MEAM Potential for the Al-Ni system developed by Silva et al. (2007) v002

A. Costa e Silva; John Agren; M. T. Clavaguera-Mora; D. Djurovic; T. Gomez-Acebo; Byeong-Joo Lee; Zi-Kui Liu; A. P. Miodownik; Hans Jeurgen Seifert

doi:10.25950/845958e4

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MEAM_LAMMPS_CostaAgrenClavaguera_2007_AlNi__MO_131642768288_002

Interatomic potential for Aluminum (Al), Nickel (Ni).
Use this Potential

Title A single sentence description.	MEAM Potential for the Al-Ni system developed by Silva et al. (2007) 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.	LAMMPS MEAM Potential for the Al-Ni system developed by Silva et al. (2007) v000
Species The supported atomic species.	Al, 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	Sang-Ho Oh
Maintainer	Sang-Ho Oh
Developer	A. Costa e Silva John Agren M. T. Clavaguera-Mora D. Djurovic T. Gomez-Acebo Byeong-Joo Lee Zi-Kui Liu A. P. Miodownik Hans Jeurgen Seifert
Published on KIM	2023
How to Cite	This Model originally published in [1] is archived in OpenKIM [2-5]. [1] Silva AC e, Ågren J, Clavaguera-Mora MT, Djurovic D, Gomez-Acebo T, Lee B-J, et al. Applications of computational thermodynamics—the extension from phase equilibrium to phase transformations and other properties. Calphad. 2007;31(1):53–74. doi:10.1016/j.calphad.2006.02.006 — (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] Silva AC e, Agren J, Clavaguera-Mora MT, Djurovic D, Gomez-Acebo T, Lee B-J, et al. MEAM Potential for the Al-Ni system developed by Silva et al. (2007) v002. OpenKIM; 2023. doi:10.25950/845958e4 [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. 46 Citations (6 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 . S. Shang et al., “Generalized stacking fault energy, ideal strength and twinnability of dilute Mg-based alloys: A first-principles study of shear deformation,” Acta Materialia. 2014. link Times cited: 178 K. Tanaka, H. Takamiya, N. Iwata, and K. Nakanishi, “Microstructure and Bond Strength of Steels Using Low-Cr-substituted Cementite Foil,” Isij International. 2011. link Times cited: 0 Abstract: In our previous paper, the eutectic liquid that appears betw… read more Abstract: In our previous paper, the eutectic liquid that appears between the cementite (θ) foil and austenite was proposed to be most suitable for rapid transient-liquid-phase (TLP) bonding of steels. A partial substitution with Cr was required for metastable θ to be thermodynamically stable up to the solidus temperature. On the other hand, the liquid region disappeared quickly by C diffusion, leaving severe Cr segregation along the bonded interface. The present study aims to decrease the ratio of Cr substitution in θ so as to eliminate the homogenization step and allow the use of steel parts as-bonded. Compared to θ with a higher Cr substitution, the synthesized θ with 1 mass% Cr (1Cr-θ) showed an enhanced tendency to decompose on cooling from 1373 K. However, the 1Cr-θ foil was confirmed to give the eutectic liquid that dissolved V during TLP bonding of V-microalloyed steels. After holding for 180 s at 1453 K, a gradient ferrite–pearlite microstructure was obtained in the bond without any boundaries or hard layers due to Cr segregation. The bonded steel showed a tensile strength and elongation corresponding to those of the original V-steel. read less A. Mahata, T. Mukhopadhyay, and M. A. Zaeem, “Modified embedded-atom method interatomic potentials for Al-Cu, Al-Fe and Al-Ni binary alloys: From room temperature to melting point,” Computational Materials Science. 2022. link Times cited: 27 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 G. Neves, H. G. Tirollo, S. Probst, C. Binder, and A. N. Klein, “Application of computational thermodynamics to Fe/Ni, Fe-3%Si/Ni and 316L/Ni systems produced by powder metallurgy,” Powder Metallurgy. 2017. link Times cited: 2 Abstract: ABSTRACT The commercial simulation software packages, Thermo… read more Abstract: ABSTRACT The commercial simulation software packages, Thermo-Calc and DICTRA, are widely used to predict phase formation and diffusion in materials prepared by traditional metallurgical processes. The goal of this work was to clarify whether the software can also be applied to materials produced by powder metallurgy techniques. For this purpose, diffusion couples of the material combinations Fe/Ni, Fe-3%Si/Ni and 316L/Ni were prepared by two techniques: co-pressing of powders followed by co-sintering and joining of two sintered parts followed by annealing. Thermo-Calc and DICTRA were used to predict interface formation and phase transformations during heat treatments. Scanning electron micrography and energy-dispersive X-ray spectrometry showed the formation of interdiffusion interfaces. The diffusion rate was higher in co-sintered couples, resulting in broader interdiffusion zones than those predicted by simulations, but the annealed couples exhibited interdiffusion profiles similar to those predicted by DICTRA simulations. In general, simulations and experimental results showed the same tendencies. read less J. Torrens-Serra, J. Rodríguez-Viejo, and M. Clavaguera-Mora, “Nanocrystallization kinetics and glass forming ability of the Fe 65 Nb 10 B 25 metallic alloy,” Physical Review B. 2007. link Times cited: 27 Abstract: The crystallization kinetics of glassy ${\mathrm{Fe}}_{65}{\… read more Abstract: The crystallization kinetics of glassy ${\mathrm{Fe}}_{65}{\mathrm{Nb}}_{10}{\mathrm{B}}_{25}$ melt-spun ribbons is studied by differential scanning calorimetry in the mode of continuous heating and isothermal annealing and by x-ray diffraction and transmission electron microscopy. Continuous heat treatments of the ribbons show the presence of multiple exothermic peaks before melting. The low-temperature peak corresponds to the precipitation of nanoscale ${\mathrm{Fe}}_{23}{\mathrm{B}}_{6}$-type crystalline metastable phase, and further annealing leads to its transformation into the metastable ${\mathrm{Fe}}_{3}\mathrm{B}$ phase and subsequent formation of $\mathrm{bcc}\text{\ensuremath{-}}\mathrm{Fe}$, ${\mathrm{Fe}}_{2}\mathrm{B}$, and FeNbB stable crystalline phases. The nucleation frequency and the growth rate are determined at selected temperatures from the analysis of the microstructures that emerge during the ${\mathrm{Fe}}_{23}{\mathrm{B}}_{6}$-type nanocrystallization. The master curve method is used to obtain the apparent activation energy and the Avrami exponent at the nanocrystallization onset. The nanocrystallization kinetics is explained in the framework of the Kolmogorov-Johnson-Mehl-Avrami theory. The rejection of insoluble alloy atoms during primary crystallization, the formation of diffusion layers around the crystals, and the decrease in the nucleation frequency caused by alloy enrichment of the residual disordered matrix is modeled through a soft impingement factor. Estimated values for the interfacial energy that provide a satisfactory agreement between experiments and modeling are derived considering that homogeneous nucleation frequency and interface-controlled grain growth are dominant at the onset of the nanocrystallization. Consequently, the time-temperature-transformation diagram is also drawn and the critical cooling rate estimated for this glass forming alloy. read less R. Xiao, K. L. Liu, Y. Ruan, and B. Wei, “Rapid acquisition of liquid thermophysical properties from pure metals to quaternary alloys by proposing a machine learning strategy,” Applied Physics Letters. 2023. link Times cited: 2 Abstract: The establishment of reliable materials genome databases inv… read more Abstract: The establishment of reliable materials genome databases involving the thermophysical properties of liquid metals and alloys promotes the progress of materials research and development, whereas acquiring these properties imposes great challenges on experimental investigation. Here, we proposed a deep learning method and achieved a deep neural network (DNN) interatomic potential for the entire Ti–Ni–Cr–Al system from pure metals to quaternary alloys. This DNN potential exhibited sufficient temperature and compositional transformability which extended beyond the training and provided the prediction of the liquid structure and thermophysical properties for metallic materials with both density functional theory accuracy and classic molecular dynamics efficiency. The predicted results agreed well with the reported experimental data. This work opens a feasible way to address the challenges of rapidly and accurately acquiring thermophysical properties data for liquid pure metals and multicomponent alloys, covering a broad temperature range from superheated to undercooled state. read less B. Waters, D. S. Karls, I. Nikiforov, R. Elliott, E. Tadmor, and B. Runnels, “Automated determination of grain boundary energy and potential-dependence using the OpenKIM framework,” Computational Materials Science. 2022. link Times cited: 5 J. Herrnring, B. Sundman, P. Staron, and B. Klusemann, “Modeling precipitation kinetics for multi-phase and multi-component systems using particle size distributions via a moving grid technique,” Acta Materialia. 2021. link Times cited: 8 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 H. Gog, “First-principles study of dehydration interfaces between diaspore and corundum, gibbsite and boehmite, and boehmite and γ-Al2O3: Energetic stability, interface charge effects, and dehydration defects,” Applied Surface Science. 2020. link Times cited: 13 D. Zhang, Y. Xue, D. Tian, C. Zeng, Y. Fu, and Y.-fang Tian, “Theoretical investigation the growth of Fe3Si on GaAs: Stability and electronic properties of Fe3Si/GaAs(0 0 1), (1 1 0) via DFT,” Applied Surface Science. 2020. link Times cited: 3 E. D. M. Alvares, W. Botta, J. Ågren, and A. C. Silva, “An assessment of Fe-Nb-B melts using the two-state liquid model,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2020. link Times cited: 3 G. Neves, E. Pio, P. Martin, C. Aguilar, C. Binder, and A. N. Klein, “Semi-empirical computational thermodynamic calculations used to predict carbide dissociation in Fe matrix,” Materials Chemistry and Physics. 2020. link Times cited: 11 W. Dong, Z. Chen, and B.-J. Lee, “Modified embedded-atom interatomic potential for Co–W and Al–W systems,” Transactions of Nonferrous Metals Society of China. 2015. link Times cited: 9 A. C. E. Silva, “Importance of Interfacial Energy in Precipitation Modeling Using Computational Thermodynamics Techniques.” 2015. link Times cited: 3 Y.-hong Zhao, Z. Wen, H. Hou, W. Guo, and P. Han, “Density functional theory study of the interfacial properties of Ni/Ni3Si eutectic alloy,” Applied Surface Science. 2014. link Times cited: 11 W. Dong, H.-K. Kim, W. Ko, B.-M. Lee, and B.-J. Lee, “Atomistic modeling of pure Co and Co–Al system,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2012. link Times cited: 42 M. Easton et al., “The role of crystallography and thermodynamics on phase selection in binary magnesium–rare earth (Ce or Nd) alloys,” Acta Materialia. 2012. link Times cited: 63 V. Tomashik, “C-N-Si Ternary Phase Diagram Evaluation,” MSI Eureka. 2012. link Times cited: 0 B.-J. Lee, W. Ko, H.-K. Kim, and E.-H. Kim, “The modified embedded-atom method interatomic potentials and recent progress in atomistic simulations,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2010. link Times cited: 137 Z.-kui Liu, “A materials research paradigm driven by computation,” JOM. 2009. link Times cited: 18 L. Zhang et al., “Thermodynamic properties of the Al–Fe–Ni system acquired via a hybrid approach combining calorimetry, first-principles and CALPHAD,” Acta Materialia. 2009. link Times cited: 85 L. Zhang et al., “Phase equilibria and thermal analysis in the Fe–Mn–Ni system,” International Journal of Materials Research. 2009. link Times cited: 15 Abstract: Based on the critical review of the experimental data availa… read more Abstract: Based on the critical review of the experimental data available in the literature, 7 decisive ternary alloys were prepared. New phase transition temperatures and phase equilibria at 800°C in the Fe – Mn – Ni system were measured. An effective method to accurately determine phase transition temperatures from differential thermal analysis curves with overlapped peaks and nonlevel baselines within a narrow temperature range was developed. A massive transformation was observed in one quenched Fe-rich alloy. In order to make the fcc_A1 phase always in the fully disordered state in the ternary system, the effect of the binary reciprocal parameter on the Gibbs energy of ternary ordered L12 phase was considered. It was found that the introduction of only one parameter could describe all reliable experimental data in the Fe – Mn – Ni system satisfactorily. The presently obtained parameters were successfully applied in two practical cases. read less L. Zhang et al., “Thermodynamic description of the C-Fe-Mn system with key experiments and its practical applications,” International Journal of Materials Research. 2008. link Times cited: 11 Abstract: Based on the critically reviewed experimental data available… read more Abstract: Based on the critically reviewed experimental data available in the literature, new phase transition temperatures and phase equilibria at 800 °C close to the Cu-Fe side of the Cu-Fe-Mn system were measured in the present work. The composition-invariant (γFe, γMn) → (αFe) massive transformations were observed in the two quenched alloys in the Fe-rich region. A set of consistent thermodynamic parameters of the Cu-Fe-Mn system was then obtained by taking into account all kinds of experimental data. Comparisons between the calculated and measured phase diagrams indicate that most of the experimental information is satisfactorily described by the present thermodynamic modeling. The liquidus isolines, liquidus projection and reaction scheme of this ternary system are also presented. Significant improvements have been made, compared with the previous assessments. The presently obtained parameters were applied in successfully solving the !surface fissure" during hot rolling of steel and controlling the micro-structure of the Cu-Fe based alloys in rapid solidification. read less H.-K. Kim, W. Jung, and B.-J. Lee, “Modified embedded-atom method interatomic potentials for the Fe–Ti–C and Fe–Ti–N ternary systems,” Acta Materialia. 2008. link Times cited: 121 L.-qing Chen and Y. Gu, “27 – Computational Metallurgy.” 2014. link Times cited: 3 M. Strangwood, “Fundamentals of ferrite formation in steels.” 2012. link Times cited: 11 Abstract: Abstract: The diffusional formation of ferrite at low underc… read more Abstract: Abstract: The diffusional formation of ferrite at low undercoolings has, historically, been extensively researched, which has led to well-established mechanisms for nucleation and growth. These have been verified against experimental data to allow modelling with good agreement to experiment, often as transformation diagrams. These mechanisms are summarised here and opportunities for improvement through advances in experimentation and computation are highlighted. read less V. Tomashik, “Carbon – Nitrogen – Silicon.” 2010. link Times cited: 1 S. Yang, J. Zhong, J. Wang, L. Zhang, and G. Kaptay, “OpenIEC: an open-source code for interfacial energy calculation in alloys,” Journal of Materials Science. 2019. link Times cited: 12 A. Walle and M. Asta, “High-throughput calculations in the context of alloy design,” MRS Bulletin. 2019. link Times cited: 24 Abstract: Modern approaches to alloy design increasingly exploit the f… read more Abstract: Modern approaches to alloy design increasingly exploit the framework of computational thermodynamics and kinetics to guide the selection of alloy compositions and processing strategies, to achieve desired microstructures, and yield tailored properties. In this context, phase diagrams play a critical role and their assessment can represent a bottleneck in the design of new multicomponent systems. In recent years, it has become possible to accelerate this process through the coupling of the CALculation of PHAse Diagram (CALPHAD) computational thermodynamics framework with high-throughput quantum mechanical calculations. This article reviews recent developments and applications in this area, and discusses future opportunities for high-throughput calculations in the context of modeling kinetics, highlighting the important role of interfacial processes and atomic mobilities. read less D. Schmidmair, V. Kahlenberg, and A. Grießer, “K2CaSi4O10: A novel phase in the ternary system K2O–CaO–SiO2 and member of the litidionite group of crystal structures,” Journal of the American Ceramic Society. 2018. link Times cited: 6 S. Liu et al., “Refinement effect of TiC on ferrite by molecular statics/dynamics simulations and first-principles calculations,” Journal of Alloys and Compounds. 2018. link Times cited: 3 H. Colpaert, “Equilibrium Phases and Constituents in the Fe–C System,” Metallography, Microstructure, and Analysis. 2017. link Times cited: 1 A. C. E. Silva, “Applications of Multicomponent Databases to the Improvement of Steel Processing and Design,” Journal of Phase Equilibria and Diffusion. 2017. link Times cited: 7 Y.-K. Kim, W. Jung, and B.-J. Lee, “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. link Times cited: 32 Abstract: Interatomic potentials for the Ni–Co binary and Ni–Al–Co ter… read more Abstract: 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. 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. read less W. Dong, B.-J. Lee, and Z. Chen, “Atomistic modeling for interfacial properties of Ni-Al-V ternary system,” Metals and Materials International. 2014. link Times cited: 6 C. Campbell, U. Kattner, and Z.-kui Liu, “The development of phase-based property data using the CALPHAD method and infrastructure needs,” Integrating Materials and Manufacturing Innovation. 2014. link Times cited: 41 S. Shang, C. L. Zacherl, H. Fang, Y. Wang, Y. Du, and Z. Liu, “Effects of alloying element and temperature on the stacking fault energies of dilute Ni-base superalloys,” Journal of Physics: Condensed Matter. 2012. link Times cited: 127 Abstract: A systematic study of stacking fault energy (γSF) resulting … read more Abstract: A systematic study of stacking fault energy (γSF) resulting from induced alias shear deformation has been performed by means of first-principles calculations for dilute Ni-base superalloys (Ni23X and Ni71X) for various alloying elements (X) as a function of temperature. Twenty-six alloying elements are considered, i.e., Al, Co, Cr, Cu, Fe, Hf, Ir, Mn, Mo, Nb, Os, Pd, Pt, Re, Rh, Ru, Sc, Si, Ta, Tc, Ti, V, W, Y, Zn, and Zr. The temperature dependence of γSF is computed using the proposed quasistatic approach based on a predicted γSF–volume–temperature relationship. Besides γSF, equilibrium volume and the normalized stacking fault energy (ΓSF = γSF/Gb, with G the shear modulus and b the Burgers vector) are also studied as a function of temperature for the 26 alloying elements. The following conclusions are obtained: all alloying elements X studied herein decrease the γSF of fcc Ni, approximately the further the alloying element X is from Ni on the periodic table, the larger the decrease of γSF for the dilute Ni–X alloy, and roughly the γSF of Ni–X decreases with increasing equilibrium volume. In addition, the values of γSF for all Ni–X systems decrease with increasing temperature (except for Ni–Cr at higher Cr content), and the largest decrease is observed for pure Ni. Similar to the case of the shear modulus, the variation of γSF for Ni–X systems due to various alloying elements is traceable from the distribution of (magnetization) charge density: the spherical distribution of charge density around a Ni atom, especially a smaller sphere, results in a lower value of γSF due to the facility of redistribution of charges. Computed stacking fault energies and the related properties are in favorable accord with available experimental and theoretical data. read less S. G. Popov, V. Lysenko, and V. N. Proselkov, “Thermodynamic simulation of phase equilibria in the UO2-Gd2O3 system at high temperatures,” High Temperature. 2012. link Times cited: 2 S. G. Popov, V. N. Proselkov, and V. Lysenko, “Thermodynamic analysis of uranium–gadolinium fuel stability at high temperatures,” Atomic Energy. 2011. link Times cited: 7 A. Ardell, “A1-L12 interfacial free energies from data on coarsening in five binary Ni alloys, informed by thermodynamic phase diagram assessments,” Journal of Materials Science. 2011. link Times cited: 57 S. Lee, “SiC Particulate‐Reinforced Si–C–N—Highly Oxidation Resistant Composites at 1500°C in Air,” International Journal of Applied Ceramic Technology. 2009. link Times cited: 1 Abstract: The thermal stability and high-temperature strength of SiC f… read more Abstract: The thermal stability and high-temperature strength of SiC filler/Si―C―N matrix particulate-reinforced ceramic (PRC) composites were investigated. The PRC retained 115% of the room temperature strength at 1500°C in air because of the crack-healing behavior. The thickness of SiO 2 formed on the PRC was 3 μm after an oxidation at 1500°C for 100 h in air. The strength of the PRC did not strongly decrease after the prolonged oxidation for 100 h. The SiC/Si―C―N PRC are a promising candidate for the applications at extremely high temperatures in air. read less K. Tanaka, H. Ikehata, K. Nakanishi, and T. Nishikawa, “Growth Simulation of Spheroidized Carbide in the Carbide-Dispersed Carburizing Process,” Metallurgical and Materials Transactions A. 2008. link Times cited: 5 U. Kattner, “THE CALPHAD METHOD AND ITS ROLE IN MATERIAL AND PROCESS DEVELOPMENT.,” Tecnologia em metalurgia, materiais e mineracao. 2016. link Times cited: 81 Abstract: Successful design of materials and manufacturing processes r… read more Abstract: Successful design of materials and manufacturing processes requires the availability of reliable materials data. Commercial alloys usually contain a large number of elements, and the needed data for the design of new materials and processes are rarely available. The CALPHAD (CALculation of PHAse Diagrams) method enables the development of thermodynamic and property databases, that in conjunction with extrapolation methods of the descriptions of binary and ternary systems to higher-order systems, allow the calculation of data for higher-order systems. The results obtained from CALPHAD calculations have been shown to be invaluable in the design of new materials. This review presents an overview of the CALPHAD method, software tools and databases and gives examples of its application. read less A. C. E. Silva, F. Beneduce, and R. Avillez, “LIQUID IRON DEOXIDATION BY ALUMINUM: A BRIEF REVIEW OF EXPERIMENTAL DATA AND THERMODYNAMIC DESCRIPTION,” Tecnologia em Metalurgia, Materiais e Mineração. 2015. link Times cited: 7 Abstract: The iron-oxygen-aluminum equilibrium has been a subject of i… read more Abstract: The iron-oxygen-aluminum equilibrium has been a subject of interest for many years due to its importance in the steel industry. A great percentage of all flat rolled steel is aluminum killed “AK” (deoxidized) low-carbon steel, not only because of the low soluble oxygen contents that can be achieved but also because of the importance of the residual aluminum in forming aluminum nitride that is one of the main tools used to achieve crystallographic texture adequate for forming. The behavior both of oxygen and of aluminum in liquid iron are relatively well understood and quantified, as is the free energy of formation of alumina. Nonetheless, the Fe-Al-O behavior at liquid iron temperatures is not fully understood and considerable controversy still prevails. Thus, the objectives of this work are (a) to critically review the experimental work and assessments performed mainly on the Al-Fe-O–Al2O3 equilibrium, (b) to evaluate the current models used to describe this equilibrium and (c) to present a recommendation about the data, based on its evaluated reliability and consistency. read less
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_131642768288_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_CostaAgrenClavaguera_2007_AlNi__MO_131642768288_002
DOI	10.25950/845958e4 https://doi.org/10.25950/845958e4 https://commons.datacite.org/doi.org/10.25950/845958e4
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_CostaAgrenClavaguera_2007_AlNi__MO_131642768288_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 3.50912e-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
N/A Unable to perform verification check due to an error.	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: Al

Species: Ni

Cohesive Energy Graph

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

Species: Al

Species: Ni

Diamond Lattice Constant

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

Species: Al

Species: Ni

Dislocation Core Energies

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

(No matching species)

FCC Elastic Constants

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

Species: Ni

Species: Al

FCC Lattice Constant

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

Species: Ni

Species: Al

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: Al

Species: Ni

FCC Surface Energies

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

Species: Al

Species: Ni

SC Lattice Constant

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

Species: Al

Species: Ni

Cubic Crystal Basic Properties Table

Species: Al

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	7877
Cohesive energy versus lattice constant curve for bcc Ni v004	view	7509
Cohesive energy versus lattice constant curve for diamond Al v004	view	7877
Cohesive energy versus lattice constant curve for diamond Ni v004	view	7877
Cohesive energy versus lattice constant curve for fcc Al v004	view	7877
Cohesive energy versus lattice constant curve for fcc Ni v004	view	7657
Cohesive energy versus lattice constant curve for sc Al v004	view	8025
Cohesive energy versus lattice constant curve for sc Ni v004	view	7804

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 AlNi in AFLOW crystal prototype A3B2_hP5_164_ad_d at zero temperature and pressure v000		view	494877

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	33497
Elastic constants for bcc Ni at zero temperature v006	view	28418
Elastic constants for diamond Al at zero temperature v001	view	43289
Elastic constants for diamond Ni at zero temperature v001	view	33757
Elastic constants for fcc Al at zero temperature v006	view	31289
Elastic constants for fcc Ni at zero temperature v006	view	24815
Elastic constants for sc Al at zero temperature v006	view	20479
Elastic constants for sc Ni at zero temperature v006	view	43289

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 AlNi in AFLOW crystal prototype A3B2_hP5_164_ad_d v002	view	89375
Equilibrium crystal structure and energy for AlNi in AFLOW crystal prototype A3B5_oC16_65_ah_bej v002	view	86872
Equilibrium crystal structure and energy for AlNi in AFLOW crystal prototype A3B_oP16_62_cd_c v002	view	71636
Equilibrium crystal structure and energy for AlNi in AFLOW crystal prototype A4B3_cI112_230_af_g v002	view	1257246
Equilibrium crystal structure and energy for Al in AFLOW crystal prototype A_cF4_225_a v002	view	64831
Equilibrium crystal structure and energy for Ni in AFLOW crystal prototype A_cF4_225_a v002	view	59180
Equilibrium crystal structure and energy for Al in AFLOW crystal prototype A_cI2_229_a v002	view	70013
Equilibrium crystal structure and energy for Ni in AFLOW crystal prototype A_cI2_229_a v002	view	58147
Equilibrium crystal structure and energy for Ni in AFLOW crystal prototype A_hP2_194_c v002	view	46664
Equilibrium crystal structure and energy for AlNi in AFLOW crystal prototype AB3_cF16_225_a_bc v002	view	128983
Equilibrium crystal structure and energy for AlNi in AFLOW crystal prototype AB3_cP4_221_a_c v002	view	60335
Equilibrium crystal structure and energy for AlNi in AFLOW crystal prototype AB_cP2_221_a_b v002	view	94897

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 Ni v001	view	40210634
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Al v001	view	66393121
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Al v001	view	36035780
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Ni v001	view	71248141

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	17475
Equilibrium zero-temperature lattice constant for bcc Ni v007	view	16122
Equilibrium zero-temperature lattice constant for diamond Al v007	view	21245
Equilibrium zero-temperature lattice constant for diamond Ni v007	view	14209
Equilibrium zero-temperature lattice constant for fcc Al v007	view	17197
Equilibrium zero-temperature lattice constant for fcc Ni v007	view	16361
Equilibrium zero-temperature lattice constant for sc Al v007	view	19878
Equilibrium zero-temperature lattice constant for sc Ni v007	view	16839

LatticeConstantHexagonalEnergy__TD_942334626465_005

Equilibrium lattice constants for hexagonal bulk structures at zero temperature and pressure v005

Creators: Daniel S. Karls and Junhao Li
Contributor: karls
Publication Year: 2019
DOI: https://doi.org/10.25950/c339ca32

Calculates lattice constant of hexagonal bulk structures at zero temperature and pressure by using simplex minimization to minimize the potential energy.

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Equilibrium lattice constants for hcp Al v005		view	184935
Equilibrium lattice constants for hcp Ni v005		view	168992

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	3387188
Linear thermal expansion coefficient of fcc Ni at 293.15 K under a pressure of 0 MPa v002		view	5827431

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 Al v004		view	86887
Phonon dispersion relations for fcc Ni v004		view	117646

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	42344009
Stacking and twinning fault energies for fcc Ni v002		view	55742655

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	133744
Broken-bond fit of high-symmetry surface energies in fcc Ni v004		view	173627

VacancyFormationEnergyRelaxationVolume__TD_647413317626_001

Monovacancy formation energy and relaxation volume for cubic and hcp monoatomic crystals v001

Creators:
Contributor: efuem
Publication Year: 2023
DOI: https://doi.org/10.25950/fca89cea

Computes the monovacancy formation energy and relaxation volume for cubic and hcp monoatomic crystals.

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Monovacancy formation energy and relaxation volume for fcc Al		view	562313
Monovacancy formation energy and relaxation volume for fcc Ni		view	844059

VacancyFormationMigration__TD_554849987965_001

Vacancy formation and migration energies for cubic and hcp monoatomic crystals v001

Creators:
Contributor: efuem
Publication Year: 2023
DOI: https://doi.org/10.25950/c27ba3cd

Computes the monovacancy formation and migration energies for cubic and hcp monoatomic crystals.

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Vacancy formation and migration energy for fcc Al		view	1147523
Vacancy formation and migration energy for fcc Ni		view	1381489

Errors

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 Ni at zero temperature v004	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

GrainBoundaryCubicCrystalSymmetricTiltRelaxedEnergyVsAngle__TD_410381120771_003

Test	Error Categories	Link to Error page
Relaxed energy as a function of tilt angle for a 100 symmetric tilt grain boundary in fcc Al v003	other	view
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
DimerContinuityC1__VC_303890932454_005	other	view

Files

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

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MEAM_LAMMPS_CostaAgrenClavaguera_2007_AlNi__MO_131642768288_002.txz	Tar+XZ	Linux and OS X archive
MEAM_LAMMPS_CostaAgrenClavaguera_2007_AlNi__MO_131642768288_002.zip	Zip	Windows archive

Download Dependency

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

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

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MEAM_LAMMPS_CostaAgrenClavaguera_2007_AlNi__MO_131642768288_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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