MEAM Potential for the Ni-Al-Co system developed by Kim, Jung, and Lee, (2015) v002

Young-Kwang Kim; Woo-Sang Jung; Byeong-Joo Lee

doi:10.25950/bf52f2c4

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MEAM_LAMMPS_KimJungLee_2015_NiAlCo__MO_876687166519_002

Interatomic potential for Aluminum (Al), Cobalt (Co), Nickel (Ni).
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Title A single sentence description.	MEAM Potential for the Ni-Al-Co system developed by Kim, Jung, and Lee, (2015) 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 Ni–Co binary and Ni–Al–Co ternary systems have been developed on the basis of the second nearest-neighbor modified embedded-atom method (2NN MEAM) formalism. The potentials describe structural, thermodynamic, deformation and defect properties of solid solution phases or compound phases in reasonable agreements with experiments or first-principles calculations. In the original paper (Kim et al Modelling and Simulation in Materials Science and Engineering, 23(5), 2015), the results demonstrate the transferability of the potentials and their applicability to large-scale atomistic simulations to investigate the effect of an alloying element, cobalt, on various microstructural factors related to mechanical properties of Ni-based superalloys on an atomic scale.
Species The supported atomic species.	Al, Co, Ni
Disclaimer A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.	None
Content Origin	http://cmse.postech.ac.kr/home_2nnmeam

Contributor	Hyeon-Seok Do
Maintainer	Hyeon-Seok Do
Developer	Young-Kwang Kim Woo-Sang Jung Byeong-Joo Lee
Published on KIM	2023
How to Cite	This Model originally published in [1] is archived in OpenKIM [2-5]. [1] Kim Y-K, Jung W-S, Lee B-J. Modified embedded-atom method interatomic potentials for the Ni–Co binary and the Ni–Al–Co ternary systems. Modelling and Simulation in Materials Science and Engineering. 2015;23(5):055004. doi:10.1088/0965-0393/23/5/055004 — (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] Kim Y-K, Jung W-S, Lee B-J. MEAM Potential for the Ni-Al-Co system developed by Kim, Jung, and Lee, (2015) v002. OpenKIM; 2023. doi:10.25950/bf52f2c4 [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. 31 Citations (24 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 . M. Shih, J. Miao, M. Mills, and M. Ghazisaeidi, “Stacking fault energy in concentrated alloys,” Nature Communications. 2021. link Times cited: 98 G. Li, T. Yu, P. Wu, and M. Chen, “Molecular dynamics simulation of phase transformation and wear behavior of Ni35Al30Co35 high temperature shape memory alloy,” Wear. 2023. link Times cited: 0 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 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 H. Li et al., “Uniting tensile ductility with ultrahigh strength via composition undulation,” Nature. 2022. link Times cited: 60 H. Xiang and W. Guo, “A newly developed interatomic potential of Nb−Al−Ti ternary systems for high-temperature applications,” Acta Mechanica Sinica. 2022. link Times cited: 5 H. Xiang and W. Guo, “A newly developed interatomic potential of Nb−Al−Ti ternary systems for high-temperature applications,” Acta Mechanica Sinica. 2022. link Times cited: 0 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 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 Q. Gao et al., “Shear deformation mechanical performance of Ni–Co alloy nanoplate by molecular dynamics simulation,” Modern Physics Letters B. 2021. link Times cited: 3 Abstract: Ni–Co alloy has great advantages in the fields of micro-elec… read more Abstract: Ni–Co alloy has great advantages in the fields of micro-electromechanical systems and aerospace, however, the lack of micro-deformation mechanism restricts its industrial application. Herein, the deformation mechanism and microstructure evolution of Ni–Co alloy nanoplate under shear loading are investigated by MD. The yield strength increases gradually with the increase of the velocity, and the highest shear modulus is 111.43 GPa. The stress concentration leads to the nucleation and expansion of the dislocation, and the stacking fault expands with the dislocation motion, swallowing most of the disordered atoms. By Dislocation Extraction Algorithm (DXA), it is found that Shockley and Perfect dislocations make a major role, and the interactions between dislocations are responsible for the high mechanical properties. As the temperature increases, the yield strength decreases significantly, the stress fluctuations in the plastic phase at 100 K and 200 K are greater compared to other temperatures. Meanwhile, the coherence of the dislocations motion decreases, and the atoms in the stacking faults are scattered, leading to the decreasing of area. The above results are helpful for the design and control of nanoelectronic facilities and provide a significant guide for the industrial applications of Ni–Co alloy nanoplate. read less 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 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 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 D. Naujoks et al., “Experimental and theoretical investigation on phase formation and mechanical properties in Cr-Co-Ni alloys processed using a novel thin-film quenching technique.,” ACS combinatorial science. 2020. link Times cited: 1 Abstract: The Cr-Co-Ni system was studied by combining experimental an… read more Abstract: The Cr-Co-Ni system was studied by combining experimental and computational methods to investigate phase stability and mechanical properties. Thin-film materials libraries were prepared and quenched from high temperatures up to 700°C using a novel quenching technique. It could be shown that a wide A1 solid solution region exists in the Cr-Co-Ni system. To validate the results obtained using thin-film materials libraries, bulk samples of selected compositions were prepared by arc melting and the experimental data were additionally compared to results from DFT calculations. The computational results are in good agreement with the measured lattice parameters and elastic moduli. The lattice parameters increase with the addition of Co and Cr, with a more pronounced effect for the latter. The addition of ~20 at. % Cr results in a similar hardening effect as the addition of ~40 at. % Co. read less S. Ding and X.-qiang Wang, “Strain rate and temperature effects on the mechanical properties of TiN/VN composite: Molecular dynamics study,” Journal of Alloys and Compounds. 2020. link Times cited: 7 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 O. Løvvik, D. Zhao, Y. Li, R. Bredesen, and T. Peters, “Grain Boundary Segregation in Pd-Cu-Ag Alloys for High Permeability Hydrogen Separation Membranes,” Membranes. 2018. link Times cited: 7 Abstract: Dense metal membranes that are based on palladium (Pd) are p… read more Abstract: Dense metal membranes that are based on palladium (Pd) are promising for hydrogen separation and production due to their high selectivity and permeability. Optimization of alloy composition has normally focused on bulk properties, but there is growing evidence that grain boundaries (GBs) play a crucial role in the overall performance of membranes. The present study provides parameters and analyses of GBs in the ternary Pd-Ag-Cu system, based on first-principles electronic structure calculations. The segregation tendency of Cu, Ag, and vacancies towards 12 different coherent ∑ GBs in Pd was quantified using three different procedures for relaxation of supercell lattice constants, representing the outer bounds of infinitely elastic and stiff lattice around the GBs. This demonstrated a clear linear correlation between the excess volume and the GB energy when volume relaxation was allowed for. The point defects were attracted by most of the GBs that were investigated. Realistic atomic-scale models of binary Pd-Cu and ternary Pd-Cu-Ag alloys were created for the ∑5(210) boundary, in which the strong GB segregation tendency was affirmed. This is a starting point for more targeted engineering of alloys and grain structure in dense metal membranes and related systems. read less Y.-K. Kim, H. Kim, W. Jung, and B.-J. Lee, “Development and application of Ni-Ti and Ni-Al-Ti 2NN-MEAM interatomic potentials for Ni-base superalloys,” Computational Materials Science. 2017. link Times cited: 24 C.-jun Wu, B.-J. Lee, and X. Su, “Modified embedded-atom interatomic potential for Fe-Ni, Cr-Ni and Fe-Cr-Ni systems,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2017. link Times cited: 60 W. Choi, Y. Kim, D. Seol, and B.-J. Lee, “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. link Times cited: 62 C. Lu et al., “Enhancing radiation tolerance by controlling defect mobility and migration pathways in multicomponent single-phase alloys,” Nature Communications. 2016. link Times cited: 494 Y.-K. Kim, H. Kim, W. Jung, and B.-J. Lee, “Atomistic modeling of the Ti–Al binary system,” Computational Materials Science. 2016. link Times cited: 45 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 S. Ding, Y. Li, Y. Luo, Z. Wu, and X. Wang, “Modified Embedded-Atom Interatomic Potential Parameters of the Ti–Cr Binary and Ti–Cr–N Ternary Systems,” Frontiers in Chemistry. 2021. link Times cited: 1 Abstract: The second nearest-neighbor modified embedded-atom method (2… read more Abstract: The second nearest-neighbor modified embedded-atom method (2NN MEAM) potential parameters of the Ti–Cr binary and Ti–Cr–N ternary systems are optimized in accordance with the 2NN MEAM method. The novel constructed potential parameters can well reproduce the multiple fundamental physical characteristics of binary and ternary systems and reasonably agree with the first-principles calculation or experimental data. Thus, the newly constructed 2NN MEAM potential parameters can be used for atomic simulations to determine the underlying principle of the hardness enhancement of TiN/CrN multilayered coatings. read less C. He, G. Pan, L. Xie, and Q. Peng, “Enhancement of Diffusion Assisted Bonding of the Bimetal Composite of Austenitic/Ferric Steels via Intrinsic Interlayers,” Materials. 2021. link Times cited: 1 Abstract: We investigate the effect of the intrinsic interlayers on th… read more Abstract: We investigate the effect of the intrinsic interlayers on the diffusion assisted bonding properties of the austenitic steel (stainless steel 316L) and ferric steels (Low-carbon steel Q345R) in a hot rolling process by molecular dynamics simulations and experiment. The introduction of an intrinsic interlayer (Cr or Ni) widens the diffusion region, leading to enhancement of bonding. The thickness of the diffusion region enlarges with an increase of temperature, with an enhancement factor of 195% and 108%, for Cr and Ni interlayer, respectively, at the temperature of 1800 K. Further diffusion analysis reveals the unsymmetrical diffusion near the interface. Our experimental investigation evidenced our computation discovery. 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 L. Selis and J. Seminario, “Dendrite formation in silicon anodes of lithium-ion batteries,” RSC Advances. 2018. link Times cited: 42 Abstract: Rechargeable lithium-ion batteries require a vigorous improv… read more Abstract: Rechargeable lithium-ion batteries require a vigorous improvement if we want to use them massively for high energy applications. Silicon and metal lithium anodes are excellent alternatives because of their large theoretical capacity when compared to graphite used in practically all rechargeable Li-ion batteries. However, several problems need to be addressed satisfactorily before a major fabrication effort can be launched; for instance, the growth of lithium dendrites is one of the most important to take care due to safety issues. In this work we attempt to predict the mechanism of dendrite growth by simulating possible behaviors of charge distributions in the anode of an already cracked solid electrolyte interphase of a nanobattery, which is under the application of an external field representing the charging of the battery; thus, elucidating the conditions for dendrite growth. The extremely slow drift velocity of the Li-ions of ∼1 mm per hour in a typical commercial Li-ion battery, makes the growth of a dendrite take a few hours; however, once a Li-ion arrives at an active site of the anode, it takes an extremely short time of ∼1 ps to react. This large difference in time-scales allows us to perform the molecular dynamics simulation of the ions at much larger drift velocities, so we can have valuable results in reasonable computational times. The conditions before the growth are assumed and conditions that do not lead to the growth are ignored. We performed molecular dynamics simulations of a pre-lithiated silicon anode with a Li : Si ratio of 21 : 5, corresponding to a fully charged battery. We simulate the dendrite growth by testing a few charge distributions in a nanosized square representing a crack of the solid electrolyte interphase, which is where the electrolyte solution comes into direct contact with the LiSi alloy anode. Depending on the selected charge distributions for such an anode surface, the dendrites grow during the simulation when an external field is applied. We found that dendrites grow when strong deviations of charge distributions take place on the surface of the crack. Results from this work are important in finding ways to constrain lithium dendrite growth using tailored coatings or pre-coatings covering the LiSi alloy anode. 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 D. E. Galvez-Aranda, V. Ponce, and J. Seminario, “Molecular dynamics simulations of the first charge of a Li-ion—Si-anode nanobattery,” Journal of Molecular Modeling. 2017. link Times cited: 25
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_876687166519_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_KimJungLee_2015_NiAlCo__MO_876687166519_002
DOI	10.25950/bf52f2c4 https://doi.org/10.25950/bf52f2c4 https://commons.datacite.org/doi.org/10.25950/bf52f2c4
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

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Grade	Name	Category	Brief Description	Full Results	Aux File(s)
P All elements claimed by model are supported in at least one of the tested configurations.	vc-species-supported-as-stated	mandatory	The model supports all species it claims to support; see full description.	Results	Files
P Periodic boundary conditions were correctly supported for all configurations that the model was able to compute.	vc-periodicity-support	mandatory	Periodic boundary conditions are handled correctly; see full description.	Results	Files
P Model energy has permutation symmetry for all configurations the model was able to compute.	vc-permutation-symmetry	mandatory	Total energy and forces are unchanged when swapping atoms of the same species; see full description.	Results	Files
B The letter grade B was assigned because the normalized error in the computation was 5.10130e-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 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: Al

Species: Co

Cohesive Energy Graph

This graph shows the cohesive energy versus volume-per-atom for the current mode for four mono-atomic cubic phases (body-centered cubic (bcc), face-centered cubic (fcc), simple cubic (sc), and diamond). The curve with the lowest minimum is the ground state of the crystal if stable. (The crystal structure is enforced in these calculations, so the phase may not be stable.) Graphs are generated for each species supported by the model.

Species: Ni

Species: Co

Species: Al

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: Al

Species: Ni

Species: Co

Dislocation Core Energies

This graph shows the dislocation core energy of a cubic crystal at zero temperature and pressure for a specific set of dislocation core cutoff radii. After obtaining the total energy of the system from conjugate gradient minimizations, non-singular, isotropic and anisotropic elasticity are applied to obtain the dislocation core energy for each of these supercells with different dipole distances. Graphs are generated for each species supported by the model.

(No matching species)

FCC Elastic Constants

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

Species: Ni

Species: Al

Species: Co

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: Co

Species: Al

Species: Ni

FCC Stacking Fault Energies

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

Species: Ni

Species: Al

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

Species: Al

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: Co

Species: Ni

Species: Al

Cubic Crystal Basic Properties Table

Species: Al

Species: Co

Species: Ni

Tests

CohesiveEnergyVsLatticeConstant__TD_554653289799_003

Cohesive energy versus lattice constant curve for monoatomic cubic lattices v003

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

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

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Cohesive energy versus lattice constant curve for bcc Al v004	view	14724
Cohesive energy versus lattice constant curve for bcc Co v004	view	14503
Cohesive energy versus lattice constant curve for bcc Ni v004	view	15019
Cohesive energy versus lattice constant curve for diamond Al v004	view	11905
Cohesive energy versus lattice constant curve for diamond Co v004	view	15166
Cohesive energy versus lattice constant curve for diamond Ni v004	view	12850
Cohesive energy versus lattice constant curve for fcc Al v004	view	16918
Cohesive energy versus lattice constant curve for fcc Co v004	view	12403
Cohesive energy versus lattice constant curve for fcc Ni v004	view	15019
Cohesive energy versus lattice constant curve for sc Al v004	view	12621
Cohesive energy versus lattice constant curve for sc Co v004	view	13258
Cohesive energy versus lattice constant curve for sc Ni v004	view	13397

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 AlCo in AFLOW crystal prototype A13B4_oP102_31_17a11b_8a2b at zero temperature and pressure v000		view	36923184
Elastic constants for AlNi in AFLOW crystal prototype A3B2_hP5_164_ad_d at zero temperature and pressure v000		view	521199

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 Al at zero temperature v006	view	32334
Elastic constants for bcc Co at zero temperature v006	view	46602
Elastic constants for bcc Ni at zero temperature v006	view	46307
Elastic constants for diamond Al at zero temperature v001	view	82087
Elastic constants for diamond Co at zero temperature v001	view	61556
Elastic constants for diamond Ni at zero temperature v001	view	86504
Elastic constants for fcc Al at zero temperature v006	view	70013
Elastic constants for fcc Co at zero temperature v006	view	55731
Elastic constants for fcc Ni at zero temperature v006	view	43215
Elastic constants for sc Al at zero temperature v006	view	44982
Elastic constants for sc Co at zero temperature v006	view	31429
Elastic constants for sc Ni at zero temperature v006	view	31897

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 CoNi in AFLOW crystal prototype A3B_cP4_221_c_a v002	view	82391
Equilibrium crystal structure and energy for AlNi in AFLOW crystal prototype A3B_oP16_62_cd_c v002	view	81479
Equilibrium crystal structure and energy for AlNi in AFLOW crystal prototype A4B3_cI112_230_af_g v002	view	1552288
Equilibrium crystal structure and energy for AlCo in AFLOW crystal prototype A5B2_hP28_194_ahk_ch v002	view	117351
Equilibrium crystal structure and energy for AlCo in AFLOW crystal prototype A9B2_mP22_14_a4e_e v002	view	163732
Equilibrium crystal structure and energy for AlCo in AFLOW crystal prototype AB3_cP4_221_a_c v002	view	93277
Equilibrium crystal structure and energy for AlCo in AFLOW crystal prototype AB3_hP8_194_c_h v002	view	82823
Equilibrium crystal structure and energy for AlCo in AFLOW crystal prototype AB_cP2_221_a_b v002	view	96426
Equilibrium crystal structure and energy for AlNi in AFLOW crystal prototype AB_cP2_221_a_b v002	view	74735
Equilibrium crystal structure and energy for CoNi in AFLOW crystal prototype AB_cP2_221_a_b v002	view	91437

EquilibriumCrystalStructure__TD_457028483760_003

Equilibrium structure and energy for a crystal structure at zero temperature and pressure v003

Creators:
Contributor: ilia
Publication Year: 2025
DOI: https://doi.org/10.25950/866c7cfa

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 AlCo in AFLOW crystal prototype A13B4_oP102_31_17a11b_8a2b v003	view	1657800
Equilibrium crystal structure and energy for AlNi in AFLOW crystal prototype A3B2_hP5_164_ad_d v003	view	332451
Equilibrium crystal structure and energy for AlNi in AFLOW crystal prototype A3B5_oC16_65_ah_bej v003	view	252944
Equilibrium crystal structure and energy for Al in AFLOW crystal prototype A_cF4_225_a v003	view	146432
Equilibrium crystal structure and energy for Co in AFLOW crystal prototype A_cF4_225_a v003	view	182560
Equilibrium crystal structure and energy for Ni in AFLOW crystal prototype A_cF4_225_a v003	view	159860
Equilibrium crystal structure and energy for Al in AFLOW crystal prototype A_cI2_229_a v003	view	152022
Equilibrium crystal structure and energy for Ni in AFLOW crystal prototype A_cI2_229_a v003	view	139080
Equilibrium crystal structure and energy for Co in AFLOW crystal prototype A_hP2_194_c v003	view	154270
Equilibrium crystal structure and energy for Ni in AFLOW crystal prototype A_hP2_194_c v003	view	151353
Equilibrium crystal structure and energy for Co in AFLOW crystal prototype A_tP28_136_f2ij v003	view	550963
Equilibrium crystal structure and energy for AlNi in AFLOW crystal prototype AB3_cF16_225_a_bc v003	view	174685
Equilibrium crystal structure and energy for AlNi in AFLOW crystal prototype AB3_cP4_221_a_c v003	view	152629

GrainBoundaryCubicCrystalSymmetricTiltRelaxedEnergyVsAngle__TD_410381120771_003

Relaxed energy as a function of tilt angle for a symmetric tilt grain boundary within a cubic crystal v003

Creators:
Contributor: brunnels
Publication Year: 2022
DOI: https://doi.org/10.25950/2c59c9d6

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

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Relaxed energy as a function of tilt angle for a 100 symmetric tilt grain boundary in fcc Al v003	view	21732279
Relaxed energy as a function of tilt angle for a 100 symmetric tilt grain boundary in fcc Ni v001	view	32366880
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Al v001	view	67568579
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Al v001	view	34001764
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Ni v001	view	57435226

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 Al v007	view	33276
Equilibrium zero-temperature lattice constant for bcc Co v007	view	35191
Equilibrium zero-temperature lattice constant for bcc Ni v007	view	34334
Equilibrium zero-temperature lattice constant for diamond Al v007	view	32762
Equilibrium zero-temperature lattice constant for diamond Co v007	view	35298
Equilibrium zero-temperature lattice constant for diamond Ni v007	view	35925
Equilibrium zero-temperature lattice constant for fcc Al v007	view	32046
Equilibrium zero-temperature lattice constant for fcc Co v007	view	43733
Equilibrium zero-temperature lattice constant for fcc Ni v007	view	34234
Equilibrium zero-temperature lattice constant for sc Al v007	view	33190
Equilibrium zero-temperature lattice constant for sc Co v007	view	33718
Equilibrium zero-temperature lattice constant for sc Ni v007	view	32982

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	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 Al v005	view	328337
Equilibrium lattice constants for hcp Co v005	view	350437
Equilibrium lattice constants for hcp Ni v005	view	389968

LinearThermalExpansionCoeffCubic__TD_522633393614_002

Linear thermal expansion coefficient of cubic crystal structures v002

Creators:
Contributor: mjwen
Publication Year: 2024
DOI: https://doi.org/10.25950/9d9822ec

This Test Driver uses LAMMPS to compute the linear thermal expansion coefficient at a finite temperature under a given pressure for a cubic lattice (fcc, bcc, sc, diamond) of a single given species.

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Linear thermal expansion coefficient of fcc Al at 293.15 K under a pressure of 0 MPa v002		view	5326296
Linear thermal expansion coefficient of fcc Ni at 293.15 K under a pressure of 0 MPa v002		view	4923140

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	86279

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 Al v002		view	37280592
Stacking and twinning fault energies for fcc Ni v002		view	47049135

SurfaceEnergyCubicCrystalBrokenBondFit__TD_955413365818_004

High-symmetry surface energies in cubic lattices and broken bond model v004

Creators: Matt Bierbaum
Contributor: mattbierbaum
Publication Year: 2019
DOI: https://doi.org/10.25950/6c43a4e6

Calculates the surface energy of several high symmetry surfaces and produces a broken-bond model fit. In latex form, the fit equations are given by:

E_{FCC} (\vec{n}) = p_1 (4 \left( |x+y| + |x-y| + |x+z| + |x-z| + |z+y| +|z-y|\right)) + p_2 (8 \left( |x| + |y| + |z|\right)) + p_3 (2 ( |x+ 2y + z| + |x+2y-z| + |x-2y + z| + |x-2y-z| + |2x+y+z| + |2x+y-z| +|2x-y+z| +|2x-y-z| +|x+y+2z| +|x+y-2z| +|x-y+2z| +|x-y-2z| ) + c

E_{BCC} (\vec{n}) = p_1 (6 \left( | x+y+z| + |x+y-z| + |-x+y-z| + |x-y+z| \right)) + p_2 (8 \left( |x| + |y| + |z|\right)) + p_3 (4 \left( |x+y| + |x-y| + |x+z| + |x-z| + |z+y| +|z-y|\right)) +c.

In Python, these two fits take the following form:

def BrokenBondFCC(params, index):

import numpy
x, y, z = index
x = x / numpy.sqrt(x**2.+y**2.+z**2.)
y = y / numpy.sqrt(x**2.+y**2.+z**2.)
z = z / numpy.sqrt(x**2.+y**2.+z**2.)

return params[0]*4* (abs(x+y) + abs(x-y) + abs(x+z) + abs(x-z) + abs(z+y) + abs(z-y)) + params[1]*8*(abs(x) + abs(y) + abs(z)) + params[2]*(abs(x+2*y+z) + abs(x+2*y-z) +abs(x-2*y+z) +abs(x-2*y-z) + abs(2*x+y+z) +abs(2*x+y-z) +abs(2*x-y+z) +abs(2*x-y-z) + abs(x+y+2*z) +abs(x+y-2*z) +abs(x-y+2*z) +abs(x-y-2*z))+params[3]

def BrokenBondBCC(params, x, y, z):

import numpy
x, y, z = index
x = x / numpy.sqrt(x**2.+y**2.+z**2.)
y = y / numpy.sqrt(x**2.+y**2.+z**2.)
z = z / numpy.sqrt(x**2.+y**2.+z**2.)

return params[0]*6*(abs(x+y+z) + abs(x-y-z) + abs(x-y+z) + abs(x+y-z)) + params[1]*8*(abs(x) + abs(y) + abs(z)) + params[2]*4* (abs(x+y) + abs(x-y) + abs(x+z) + abs(x-z) + abs(z+y) + abs(z-y)) + params[3]

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Broken-bond fit of high-symmetry surface energies in fcc Al v004		view	113713
Broken-bond fit of high-symmetry surface energies in fcc Ni v004		view	137235

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	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Monovacancy formation energy and relaxation volume for fcc Al	view	506362
Monovacancy formation energy and relaxation volume for fcc Ni	view	747690
Monovacancy formation energy and relaxation volume for hcp Co	view	728401

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	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Vacancy formation and migration energy for fcc Al	view	2325303
Vacancy formation and migration energy for fcc Ni	view	1321341
Vacancy formation and migration energy for hcp Co	view	5143055

Errors

ElasticConstantsCrystal__TD_034002468289_000

Test	Error Categories	Link to Error page
Elastic constants for AlCo in AFLOW crystal prototype A13B4_oP102_31_17a11b_8a2b at zero temperature and pressure v000	other	view

ElasticConstantsHexagonal__TD_612503193866_004

Test	Error Categories	Link to Error page
Elastic constants for hcp Al at zero temperature v004	other	view
Elastic constants for hcp Co at zero temperature v004	other	view
Elastic constants for hcp Ni at zero temperature v004	other	view

EquilibriumCrystalStructure__TD_457028483760_000

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for AlCo in AFLOW crystal prototype A13B4_oP102_31_17a11b_8a2b v000	other	view
Equilibrium crystal structure and energy for AlCo in AFLOW crystal prototype A9B2_mP22_14_a4e_e v000	other	view
Equilibrium crystal structure and energy for Ni in AFLOW crystal prototype A_cF4_225_a v000	other	view
Equilibrium crystal structure and energy for Ni in AFLOW crystal prototype A_hP2_194_c v000	other	view

EquilibriumCrystalStructure__TD_457028483760_002

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for AlNi in AFLOW crystal prototype AB3_tP4_123_a_ce v002	other	view

EquilibriumCrystalStructure__TD_457028483760_003

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for AlNi in AFLOW crystal prototype A3B2_hP5_164_ad_d v003	other	view
Equilibrium crystal structure and energy for Co in AFLOW crystal prototype A_oC4_63_c v003	other	view
Equilibrium crystal structure and energy for Co in AFLOW crystal prototype A_tI2_139_a v003	other	view

GrainBoundaryCubicCrystalSymmetricTiltRelaxedEnergyVsAngle__TD_410381120771_003

Test	Error Categories	Link to Error page
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Ni v001	other	view
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Al v001	other	view
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Ni v001	other	view

PhononDispersionCurve__TD_530195868545_004

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

SurfaceEnergyCubicCrystalBrokenBondFit__TD_955413365818_004

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

No Driver

Verification Check	Error Categories	Link to Error page
MemoryLeak__VC_561022993723_004	other	view

Files

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

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MEAM_LAMMPS_KimJungLee_2015_NiAlCo__MO_876687166519_002.zip	Zip	Windows archive

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

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

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MEAM_LAMMPS_KimJungLee_2015_NiAlCo__MO_876687166519_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

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