MEAM potential for HfNbTaTiZr alloy developed by Huang et al. (2021) v002

Xiusong Huang; Lehua Liu; Xianbao Duan; Wei-Bing Liao; Jianjun Huang; Huibin Sun; Chunyan Yu

doi:10.25950/6f4deef5

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MEAM_LAMMPS_HuangLiuDuan_2021_HfNbTaTiZr__MO_893505888031_002

Interatomic potential for Hafnium (Hf), Niobium (Nb), Tantalum (Ta), Titanium (Ti), Zirconium (Zr).
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Title A single sentence description.	MEAM potential for HfNbTaTiZr alloy developed by Huang et al. (2021) v002
Description A short description of the Model describing its key features including for example: type of model (pair potential, 3-body potential, EAM, etc.), modeled species (Ac, Ag, ..., Zr), intended purpose, origin, and so on.	A modified embedded-atom method (MEAM) interatomic potential with good accuracy for studying chemical short-range order (CSRO) in the HfNbTaTiZr alloy system was developed. The potential accuracy was further validated on the formation enthalpies, lattice constants, and melting points for the solid solutions.
Species The supported atomic species.	Hf, Nb, Ta, Ti, Zr
Disclaimer A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.	None
Content Origin	Files are provided by Xiusong Huang (Tsinghua University) on Feb 12, 2021, and posted with his permission.

Contributor	Yaser Afshar
Maintainer	Yaser Afshar
Developer	Xiusong Huang Lehua Liu Xianbao Duan Wei-Bing Liao Jianjun Huang Huibin Sun Chunyan Yu
Published on KIM	2023
How to Cite	This Model originally published in [1] is archived in OpenKIM [2-5]. [1] Huang X, Liu L, Duan X, Liao W, Huang J, Sun H, et al. Atomistic simulation of chemical short-range order in HfNbTaZr high entropy alloy based on a newly-developed interatomic potential. Materials & Design. 2021;202:109560. doi:10.1016/j.matdes.2021.109560 — (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] Huang X, Liu L, Duan X, Liao W-B, Huang J, Sun H, et al. MEAM potential for HfNbTaTiZr alloy developed by Huang et al. (2021) v002. OpenKIM; 2023. doi:10.25950/6f4deef5 [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. 49 Citations (28 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 . X. Jin, S. Chen, C. Lemkan, and T. Li, “Role of local atomic short-range order distribution in alloys: Why it matters in Si-Ge-Sn alloys,” Physical Review Materials. 2023. link Times cited: 0 S.-P. Ju, C.-H. Yang, and H.-Y. Chen, “Unveiling Mechanisms of Self-Healing in CoCrFeMnNi/HfNbTaTiZr Dual-Phase High-Entropy Alloys: A Molecular Dynamics Simulation Study,” Materials Today Communications. 2023. link Times cited: 0 X. Duan et al., “Atomistic simulation of local chemical order in NbTiZrMoV high entropy alloy based on a newly-developed interatomic potential,” Computational Materials Science. 2023. link Times cited: 0 S. Ataollahi and M. Mahtabi, “An interatomic potential for ternary NiTiHf shape memory alloys based on modified embedded atom method,” Computational Materials Science. 2023. link Times cited: 2 Y.-C. Wu and J. Shao, “FCC-BCC Phase Transformation Induced Simultaneous Enhancement of Tensile Strength and Ductility at High Strain Rate in High-Entropy Alloy,” International Journal of Plasticity. 2023. link Times cited: 2 A. Chen, Y. Pan, J. Dai, W. Fu, and X. Song, “Theoretical study on the element distribution characteristics and the effects of oxygen in TiZrHfNb high entropy alloys,” Materials Today Communications. 2023. link Times cited: 1 M. Zhu, J. Wang, P. Jiang, F. Yuan, and X. Wu, “Formation of chemical short-range orders of two kinds and the co-existence with medium-range orders in an equiatomic VFeCoNi alloy,” Intermetallics. 2023. link Times cited: 1 D. Gu et al., “Designing (TiZrHf)100-xCux high entropy alloys with abnormal as-cast divorced eutectoid microstructure and balanced mechanical properties,” Materials Science and Engineering: A. 2023. link Times cited: 0 T. Li, H. Zong, F. Zhao, X. Ding, T. Lookman, and J. Sun, “Effects of atomic size mismatch on glass transition decoupling in high-entropy metallic glasses,” Acta Materialia. 2023. link Times cited: 0 C. Tsai, C.-H. Tung, C.-C. Chen, and S.-Y. Chang, “Chemical Complexity-Changed Deformation Behavior of NiTi-Based B2 Low- to High-Entropy Intermetallic Compounds: Atomistic Simulations,” Journal of Alloys and Compounds. 2023. link Times cited: 0 Z. Liang, Y. Wu, Y. Miao, W. Pan, and Y.-zhong Zhang, “Composition Design and Tensile Properties of Additive Manufactured Low Density Hf-Nb-Ta-Ti-Zr High Entropy Alloys Based on Atomic Simulations,” Materials. 2023. link Times cited: 1 Abstract: High-entropy alloy (HEA) is a new type of multi-principal al… read more Abstract: High-entropy alloy (HEA) is a new type of multi-principal alloy material and the Hf-Nb-Ta-Ti-Zr HEAs have attracted more and more attention from researchers due to their high melting point, special plasticity, and excellent corrosion resistance. In this paper, in order to reduce the density of the alloy and maintain the strength of the Hf-Nb-Ta-Ti-Zr HEAs, the effects of high-density elements Hf and Ta on the properties of HEAs were explored for the first time based on molecular dynamics simulations. A low-density and high-strength Hf0.25NbTa0.25TiZr HEA suitable for laser melting deposition was designed and formed. Studies have shown that the decrease in the proportion of Ta element reduces the strength of HEA, while the decrease in Hf element increases the strength of HEA. The simultaneous decrease in the ratio of Hf and Ta elements reduces the elastic modulus and strength of HEA and leads to the coarsening of the alloy microstructure. The application of laser melting deposition (LMD) technology refines the grains and effectively solves the coarsening problem. Compared with the as-cast state, the as-deposited Hf0.25NbTa0.25TiZr HEA obtained by LMD forming has obvious grain refinement (from 300 μm to 20–80 μm). At the same time, compared with the as-cast Hf0.25NbTa0.25TiZr HEA (σs = 730 ± 23 MPa), the as-deposited Hf0.25NbTa0.25TiZr HEA has higher strength (σs = 925 ± 9 MPa), which is similar to the as-cast equiatomic ratio HfNbTaTiZr HEA (σs = 970 ± 15 MPa). read less Z. Sun et al., “An experimental and computational design low-modulus (HfNbTa)1-xTix multiprinciple elemental alloys with super formability for biomedical applications,” Materials Science and Engineering: A. 2023. link Times cited: 1 C. Yang et al., “Low modulus Ti-rich biocompatible TiNbZrTaHf concentrated alloys with exceptional plasticity,” Materials Research Letters. 2023. link Times cited: 3 Abstract: This study investigates the evolutions of microstructure and… read more Abstract: This study investigates the evolutions of microstructure and performance of TiNbZrTaHf-based alloys from equiatomic high-entropy alloys to Ti-rich dilute alloys. A novel biocompatible alloy, Ti50Nb12.5Zr12.5Ta12.5Hf12.5, was developed with a high yield strength of 839 ± 12 MPa, low modulus of 61.5 GPa, low magnetic susceptibility of ∼1.99 × 10−6 cm3g−1, and unprecedented tensile plasticity of 28.7 ± 2.2%. The study discusses the underlying mechanisms responsible for these superior performances, attributing the exceptional plasticity to the activation of cross-slip dislocations, enhanced dynamic recovery and high resistance to crack propagation. The findings provide new insights into the development of biomedical titanium alloys. GRAPHICAL ABSTRACT IMPACT STATEMENT This study introduces a novel biocompatible concentrated alloy with high strength, low modulus and unprecedented ductility, providing new insights for developing high-performance biomedical titanium alloys. read less J. Li, Y.-F. Wu, Z. Bai, W. Yu, and S. Shen, “Nanostructure-property relation of Σ5 grain boundary in HfNbZrTi high-entropy alloy under shear,” Journal of Materials Science. 2023. link Times cited: 2 A. Nazarahari, A. Fromm, H. Ozdemir, C. Klose, H. Maier, and D. Canadinc, “Determination of thermal conductivity of eutectic Al–Cu compounds utilizing experiments, molecular dynamics simulations and machine learning,” Modelling and Simulation in Materials Science and Engineering. 2023. link Times cited: 0 Abstract: In this study, the thermal conductivity ( κ ) of Al–Cu eutec… read more Abstract: In this study, the thermal conductivity ( κ ) of Al–Cu eutectics were investigated by experimental and computational methods to shed light on the role of these compounds in thermal properties of Al–Cu connections in compound casting. Specifically, the nonequilibrium molecular dynamics (MD) method was utilized to simulate the lattice thermal conductivity ( κl ) of six compositions of Al–Cu with 5–30 at.% Cu. To extend the results of the MD simulations to bulk materials, instead of using conventional linear extrapolation methods, a machine learning approach was developed for the dataset acquired from the MD simulations. The bootstrapping approach was utilized to find the most suitable method among the support vector machine (SVM) with polynomial and radial basis function (RBF) kernels and the random forest method. The results showed that the SVM model with RBF kernel performed the best, and thus was used to predict the bulk κl . Subsequently, the chosen compositions were produced by induction casting and their electrical conductivities were measured via eddy current method for calculating the electronic contribution of κ using the Wiedemann–Franz law. Finally, the actual κ of the alloys were measured using the xenon flash method and the results were compared with the computational values. It was shown that the MD method is capable of successfully simulating the thermal conductivity of this system. In addition, the experimental results demonstrated that the κ of Al–Cu eutectics decreases almost linearly with formation of the Al2Cu phase due to increase in the Cu content. Overall, the current findings can be used to enhance the κ of cooling devices made via Al–Cu compound casting. read less 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 S. Xu, W. Jian, and I. Beyerlein, “Ideal simple shear strengths of two HfNbTaTi-based quinary refractory multi-principal element alloys,” APL Materials. 2022. link Times cited: 4 Abstract: Atomistic simulations are employed to investigate chemical s… read more Abstract: Atomistic simulations are employed to investigate chemical short-range ordering in two body-centered cubic refractory multi-principal element alloys, HfMoNbTaTi and HfNbTaTiZr, and its influence on their ideal simple shear strengths. Both the alias and affine shear strengths are analyzed on the {110} and {112} planes in the two opposing [Formula: see text] directions. In both quinary alloys, local ordering of NbNb, TaTa, HfNb, HfTa, and NbTa is preferred as the annealing temperature decreases from 900 to 300 K. The pair that achieves the highest degree of local ordering is TiTi in HfMoNbTaTi and HfTi in HfNbTaTiZr. Subject to the affine shear, these alloys yield by first phase transformation at the most likely pairs followed by deformation twinning at those sites. read less A. Huang, S. Fensin, and M. Meyers, “Strain-Rate Effects and Dynamic Behavior of High Entropy Alloys,” Journal of Materials Research and Technology. 2022. link Times cited: 10 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: 4 A. Manzoor and Y. Zhang, “Influence of Defect Thermodynamics on Self-Diffusion in Complex Concentrated Alloys with Chemical Ordering,” JOM. 2022. link Times cited: 2 R. Salloom, M. Baskes, and S. G. Srinivasan, “Atomic level simulations of the phase stability and stacking fault energy of FeCoCrMnSi high entropy alloy,” Modelling and Simulation in Materials Science and Engineering. 2022. link Times cited: 4 Abstract: High entropy alloys (HEAs) have many promising properties be… read more Abstract: High entropy alloys (HEAs) have many promising properties beneficial to advanced technologies. However, their underlying deformation mechanisms are largely unclear. So, as a first step, we have developed a modified embedded atom method potential for FeCoCrMnSi alloys to study such mechanisms. We predict the phase stability, chemical short-range ordering (CSRO), and stacking fault energy (SFE) of a specific alloy system using molecular dynamics (MD) and hybrid Monte-Carlo and molecular dynamics (MC/MD) simulation techniques. Room temperature MD simulations showed that both the potential energy and free energy of the single phase ε-hcp alloy is marginally more stable than the γ-fcc phase alloy, which resulted in a large, negative SFE. However, the room temperature MC/MD simulation showed an opposite trend where the γ-fcc phase was found to be more stable than the ε-hcp phase, and this resulted in a small, positive SFE. The prediction of the lower energy γ-fcc phase and resultant SFE agreed well with the experimentally reported SFE and phase stability for the Fe40Co20Cr15Mn20Si5 HEA, illustrating the importance of CSRO. Also, the calculated basal SFE of the hcp phase was close to that of the fcc phase. Therefore, the MC/MD implementation is crucial for the proper prediction of the phase stability and structural evolution in this HEA system. Many previous studies showed the ability of hybrid MC/MD technique to obtain consistent structural and configurational information of different alloy systems. The current work illustrates the potential of accelerating HEA materials development by utilizing computational methods based on the MC/MD technique which can reduce time and cost associated with experimental methods. read less N. Zhang, K. Gan, and Z. Li, “Atomistic insights on the deformation mechanisms of Cox(CrNi)100-x multicomponent alloys: The effect of Co content,” Computational Materials Science. 2022. link Times cited: 5 S. Guo et al., “Research on optimizing strength and ductility of HfNbTaZr dual-phase high-entropy alloy by tuning chemical short-range order,” International Journal of Refractory Metals and Hard Materials. 2022. link Times cited: 2 M. Charpagne, J. Stinville, F. Wang, N. Philips, and T. Pollock, “Orientation dependent plastic localization in the refractory high entropy alloy HfNbTaTiZr at room temperature,” Materials Science and Engineering: A. 2022. link Times cited: 3 J. Startt, A. Kustas, J. Pegues, P. Yang, and R. Dingreville, “Compositional effects on the mechanical and thermal properties of MoNbTaTi refractory complex concentrated alloys,” Materials & Design. 2022. link Times cited: 7 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. 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 U. S. Anamu et al., “Fundamental design strategies for advancing the development of high entropy alloys for thermo-mechanical application: A critical review,” Journal of Materials Research and Technology. 2023. link Times cited: 0 D. Jiang, L. Xie, and L. Wang, “Current Application Status of Multi-Scale Simulation and Machine Learning in Research on High-Entropy Alloys,” Journal of Materials Research and Technology. 2023. link Times cited: 1 Q. Guo et al., “Hardening-softening of Al0.3CoCrFeNi high-entropy alloy under nanoindentation,” Materials & Design. 2023. link Times cited: 19 Z. Li, D. Dong, and C. Dong, “Intuitive graphical presentation of cluster-plus-glue-atom model to obtain composition formulas of industrial alloys,” Materials Today Communications. 2023. link Times cited: 0 A. Ferrari, F. Körmann, M. Asta, and J. Neugebauer, “Simulating short-range order in compositionally complex materials,” Nature Computational Science. 2023. link Times cited: 4 Y.-hong Niu, D. Zhao, B. Zhu, S. Wang, Z. Wang, and H. Zhao, “Investigations on the role of chemical short-range order in the tensile deformation of FCC Co30Fe16.67Ni36.67Ti16.67 high-entropy alloys via Monte Carlo and molecular dynamics hybrid simulations,” Computational Materials Science. 2022. link Times cited: 4 X. Wu, “Chemical short-range orders in high-/medium-entropy alloys,” Journal of Materials Science & Technology. 2022. link Times cited: 4 Z. Zhang, L. Chen, J. Guo, X. Duan, B. Shan, and X. Duan, “Strategy to consider element distribution when constructing training datasets for developing machine learning potentials of alloys based on a Monte-Carlo-like method,” Physical Review B. 2022. link Times cited: 1 B. Yao, Z. R. Liu, and R. F. Zhang, “EAPOTc: An integrated empirical interatomic potential optimization platform for compound solids,” Computational Materials Science. 2022. link Times cited: 1 D.-Q. Doan, T. Fang, and T. Chen, “Structural transformation and strain localization at twin boundaries in Al0.4CoCrFeNi high-entropy alloy,” Applied Surface Science. 2022. link Times cited: 13 V. Soni, S. K. Sanyal, K. R. Rao, and S. K. Sinha, “A review on phase prediction in high entropy alloys,” Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. 2021. link Times cited: 7 Abstract: The formation of single phase solid solution in High Entropy… read more Abstract: The formation of single phase solid solution in High Entropy Alloys (HEAs) is essential for the properties of the alloys therefore, numerous approach were proposed by many researchers to predict the stability of single phase solid solution in High Entropy Alloy. The present review examines some of the recent developments while using computational intelligence techniques such as parametric approach, CALPHAD, Machine Learning etc. for prediction of various phase formation in multicomponent high entropy alloys. A detail study of this data-driven approaches pertaining to the understanding of structural and phase formation behaviour of a new class of compositionally complex alloys is done in the present investigation. The advantages and drawbacks of the various computational are also discussed. Finally, this review aims at understanding several computational modeling tools complying the thermodynamic criteria for phase formation of novel HEAs which could possibly deliver superior mechanical properties keeping an aim at advanced engineering applications. read less F. Wang et al., “Atomic-scale simulations in multi-component alloys and compounds: A review on advances in interatomic potential,” Journal of Materials Science & Technology. 2023. link Times cited: 5 X. Liu et al., “A statistics-based study and machine-learning of stacking fault energies in HEAs,” Journal of Alloys and Compounds. 2023. link Times cited: 0 G. Anand, S. Ghosh, and M. Eisenbach, “Order Parameter Engineering for Random Systems,” High Entropy Alloys & Materials. 2022. link Times cited: 1 M. Zamani, H. Mirzadeh, M. Malekan, S. Cao, and J. Yeh, “Grain Growth in High-Entropy Alloys (HEAs): A Review,” High Entropy Alloys & Materials. 2022. link Times cited: 10 L. T. W. Fey and I. Beyerlein, “Random Generation of Lattice Structures with Short-Range Order,” Integrating Materials and Manufacturing Innovation. 2022. link Times cited: 4 F. Aquistapace et al., “Atomistic Simulations of Ductile Failure in a b.c.c. High-Entropy Alloy,” High Entropy Alloys & Materials. 2022. link Times cited: 4 S. Ju, C.-C. Li, and H.-T. Shih, “How atoms of polycrystalline Nb20.6Mo21.7Ta15.6W21.1V21.0 refractory high-entropy alloys rearrange during the melting process,” Scientific Reports. 2022. link Times cited: 4 J. S. Andrade, I. N. Bastos, and L. C. R. Aliaga, “Determinação das características estruturais e mecânicas da liga de alta entropia Hf-Nb-Ta-Zr,” VETOR - Revista de Ciências Exatas e Engenharias. 2021. link Times cited: 0 Abstract: Neste artigo, os comportamentos estrutural e mecânico da lig… read more Abstract: Neste artigo, os comportamentos estrutural e mecânico da liga equiatômica de alta entropia Hf-Nb-Ta-Zr foram estudados mediante simulações computacionais de dinâmica molecular. As simulações foram realizadas no código livre LAMMPS, em um sistema composto de 154.000 átomos que interagiram sob o potencial Embedded Atom Method (EAM). O estudo focou na estrutura cúbica de corpo centrado (CCC). Esta estrutura apresenta a maior estabilidade estrutural ou a menor energia potencial a 0 K. A liga foi submetida a ensaios de nanoindentação utilizando um penetrador virtual esférico de diâmetro de 40 Å. Ensaiou-se à temperatura de 10 K para eliminar as contribuições térmicas dos átomos, em três planos cristalográficos (001), (011) e (111), e identificar efeitos de anisotropia. A evolução estrutural da liga foi analisada mediante as funções de distribuição radial parcial (PRDF), funções de distribuição radial total (TRDF) e também por difração de raios-X. As curvas de carregamento-descarregamento mostraram que a nanoindentação na superfície correspondente ao plano (011) requer a maior força de indentação, de cerca de 142 nN, enquanto que o plano (111) conduz à maior deformação elástica antes do início da deformação plástica. read less X.-song Huang, L. Liu, W. Liao, J.-J. Huang, H. Sun, and C.-Y. Yu, “Characterization of Nucleation Behavior in Temperature-Induced BCC-to-HCP Phase Transformation for High Entropy Alloy,” Acta Metallurgica Sinica (English Letters). 2021. link Times cited: 6 S. Yamanaka, K. Ikeda, and S. Miura, “The effect of titanium and silicon addition on phase equilibrium and mechanical properties of CoCrFeMnNi-based high entropy alloy,” Journal of Materials Research. 2021. link Times cited: 9 Abstract: The effects of Ti and Si addition on the phase equilibrium a… read more Abstract: The effects of Ti and Si addition on the phase equilibrium and mechanical properties of the equiatomic CoCrFeMnNi high entropy alloy (Cantor alloy) were investigated. The phase equilibrium at 1000 °C was determined from the result of X-ray diffraction and electron probe micro-analysis. Ti addition stabilizes the σ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} $\begin{document}$$\sigma$$\end{document}$ phase, A12 phase and C14-Laves phase, while Si addition stabilizes the A13 phase. The phase relationships were represented by projection onto (Co, Fe, Mn, Ni)–Cr–X(Ti or Si) isothermal ternary cross-section at 1000 °C in Co–Cr–Fe–Mn–Ni–X senary system. Tensile tests were conducted on Cantor-based fcc single solid solution alloys with Ti or Si dissolution at room temperature. The 0.2% yield strength and ultimate tensile strength increased with either element addition. The Ti-added alloy showed higher strength than the Si-added alloy. The difference in ductility in the alloys is related to their strain hardening behavior in the higher strain range. read less
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_893505888031_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_HuangLiuDuan_2021_HfNbTaTiZr__MO_893505888031_002
DOI	10.25950/6f4deef5 https://doi.org/10.25950/6f4deef5 https://commons.datacite.org/doi.org/10.25950/6f4deef5
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_HuangLiuDuan_2021_HfNbTaTiZr__MO_893505888031_001

Verification Check Dashboard

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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 2.61950e-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^-1 continuous. This means that the model has discontinuous energy.	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: Nb

Species: Zr

Species: Ta

Species: Hf

Species: Ti

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: Zr

Species: Nb

Species: Ti

Species: Hf

Species: Ta

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: Nb

Species: Ta

Species: Zr

Species: Ti

Species: Hf

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: Hf

Species: Ta

Species: Zr

Species: Ti

Species: Nb

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: Nb

Species: Ti

Species: Hf

Species: Ta

Species: Zr

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: Zr

Species: Ti

Species: Nb

Species: Hf

Species: Ta

Cubic Crystal Basic Properties Table

Species: Hf

Species: Nb

Species: Ta

Species: Ti

Species: Zr

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 Hf v004	view	29281
Cohesive energy versus lattice constant curve for bcc Nb v004	view	27401
Cohesive energy versus lattice constant curve for bcc Ta v004	view	27361
Cohesive energy versus lattice constant curve for bcc Ti v004	view	40530
Cohesive energy versus lattice constant curve for bcc Zr v004	view	32540
Cohesive energy versus lattice constant curve for diamond Hf v004	view	40600
Cohesive energy versus lattice constant curve for diamond Nb v004	view	32982
Cohesive energy versus lattice constant curve for diamond Ta v004	view	29579
Cohesive energy versus lattice constant curve for diamond Ti v004	view	27401
Cohesive energy versus lattice constant curve for diamond Zr v004	view	25850
Cohesive energy versus lattice constant curve for fcc Hf v004	view	26327
Cohesive energy versus lattice constant curve for fcc Nb v004	view	33792
Cohesive energy versus lattice constant curve for fcc Ta v004	view	26665
Cohesive energy versus lattice constant curve for fcc Ti v004	view	33718
Cohesive energy versus lattice constant curve for fcc Zr v004	view	33497
Cohesive energy versus lattice constant curve for sc Hf v004	view	32319
Cohesive energy versus lattice constant curve for sc Nb v004	view	32982
Cohesive energy versus lattice constant curve for sc Ta v004	view	33939
Cohesive energy versus lattice constant curve for sc Ti v004	view	26367
Cohesive energy versus lattice constant curve for sc Zr v004	view	27431

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 Hf at zero temperature v006	view	59119
Elastic constants for bcc Nb at zero temperature v006	view	79068
Elastic constants for bcc Ta at zero temperature v006	view	62163
Elastic constants for bcc Ti at zero temperature v006	view	60064
Elastic constants for bcc Zr at zero temperature v006	view	58234
Elastic constants for diamond Nb at zero temperature v001	view	282834
Elastic constants for fcc Hf at zero temperature v006	view	85473
Elastic constants for fcc Nb at zero temperature v006	view	84516
Elastic constants for fcc Ta at zero temperature v006	view	81607
Elastic constants for fcc Ti at zero temperature v006	view	75659
Elastic constants for fcc Zr at zero temperature v006	view	59139
Elastic constants for sc Hf at zero temperature v006	view	58492
Elastic constants for sc Nb at zero temperature v006	view	74798
Elastic constants for sc Ta at zero temperature v006	view	89302
Elastic constants for sc Ti at zero temperature v006	view	58423
Elastic constants for sc Zr at zero temperature v006	view	78627

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 Hf in AFLOW crystal prototype A_cF4_225_a v003	view	179758
Equilibrium crystal structure and energy for Nb in AFLOW crystal prototype A_cF4_225_a v003	view	201296
Equilibrium crystal structure and energy for Ta in AFLOW crystal prototype A_cF4_225_a v003	view	161136
Equilibrium crystal structure and energy for Ti in AFLOW crystal prototype A_cF4_225_a v003	view	185763
Equilibrium crystal structure and energy for Zr in AFLOW crystal prototype A_cF4_225_a v003	view	160589
Equilibrium crystal structure and energy for Hf in AFLOW crystal prototype A_cI2_229_a v003	view	160710
Equilibrium crystal structure and energy for Nb in AFLOW crystal prototype A_cI2_229_a v003	view	175674
Equilibrium crystal structure and energy for Ta in AFLOW crystal prototype A_cI2_229_a v003	view	174873
Equilibrium crystal structure and energy for Ti in AFLOW crystal prototype A_cI2_229_a v003	view	178877
Equilibrium crystal structure and energy for Zr in AFLOW crystal prototype A_cI2_229_a v003	view	189766
Equilibrium crystal structure and energy for Hf in AFLOW crystal prototype A_hP2_194_c v003	view	187685
Equilibrium crystal structure and energy for Ti in AFLOW crystal prototype A_hP2_194_c v003	view	147221
Equilibrium crystal structure and energy for Zr in AFLOW crystal prototype A_hP2_194_c v003	view	174873
Equilibrium crystal structure and energy for Hf in AFLOW crystal prototype A_hP3_191_ad v003	view	209944
Equilibrium crystal structure and energy for Ti in AFLOW crystal prototype A_hP3_191_ad v003	view	182560
Equilibrium crystal structure and energy for Ta in AFLOW crystal prototype A_tP22_136_af2i v003	view	448473
Equilibrium crystal structure and energy for Ta in AFLOW crystal prototype A_tP30_136_af2ij v003	view	568498
Equilibrium crystal structure and energy for Ta in AFLOW crystal prototype A_tP4_127_g v003	view	198574

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 Hf v007	view	54096
Equilibrium zero-temperature lattice constant for bcc Nb v007	view	60611
Equilibrium zero-temperature lattice constant for bcc Ta v007	view	66332
Equilibrium zero-temperature lattice constant for bcc Ti v007	view	59726
Equilibrium zero-temperature lattice constant for bcc Zr v007	view	58343
Equilibrium zero-temperature lattice constant for diamond Hf v007	view	62958
Equilibrium zero-temperature lattice constant for diamond Nb v007	view	59209
Equilibrium zero-temperature lattice constant for diamond Ta v007	view	61031
Equilibrium zero-temperature lattice constant for diamond Ti v007	view	66627
Equilibrium zero-temperature lattice constant for diamond Zr v007	view	56364
Equilibrium zero-temperature lattice constant for fcc Hf v007	view	60183
Equilibrium zero-temperature lattice constant for fcc Nb v007	view	66787
Equilibrium zero-temperature lattice constant for fcc Ta v007	view	74283
Equilibrium zero-temperature lattice constant for fcc Ti v007	view	62577
Equilibrium zero-temperature lattice constant for fcc Zr v007	view	62725
Equilibrium zero-temperature lattice constant for sc Hf v007	view	63755
Equilibrium zero-temperature lattice constant for sc Nb v007	view	85357
Equilibrium zero-temperature lattice constant for sc Ta v007	view	65703
Equilibrium zero-temperature lattice constant for sc Ti v007	view	61765
Equilibrium zero-temperature lattice constant for sc Zr v007	view	65644

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 Hf v005	view	748337
Equilibrium lattice constants for hcp Nb v005	view	990122
Equilibrium lattice constants for hcp Ta v005	view	845519
Equilibrium lattice constants for hcp Ti v005	view	1063595
Equilibrium lattice constants for hcp Zr v005	view	1013754

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 Ta at 293.15 K under a pressure of 0 MPa v002		view	8987296

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 Nb v004		view	136360
Broken-bond fit of high-symmetry surface energies in bcc Ta v004		view	118288

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 bcc Nb	view	773531
Monovacancy formation energy and relaxation volume for hcp Hf	view	457772
Monovacancy formation energy and relaxation volume for hcp Ti	view	467711
Monovacancy formation energy and relaxation volume for hcp Zr	view	406680

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 bcc Nb	view	3844978
Vacancy formation and migration energy for hcp Hf	view	1742744
Vacancy formation and migration energy for hcp Ti	view	4293400
Vacancy formation and migration energy for hcp Zr	view	3387721

Errors

ElasticConstantsCubic__TD_011862047401_006

Test	Error Categories	Link to Error page
Elastic constants for diamond Hf at zero temperature v001	other	view
Elastic constants for diamond Ta at zero temperature v001	other	view
Elastic constants for diamond Ti at zero temperature v001	other	view
Elastic constants for diamond Zr at zero temperature v001	other	view

ElasticConstantsHexagonal__TD_612503193866_004

Test	Error Categories	Link to Error page
Elastic constants for hcp Hf at zero temperature v004	other	view
Elastic constants for hcp Nb at zero temperature v004	other	view
Elastic constants for hcp Ta at zero temperature v004	other	view
Elastic constants for hcp Ti at zero temperature v004	other	view
Elastic constants for hcp Zr at zero temperature v004	other	view

EquilibriumCrystalStructure__TD_457028483760_000

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for Ti in AFLOW crystal prototype A_cF4_225_a v000	other	view
Equilibrium crystal structure and energy for Zr in AFLOW crystal prototype A_hP2_194_c v000	other	view

EquilibriumCrystalStructure__TD_457028483760_003

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for Ta in AFLOW crystal prototype A_tP22_81_g5h v003	other	view
Equilibrium crystal structure and energy for Ta in AFLOW crystal prototype A_tP30_113_c3e2f v003	other	view

SurfaceEnergyCubicCrystalBrokenBondFit__TD_955413365818_004

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

Files

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

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MEAM_LAMMPS_HuangLiuDuan_2021_HfNbTaTiZr__MO_893505888031_002.txz	Tar+XZ	Linux and OS X 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
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MEAM_LAMMPS_HuangLiuDuan_2021_HfNbTaTiZr__MO_893505888031_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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