivity of HEAs for heat dissipation result in the higher efficiency of defect recombination. Furthermore, the substantially small binding energies of interstitial loops in the NiCoCrFe HEA, as compared with those in Ni, are responsible for the delayed interstitial clustering in the NiCoCrFe HEA. read less I. A. Alhafez, C. Ruestes, E. Bringa, and H. Urbassek, “Nanoindentation into a high-entropy alloy – An atomistic study,” Journal of Alloys and Compounds. 2019. link Times cited: 80 Y. Wang et al., “Crystallization kinetics of Ni-Mn alloy thin film using molecular dynamics simulation,” Ferroelectrics. 2019. link Times cited: 0 Abstract: The crystallization kinetics of Ni-Mn alloy thin films is in… read more Abstract: The crystallization kinetics of Ni-Mn alloy thin films is investigated by molecular dynamic simulation. The results show all curves have a single exothermic peak representing crystallization, and the isothermal peaks are significantly shifted to higher temperatures with increasing heating rate. When heating rate is 5 1010 K/s, the crystallization temperatures is found at 715 K. Moreover, we find the crystallization behavior is a two-dimensional grown. Meanwhile, the Radial Distribution Function curves show crystallizing degree at different temperatures and the temperature is 600 K has a crystallization volume fraction is 28%. This work reveals the mechanism of the nucleation and growth in crystallization process. read less A. Korchuganov and I. S. Lucenko, “Peculiarities of chemical element redistribution near free surfaces in CoCrFeMnNi high-entropy alloys,” IOP Conference Series: Materials Science and Engineering. 2019. link Times cited: 1 Abstract: Based on molecular dynamics and Monte Carlo simulation, the … read more Abstract: Based on molecular dynamics and Monte Carlo simulation, the distribution of chemical elements near free surfaces of various crystallographic orientations in high-entropy CoCrFeMnNi alloys was investigated. It is shown that for studied stoichiometric compositions of the alloy it has a different character and differently affects the mechanical characteristics and the defect structure of alloys subjected to uniaxial tension. This is due to the different influence of each element on the elastic modulus of the alloy. Segregation has a greater effect on the Young’s modulus and elastic limit for Co30Cr30Fe10Mn10Ni20, while the resulting defect structures have more differences for Co10Cr10Fe30Mn30Ni20. read less A. Korchuganov, “Atomic-scale mechanisms of single crystal plasticity in CoCrFeMnNi high-entropy alloys,” Journal of Physics: Conference Series. 2019. link Times cited: 5 Abstract: The behavior of CoCrFeMnNi high-entropy alloys under mechani… read more Abstract: The behavior of CoCrFeMnNi high-entropy alloys under mechanical loading was studied within the framework of the molecular dynamics method. The mechanisms of local structural transformations of the crystal lattice responsible for the onset of plasticity at the tension of CoCrFeMnNi single crystals were determined. A crystallographic analysis of the structure and identification of the defects formed was carried out. Irrespectively on stoichiometric composition of samples the plasticity is realized by the nucleation, growth and intersection of intrinsic stacking faults. Rearrangement of fcc lattice to bcc structure in the regions where the local atom fraction of Fe, Mn and Ni is above average was found to be the mechanism of stacking fault formation. The effect of the stoichiometric composition and crystallographic orientation of single-crystal CoCrFeMnNi samples upon the structural rearrangements at the nucleation and development of plastic deformation under tension was studied. read less M. Widom, “Modeling the structure and thermodynamics of high-entropy alloys,” Journal of Materials Research. 2018. link Times cited: 72 Abstract: High-entropy and multiprincipal element alloys present excit… read more Abstract: High-entropy and multiprincipal element alloys present exciting opportunities and challenges for computational modeling of their structure and phase stability. Recent interest has catalyzed rapid development of techniques and equally rapid growth of new results. This review surveys the essential concepts of thermodynamics and total energy calculation, and the bridge between them provided by statistical mechanics. Specifically, we review the electronic density functional theory of alloy total energy as applied to supercells and special quasirandom structures. We contrast these with the coherent potential approximation and semi-empirical approximations. Statistical mechanical approaches include cluster expansions, hybrid Monte Carlo/molecular dynamics simulations, and extraction of entropy from correlation functions. We also compare first-principles approaches with Calculation of Phase Diagrams (CALPHAD) and highlight the need to augment experimental databases with first-principles derived data. Numerous example applications are given highlighting recent progress utilizing the concepts and methods that are introduced. read less M. Jang, S. Praveen, H. Sung, J. Bae, J. Moon, and H.-S. Kim, “High-temperature tensile deformation behavior of hot rolled CrMnFeCoNi high-entropy alloy,” Journal of Alloys and Compounds. 2018. link Times cited: 73 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 A. Korchuganov, “Formation of defect structure at the atomic level under mechanical loading of CoCrFeMnNi high-entropy alloys.” 2018. link Times cited: 4 A. Korchuganov and I. Lutsenko, “Molecular dynamics research of mechanical, diffusion and thermal properties of CoCrFeMnNi high-entropy alloys.” 2018. link Times cited: 11 S. Oh, J.-S. Kim, C. S. Park, and B.-J. Lee, “Second nearest-neighbor modified embedded-atom method interatomic potentials for the Mo-M (M = Al, Co, Cr, Fe, Ni, Ti) binary alloy systems,” Computational Materials Science. 2021. link Times cited: 5 S. Oh, D. Seol, and B.-J. Lee, “Second nearest-neighbor modified embedded-atom method interatomic potentials for the Co-M (M = Ti, V) binary systems,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2020. link Times cited: 10 J. Wang, H. Kwon, H. S. Kim, and B. Lee, “A neural network model for high entropy alloy design,” npj Computational Materials. 2023. link Times cited: 1 Y. Li et al., “Molecular dynamics simulation of the transformation of Fe-Co alloy by machine learning force field based on atomic cluster expansion,” Chemical Physics Letters. 2023. link Times cited: 0 Y. Cui, Y. Toku, and Y. Ju, “Nanotwinning and tensile behavior in cold-welded high-entropy-alloy nanowires,” Nanotechnology. 2021. link Times cited: 8 Abstract: Since the fabrication technique for high-entropy alloy (HEA)… read more Abstract: Since the fabrication technique for high-entropy alloy (HEA) nanowires/nanopillars is still in its infancy, neither experimental nor modeling analyses of their cold-welding performance have been reported. Based on insights accumulated in our previous experiments and simulations regarding cold-welded metallic nanowires, in this study, the cold-welding performance of HEA nanowires is probed by atomistic simulations. Among different materials, our simulations reveal that extensively twinned structures are formed in CoCrMnFeNi samples, but not in CoCrCuFeNi or Ni samples. The larger fracture strain in certain HEAs is due to the improved ductility around the fracturing area as well as multiple twinning. Unlike in Ni samples, the fracture strains in HEA samples, regardless of being cuboid or cylindrical, are improved by shrinking the sample size. Among different orientations, the [010]-direction monocrystalline nanowires fail at a strain over 0.6, which is almost double that of the [111] direction. The fracture strains in polycrystalline HEA samples are, on average, larger than those in polycrystalline Ni samples. Furthermore, fracture strains in randomly generated polycrystalline HEA samples are more predictable than those in polycrystalline Ni samples with identical grain configurations. As previously reported, dislocation emission is still a prerequisite to fracture in all cold-welded samples. read less Z. Aitken, V. Sorkin, and Y.-W. Zhang, “Atomistic modeling of nanoscale plasticity in high-entropy alloys,” Journal of Materials Research. 2019. link Times cited: 32 Abstract: Lattice structures, defect structures, and deformation mecha… read more Abstract: Lattice structures, defect structures, and deformation mechanisms of high-entropy alloys (HEAs) have been studied using atomistic simulations to explain their remarkable mechanical properties. These atomistic simulation techniques, such as first-principles calculations and molecular dynamics allow atomistic-level resolution of structure, defect configuration, and energetics. Following the structure–property paradigm, such understandings can be useful for guiding the design of high-performance HEAs. Although there have been a number of atomistic studies on HEAs, there is no comprehensive review on the state-of-the-art techniques and results of atomistic simulations of HEAs. This article is intended to fill the gap, providing an overview of the state-of-the-art atomistic simulations on HEAs. In particular, we discuss how atomistic simulations can elucidate the nanoscale mechanisms of plasticity underlying the outstanding properties of HEAs, and further present a list of interesting problems for forthcoming atomistic simulations of HEAs. read less H. Wang, J. Zhao, W. Liu, and B. Wei, “An anomalous thermal expansion phenomenon induced by phase transition of Fe-Co-Ni alloys,” Journal of Applied Physics. 2018. link Times cited: 5 Abstract: The thermal expansion and the phase transition of Fe-15.6 wt… read more Abstract: The thermal expansion and the phase transition of Fe-15.6 wt. %Co-12 wt. %Ni single-phase solid solution alloy were systematically investigated by thermal analysis experiments and molecular dynamics simulations. The coefficient of thermal expansion (CTE) was accurately measured in the temperature range of 300-1580 K. The eccentric changes of thermal expansion ranging from 900 to 1150 K were verified from the incomplete transformation of α-Fe phase to γ-Fe phase by differential scanning calorimetry (DSC) and in situ X-ray diffraction experiments. The CTE of α-Fe phase increases nonlinearly from 9.29 × 10−6 to 1.278 × 10−5 K−1 in the range of 300-900 K, which is in good agreement with the results obtained by molecular dynamics simulation, whereas the CTE of γ-Fe phase increases linearly from 2.024 × 10−5 to 2.398 × 10−5 K−1 in the range of 1150-1580 K. Meanwhile, the visual atomic positions at different temperatures indicate that thermal expansion is attributed to the anharmonic vibration and short-range diffusion of atoms when the temperature exceeds a certain value. Furthermore, the Curie temperature is determined as 725 K by the thermal expansion and DSC experiments. Additionally, the isothermal sections of the Fe-rich corner [Fe-5x wt. %Co-5y wt. %Ni(2 ≤ x + y ≤ 8)] in Fe-Co-Ni non-equilibrium ternary phase diagram at 300 K are derived by X-ray diffraction. Moreover, the CTE ranging from 300 to 1700 K of the Fe-rich corner in Fe-Co-Ni ternary phase diagram was predicted theoretically on the basis of the molecular dynamics method.The thermal expansion and the phase transition of Fe-15.6 wt. %Co-12 wt. %Ni single-phase solid solution alloy were systematically investigated by thermal analysis experiments and molecular dynamics simulations. The coefficient of thermal expansion (CTE) was accurately measured in the temperature range of 300-1580 K. The eccentric changes of thermal expansion ranging from 900 to 1150 K were verified from the incomplete transformation of α-Fe phase to γ-Fe phase by differential scanning calorimetry (DSC) and in situ X-ray diffraction experiments. The CTE of α-Fe phase increases nonlinearly from 9.29 × 10−6 to 1.278 × 10−5 K−1 in the range of 300-900 K, which is in good agreement with the results obtained by molecular dynamics simulation, whereas the CTE of γ-Fe phase increases linearly from 2.024 × 10−5 to 2.398 × 10−5 K−1 in the range of 1150-1580 K. Meanwhile, the visual atomic positions at different temperatures indicate that thermal expansion is attributed to the anharmonic vibration and short-range di... read less K. Yang, L. Lang, H. Deng, F. Gao, and W. Hu, “Modified analytic embedded atom method potential for chromium,” Modelling and Simulation in Materials Science and Engineering. 2018. link Times cited: 5 Abstract: In the present paper, we have developed a modified analytic … read more Abstract: In the present paper, we have developed a modified analytic embedded atom method potential for chromium. To solve the problem of a negative Cauchy relation for body-centered cubic metal at zero Kelvin temperature, a modification term is added to the total energy. Compared with available interatomic potentials, the present one is easier to be extended because of its analytic form. The fitted or input parameters are all well reproduced, and the properties beyond the fitting range (such as Cauchy relation, melting point and self-interstitial atom formation energies) are also well predicted. We have also studied the relation between the stacking faults energy and 1 2 〈 111 〉 screw dislocation core structure with different potentials. Especially, only our potential predicts a compact core structure, which agrees with the results obtained by density functional theory calculations. read less W. Choi, Y. Jo, S. Sohn, S. Lee, and B.-J. Lee, “Understanding the physical metallurgy of the CoCrFeMnNi high-entropy alloy: an atomistic simulation study,” npj Computational Materials. 2018. link Times cited: 436 I. Toda-Caraballo, J. Wróbel, D. Nguyen-Manh, P. Pérez, and P. Rivera-Díaz-del-Castillo, “Simulation and Modeling in High Entropy Alloys,” JOM. 2017. link Times cited: 27
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_671124822359_002
Extended KIM ID The long form of the KIM ID including a human readable prefix (100 characters max), two underscores, and the Short KIM ID. Extended KIM IDs can only contain alpha-numeric characters (letters and digits) and underscores and must begin with a letter.	MEAM_LAMMPS_ChoiKimSeol_2017_CrMn__MO_671124822359_002
DOI	10.25950/45ea3b75 https://doi.org/10.25950/45ea3b75 https://commons.datacite.org/doi.org/10.25950/45ea3b75
KIM Item Type Specifies whether this is a Portable Model (software implementation of an interatomic model); Portable Model with parameter file (parameter file to be read in by a Model Driver); Model Driver (software implementation of an interatomic model that reads in parameters).	Portable Model using Model Driver MEAM_LAMMPS__MD_249792265679_002
Driver	MEAM_LAMMPS__MD_249792265679_002
KIM API Version	2.2
Potential Type	meam

Previous Version	MEAM_LAMMPS_ChoiKimSeol_2017_CrMn__MO_671124822359_001

Verification Check Dashboard

(Click here to learn more about Verification Checks)

Grade	Name	Category	Brief Description	Full Results	Aux File(s)
P All elements claimed by model are supported in at least one of the tested configurations.	vc-species-supported-as-stated	mandatory	The model supports all species it claims to support; see full description.	Results	Files
P Periodic boundary conditions were correctly supported for all configurations that the model was able to compute.	vc-periodicity-support	mandatory	Periodic boundary conditions are handled correctly; see full description.	Results	Files
P Model energy has permutation symmetry for all configurations the model was able to compute.	vc-permutation-symmetry	mandatory	Total energy and forces are unchanged when swapping atoms of the same species; see full description.	Results	Files
B The letter grade B was assigned because the normalized error in the computation was 9.95165e-09 compared with a machine precision of 2.22045e-16. The letter grade was based on 'score=log10(error/eps)', with ranges A=[0, 7.5], B=(7.5, 10.0], C=(10.0, 12.5], D=(12.5, 15.0), F>15.0. 'A' is the best grade, and 'F' indicates failure.	vc-forces-numerical-derivative	consistency	Forces computed by the model agree with numerical derivatives of the energy; see full description.	Results	Files
F The model is C^0 continuous. This means that the model has continuous energy, but a discontinuous first derivative.	vc-dimer-continuity-c1	informational	The energy versus separation relation of a pair of atoms is C1 continuous (i.e. the function and its first derivative are continuous); see full description.	Results	Files
P Model energy and forces are invariant with respect to rigid-body motion (translation and rotation) for all configurations the model was able to compute.	vc-objectivity	informational	Total energy is unchanged and forces transform correctly under rigid-body translation and rotation; see full description.	Results	Files
P Model energy has inversion symmetry for all configurations the model was able to compute.	vc-inversion-symmetry	informational	Total energy is unchanged and forces change sign when inverting a configuration through the origin; see full description.	Results	Files
P No memory leak detected.	vc-memory-leak	informational	The model code does not have memory leaks (i.e. it releases all allocated memory at the end); see full description.	Results	Files
P All threads give identical results for tested case. Model appears to be thread-safe.	vc-thread-safe	mandatory	The model returns the same energy and forces when computed in serial and when using parallel threads for a set of configurations. Note that this is not a guarantee of thread safety; see full description.	Results	Files
P Unit conversion successful	vc-unit-conversion	mandatory	The model is able to correctly convert its energy and/or forces to different unit sets; see full description.	Results	Files

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

Species: Mn

Species: Cr

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: Mn

Species: Cr

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: Cr

Species: Mn

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: Cr

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: Cr

Species: Mn

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.

(No matching species)

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.

(No matching species)

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: Mn

Species: Cr

Cubic Crystal Basic Properties Table

Species: Cr

Species: Mn

Tests

CohesiveEnergyVsLatticeConstant__TD_554653289799_003

Cohesive energy versus lattice constant curve for monoatomic cubic lattices v003

Creators:
Contributor: karls
Publication Year: 2019
DOI: https://doi.org/10.25950/64cb38c5

This Test Driver uses LAMMPS to compute the cohesive energy of a given monoatomic cubic lattice (fcc, bcc, sc, or diamond) at a variety of lattice spacings. The lattice spacings range from a_min (=a_min_frac*a_0) to a_max (=a_max_frac*a_0) where a_0, a_min_frac, and a_max_frac are read from stdin (a_0 is typically approximately equal to the equilibrium lattice constant). The precise scaling and number of lattice spacings sampled between a_min and a_0 (a_0 and a_max) is specified by two additional parameters passed from stdin: N_lower and samplespacing_lower (N_upper and samplespacing_upper). Please see README.txt for further details.

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Cohesive energy versus lattice constant curve for bcc Cr v004	view	10380
Cohesive energy versus lattice constant curve for bcc Mn v004	view	10749
Cohesive energy versus lattice constant curve for diamond Cr v004	view	9488
Cohesive energy versus lattice constant curve for diamond Mn v004	view	10822
Cohesive energy versus lattice constant curve for fcc Cr v004	view	12741
Cohesive energy versus lattice constant curve for fcc Mn v004	view	9439
Cohesive energy versus lattice constant curve for sc Cr v004	view	10380
Cohesive energy versus lattice constant curve for sc Mn v004	view	10528

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 Cr at zero temperature v006	view	39976
Elastic constants for diamond Cr at zero temperature v001	view	75093
Elastic constants for fcc Cr at zero temperature v006	view	32931
Elastic constants for sc Cr at zero temperature v006	view	34013

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 Cr in AFLOW crystal prototype A_cF4_225_a v002	view	95559
Equilibrium crystal structure and energy for Mn in AFLOW crystal prototype A_cF4_225_a v002	view	88786
Equilibrium crystal structure and energy for Cr in AFLOW crystal prototype A_cI2_229_a v002	view	69570
Equilibrium crystal structure and energy for Mn in AFLOW crystal prototype A_cI58_217_ac2g v002	view	260964
Equilibrium crystal structure and energy for Mn in AFLOW crystal prototype A_cP20_213_cd v002	view	145253
Equilibrium crystal structure and energy for Cr in AFLOW crystal prototype A_cP8_223_ac v002	view	91444
Equilibrium crystal structure and energy for Cr in AFLOW crystal prototype A_hP2_194_c v002	view	43626
Equilibrium crystal structure and energy for Cr in AFLOW crystal prototype A_tP28_136_f2ij v002	view	96669

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 Cr v007	view	29006
Equilibrium zero-temperature lattice constant for bcc Mn v007	view	31362
Equilibrium zero-temperature lattice constant for diamond Cr v007	view	33350
Equilibrium zero-temperature lattice constant for diamond Mn v007	view	30332
Equilibrium zero-temperature lattice constant for fcc Cr v007	view	30111
Equilibrium zero-temperature lattice constant for fcc Mn v007	view	25031
Equilibrium zero-temperature lattice constant for sc Cr v007	view	23338
Equilibrium zero-temperature lattice constant for sc Mn v007	view	22985

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 Cr v005		view	248027
Equilibrium lattice constants for hcp Mn v005		view	273058

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 Cr at 293.15 K under a pressure of 0 MPa v002		view	2711369

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 Cr v004		view	67792

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 Cr		view	415440

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 Cr		view	791936

Errors

ElasticConstantsCubic__TD_011862047401_006

Test	Error Categories	Link to Error page
Elastic constants for bcc Mn at zero temperature v006	other	view
Elastic constants for diamond Mn at zero temperature v001	other	view
Elastic constants for fcc Mn at zero temperature v006	other	view
Elastic constants for sc Mn at zero temperature v006	other	view

ElasticConstantsHexagonal__TD_612503193866_004

Test	Error Categories	Link to Error page
Elastic constants for hcp Cr at zero temperature v004	other	view
Elastic constants for hcp Mn at zero temperature v004	other	view

SurfaceEnergyCubicCrystalBrokenBondFit__TD_955413365818_004

Test	Error Categories	Link to Error page
Broken-bond fit of high-symmetry surface energies in bcc Cr v004	other	view

VacancyFormationEnergyRelaxationVolume__TD_647413317626_001

Test	Error Categories	Link to Error page
Monovacancy formation energy and relaxation volume for bcc Mn	other	view

VacancyFormationMigration__TD_554849987965_001

Test	Error Categories	Link to Error page
Vacancy formation and migration energy for bcc Mn	other	view

Files

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

Download

MEAM_LAMMPS_ChoiKimSeol_2017_CrMn__MO_671124822359_002.txz	Tar+XZ	Linux and OS X archive
MEAM_LAMMPS_ChoiKimSeol_2017_CrMn__MO_671124822359_002.zip	Zip	Windows archive

Download Dependency

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

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

Wiki

Wiki is ready to accept new content.

MEAM_LAMMPS_ChoiKimSeol_2017_CrMn__MO_671124822359_002

Verification Check Dashboard

Visualizers (in-page)

BCC Lattice Constant

Cohesive Energy Graph

Diamond Lattice Constant

Dislocation Core Energies

FCC Elastic Constants

FCC Lattice Constant

FCC Stacking Fault Energies

FCC Surface Energies

SC Lattice Constant

Cubic Crystal Basic Properties Table

Tests

Errors

Files

Download

Download Dependency

Wiki