MEAM potential for Fe developed by Etesami and Asadi (2018) v002

Seyed-Alireza Etesami; Ebrahim Asadi

doi:10.25950/88bf887e

Jump to: Tests | Visualizers | Files | Wiki

MEAM_LAMMPS_EtesamiAsadi_2018_Fe__MO_549900287421_002

Interatomic potential for Iron (Fe).
Use this Potential

Title A single sentence description.	MEAM potential for Fe developed by Etesami and Asadi (2018) 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.	Availability of a reliable interatomic potential is one of the major challenges in utilizing molecular dynamics (MD) for simulations of metals near the melting temperatures and melting point (MP). Here, we propose a novel approach to address this challenge in the concept of modified-embedded-atom (MEAM) interatomic potential; also, we apply the approach to iron, nickel, copper, and aluminum as case studies. We propose adding experimentally available high-temperature elastic constants and MP of the element to the list of typical low-temperature properties used for the development of MD interatomic potential parameters. We show that the proposed approach results in a reasonable agreement between the MD calculations of melting properties such as latent heat, expansion in melting, liquid structure factor, and solid-liquid interface stiffness and their experimental/computational counterparts. Then, we present the physical properties of mentioned elements near melting temperatures using the new MEAM parameters. We observe that the behavior of elastic constants, heat capacity, and thermal linear expansion coefficient at room temperature compared to MP follows an empirical linear relation (α±β × MP) for transition metals. Furthermore, a linear relation between the tetragonal shear modulus and the enthalpy change from room temperature to MP is observed for face-centered cubic materials.
Species The supported atomic species.	Fe
Disclaimer A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.	None
Content Origin	NIST IPRP (https://www.ctcms.nist.gov/potentials/Fe.html)
Content Other Locations	https://openkim.org/id/Sim_LAMMPS_MEAM_EtesamiAsadi_2018_Fe__SM_267016608755_000

Contributor	Yaser Afshar
Maintainer	Yaser Afshar
Developer	Seyed-Alireza Etesami Ebrahim Asadi
Published on KIM	2023
How to Cite	This Model originally published in [1] is archived in OpenKIM [2-5]. [1] Etesami SA, Asadi E. Molecular dynamics for near melting temperatures simulations of metals using modified embedded-atom method. Journal of Physics and Chemistry of Solids. 2018;112:61–72. doi:10.1016/j.jpcs.2017.09.001 — (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] Etesami S-A, Asadi E. MEAM potential for Fe developed by Etesami and Asadi (2018) v002. OpenKIM; 2023. doi:10.25950/88bf887e [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. 69 Citations (53 used) Show Model Used Show All Help us to determine which of the papers that cite this potential actually used it to perform calculations. If you know, click the . B. Waters, D. S. Karls, I. Nikiforov, R. Elliott, E. Tadmor, and B. Runnels, “Automated determination of grain boundary energy and potential-dependence using the OpenKIM framework,” Computational Materials Science. 2022. link Times cited: 5 N. Chen, Q. Peng, Z. Jiao, I. van Rooyen, W. Skerjanc, and F. Gao, “Analytical bond-order potential for silver, palladium, ruthenium and iodine bulk diffusion in silicon carbide,” Journal of Physics: Condensed Matter. 2019. link Times cited: 6 Abstract: The analytical bond-order potential has been developed for s… read more Abstract: The analytical bond-order potential has been developed for simulating fission product (Ag, Pd, Ru, and I) behavior in SiC, especially for their diffusion. We have proposed adding experimentally available elastic constants and physical properties of the elements as well as important defect formation energies calculated from density functional theory simulation to the list of typical properties as the extensive fitting database. The results from molecular dynamics simulations are in a reasonable agreement with defect properties and energy barriers of their experimental/computational counterparts. The successful validation of the new potential has established a good reliability and transferability of the potentials, which enables the ability of simulation in extended scale. The kinetic behavior such as diffusion of different interstitials is then realized by applying the new interatomic potentials. The bulk diffusion is less likely to dominate the transport of the four fission products under pure thermal condition, when we refer to their extremely small values of the effective diffusion coefficients. The interstitial mechanism is hard for Pd, Ru, and I to access due to the high formation energy and high migration energy. However, it is found that the migration energy of silver is relatively low, which indicates Ag diffusion via an interstitial mechanism being feasible, especially under irradiation condition, where massive interstitials can be formed in high-temperature nuclear reactors. read less W. Dednam et al., “Directional bonding explains the high conductance of atomic contacts in bcc metals,” Physical Review B. 2019. link Times cited: 3 Abstract: Atomic-sized junctions of iron, created by controlled ruptur… read more Abstract: Atomic-sized junctions of iron, created by controlled rupture, present unusually high values of conductance compared to other metals. This result is counter-intuitive since, at the nanoscale, body-centered cubic metals are expected to exhibit lower coordination than face-centered cubic metals. In this work, classical molecular dynamics simulations of contact rupture, using an interatomic potential that accounts for directional bonding, yield highly-coordinated stable structures before rupture, unlike an isotropic bonding potential, which results in the expected stable single-atom contacts. Density functional theory electronic transport calculations show that conductance values of these highly coordinated and highly stable structures, can explain the experimentally measured values for conductance of body-centered cubic atomic contacts, thus revealing the important role of directional bonding in these metals. read less S. M. Handrigan and S. Nakhla, “Generation of viable nanocrystalline structures using the melt-cool method: the influence of force field selection,” Philosophical Magazine. 2023. link Times cited: 0 Z. Zou and P. Tiwary, “Enhanced sampling of Crystal Nucleation with Graph Representation Learnt Variables,” ArXiv. 2023. link Times cited: 1 Abstract: In this study, we present a graph neural network-based learn… read more Abstract: In this study, we present a graph neural network-based learning approach using an autoencoder setup to derive low-dimensional variables from features observed in experimental crystal structures. These variables are then biased in enhanced sampling to observe state-to-state transitions and reliable thermodynamic weights. Our approach uses simple convolution and pooling methods. To verify the effectiveness of our protocol, we examined the nucleation of various allotropes and polymorphs of iron and glycine from their molten states. Our graph latent variables when biased in well-tempered metadynamics consistently show transitions between states and achieve accurate free energy calculations in agreement with experiments, both of which are indicators of dependable sampling. This underscores the strength and promise of our graph neural net variables for improved sampling. The protocol shown here should be applicable for other systems and with other sampling methods. read less C. Li, S. Lu, S. Divinski, and L. Vitos, “Theoretical and experimental grain boundary energies in body-centered cubic metals,” Acta Materialia. 2023. link Times cited: 3 O. Klimanova, T. Miryashkin, and A. Shapeev, “Accurate melting point prediction through autonomous physics-informed learning,” Physical Review B. 2023. link Times cited: 0 Abstract: We present an algorithm for computing melting points by auto… read more Abstract: We present an algorithm for computing melting points by autonomously learning from coexistence simulations in the NPT ensemble. Given the interatomic interaction model, the method makes decisions regarding the number of atoms and temperature at which to conduct simulations, and based on the collected data predicts the melting point along with the uncertainty, which can be systematically improved with more data. We demonstrate how incorporating physical models of the solid-liquid coexistence evolution enhances the algorithm's accuracy and enables optimal decision-making to effectively reduce predictive uncertainty. To validate our approach, we compare the results of 20 melting point calculations from the literature to the results of our calculations, all conducted with same interatomic potentials. Remarkably, we observe significant deviations in about one-third of the cases, underscoring the need for accurate and reliable algorithms for materials property calculations. read less T. Chen et al., “Grain boundary serration tuning and its effect on hot workability of a wrought superalloy,” Journal of Alloys and Compounds. 2023. link Times cited: 0 S. Kazanç and C. Canbay, “Investigation of microstructural development of liquid Nb in dependence of cooling rate: Molecular dynamics simulation study,” Vacuum. 2023. link Times cited: 1 S. Paul, D. Schwen, M. Short, and K. Momeni, “A Modified Embedded-Atom Method Potential for a Quaternary Fe-Cr-Si-Mo Solid Solution Alloy,” Materials. 2023. link Times cited: 0 Abstract: Ferritic-martensitic steels, such as T91, are candidate mate… read more Abstract: Ferritic-martensitic steels, such as T91, are candidate materials for high-temperature applications, including superheaters, heat exchangers, and advanced nuclear reactors. Considering these alloys’ wide applications, an atomistic understanding of the underlying mechanisms responsible for their excellent mechano-chemical properties is crucial. Here, we developed a modified embedded-atom method (MEAM) potential for the Fe-Cr-Si-Mo quaternary alloy system—i.e., four major elements of T91—using a multi-objective optimization approach to fit thermomechanical properties reported using density functional theory (DFT) calculations and experimental measurements. Elastic constants calculated using the proposed potential for binary interactions agreed well with ab initio calculations. Furthermore, the computed thermal expansion and self-diffusion coefficients employing this potential are in good agreement with other studies. This potential will offer insightful atomistic knowledge to design alloys for use in harsh environments. read less C. Zhang, Q. Liao, X. Zhang, F. Ma, M. Wu, and Q. Xu, “Characterization of porosity in lack of fusion pores in selective laser melting using the wavefunction,” Materials Research Express. 2022. link Times cited: 0 Abstract: Selective laser melting (SLM) is used extensively in the man… read more Abstract: Selective laser melting (SLM) is used extensively in the manufacture of components for both production and domestic applications. However, the lack of fusion pores is one of the most common defects in the SLM process, affecting the performance and life of the part and hindering the development of the SLM process. Meanwhile, the defects are particularly sensitive to changes in SLM process parameters. The micro-selective laser melting (μ SLM) model was established by molecular dynamics simulation, and the lack of fusion pores in the melt pool was analyzed by a multifunctional wavefunction analyzer to understand the difference of the porosities under different processes. The results show that both laser power and scanning speed can prolong the existence time of the melt pool by changing the input energy density. The melted powder has more time to fill the lack of fusion pores, thus reducing the porosity. The larger scanning spacing hinders the combination of adjacent melt pools, leading to an increase in porosity. Reducing scanning spacing will lead to sintering or remelting, thus improving the bonding quality of adjacent melt pools and effectively reducing porosity. read less H. Deng, J. Comer, and B. Liu, “A high-dimensional neural network potential for molecular dynamics simulations of condensed phase nickel and phase transitions,” Molecular Simulation. 2022. link Times cited: 0 Abstract: ABSTRACT A high-dimensional neural network interatomic poten… read more Abstract: ABSTRACT A high-dimensional neural network interatomic potential was developed and used in molecular dynamics simulations of condensed phase Ni and Ni systems with liquid–solid phase coexistence. The reference data set was generated by sampling the potential energy surface over a broad temperature-pressure domain using ab initio MD simulations to train a unified potential. Excellent agreement was achieved between bulk face-centred cubic nickel thermal expansion simulations and relevant experimental data. The same potential also yields accurate structures and diffusivities in the liquid state. The phase transition between liquid and solid phases was simulated using the two-phase interface method. The predicted melting point temperature is within a few kelvins of the literature value. The general methodology could be applied to describe crystals with much more complex phase behaviours. read less J.-L. Lee et al., “Effect of serrated grain boundary on tensile and creep properties of a precipitation strengthened high entropy alloy,” Science and Technology of Advanced Materials. 2022. link Times cited: 6 Abstract: ABSTRACT In this study, tensile and creep deformation of a h… read more Abstract: ABSTRACT In this study, tensile and creep deformation of a high-entropy alloy processed by selective laser melting (SLM) has been investigated; hot ductility drop was identified at first, and the loss of ductility at elevated temperature was associated with intergranular fracture. By modifying the grain boundary morphology from straight to serration, the hot ductility drop issue has been resolved successfully. The serrated grain boundary could be achieved by reducing the cooling rate of solution heat treatment, which allowed the coarsening of L12 structured γ′ precipitates to interfere with mobile grain boundaries, resulting in undulation of the grain boundary morphology. Tensile and creep tests at 650°C were conducted, and serrated grain boundary could render a significant increase in tensile fracture strain and creep rupture life by a factor of 3.5 and 400, respectively. Detailed microstructure analysis has indicated that serrated grain boundary could distribute strains more evenly than that of straight morphology. The underlying mechanism of deformation with grain boundary serration was further demonstrated by molecular dynamic simulation, which has indicated that serrated grain boundaries could reduce local strain concentration and provide resistance against intergranular cracking. This is the first study to tackle the hot ductility drop issue in a high-entropy alloy fabricated by SLM; it can provide a guideline to develop future high-entropy alloys and design post heat treatment for elevated temperature applications. GRAPHICAL ABSTRACT read less S. Luo et al., “Thermal Behavior of Li Electrode in All-Solid-State Batteries and Improved Performance by Temperature Modulation,” SSRN Electronic Journal. 2022. link Times cited: 3 S. S. M. N. Souq, F. A. Ghasemi, and M. M. S. Fakhrabadi, “Performance of different traditional and machine learning-based atomistic potential functions in the simulation of mechanical behavior of Fe nanowires,” Computational Materials Science. 2022. link Times cited: 0 X.-W. Wang, X. Sun, T. Song, J. Tian, and Z.-J. Liu, “Prediction of the melting curve and phase diagram for CaO using newly developed interatomic potentials,” Vacuum. 2022. link Times cited: 3 J. Shi, W. Xiao, J. Wang, and H. Yang, “A molecular dynamics study on sintering behavior and densification characterization of nanocopper,” Journal of Physics: Conference Series. 2022. link Times cited: 0 Abstract: The technical problem of copper additive manufacturing is ex… read more Abstract: The technical problem of copper additive manufacturing is expected to be solved through the size effect of nanomaterials. The molecular dynamics method was employed to understand the laser sintering process of single-crystal copper nanoparticles. Based on a theoretical characterization of the densification of nanocopper sintering developed at present and the prediction of the melting point of nanocopper, the sintering and densification behaviors of copper nanoparticles with different sizes at different sintering temperatures were investigated. It is finally concluded that the densification of the nanocopper sinter can reach up to 95% under the condition of sintering temperature below the melting point of the nanocopper. read less N. Gui, Q. Wang, X. Zhang, X. Yang, J. Tu, and S. Jiang, “Diffusion and Thermo-Driven Migration of Silver, Palladium and Ruthenium Nanoparticles in Cubic Sic Matrix Using Molecular Dynamics,” SSRN Electronic Journal. 2022. link Times cited: 1 Y. Wang, F. Wang, W. Yu, Y. Wang, Z. Qi, and Y. Wang, “Effects of pressure on volatilisation of pure Bi nanoparticles and Bi–Fe core–shell nanoparticles during continuous heating: a molecular dynamics study,” Molecular Physics. 2022. link Times cited: 3 Abstract: In the present work, the molecular dynamics study method has… read more Abstract: In the present work, the molecular dynamics study method has been utilised to investigate the effects of pressure on the volatilisation of pure Bi nanoparticles and Bi–Fe core–shell nanoparticles during continuous heating. Computational total energy curves between 300 and 2000 K are used to explore the structural changes of nanoparticles under different pressures. On the other hand, the radial distribution function is examined to determine the structural evolution of a system. The calculated root mean square displacement curves under pressures of 0–5 GPa between 300 and 2000 K are employed to explore the diffusion of Bi element and the calculated volatilisation rate of Bi element is used to quantitatively obtain the volatilisation characteristics. The volatilisation patterns of pure Bi nanoparticles and Bi–Fe core–shell nanoparticles are different under different temperatures and pressures. The results show that the volatilisation of Bi element is increasing during the heating from 300 to 2000 K, and the volatilisation decreases with the increase of pressure. Furthermore, the Fe shell can effectively decrease the volatilisation of the Bi element. GRAPHICAL ABSTRACT read less Y. Lei et al., “An Embedded-Atom Method Potential for studying the properties of Fe-Pb solid-liquid interface,” Journal of Nuclear Materials. 2022. link Times cited: 1 L. Zhang, G. Csányi, E. Giessen, and F. Maresca, “Atomistic fracture in bcc iron revealed by active learning of Gaussian approximation potential,” npj Computational Materials. 2022. link Times cited: 3 I. Toda-Caraballo, J. Wróbel, and D. Nguyen-Manh, “Generalized universal equation of states for magnetic materials: A novel formulation for an interatomic potential in Fe,” Physical Review Materials. 2022. link Times cited: 0 C. C. Sluss, J. Pittman, D. Nicholson, and D. Keffer, “Exploration of Entropy Pair Functional Theory,” Entropy. 2022. link Times cited: 1 Abstract: Evaluation of the entropy from molecular dynamics (MD) simul… read more Abstract: Evaluation of the entropy from molecular dynamics (MD) simulation remains an outstanding challenge. The standard approach requires thermodynamic integration across a series of simulations. Recent work Nicholson et al. demonstrated the ability to construct a functional that returns excess entropy, based on the pair correlation function (PCF); it was capable of providing, with acceptable accuracy, the absolute excess entropy of iron simulated with a pair potential in both fluid and crystalline states. In this work, the general applicability of the Entropy Pair Functional Theory (EPFT) approach is explored by applying it to three many-body interaction potentials. These potentials are state of the art for large scale models for the three materials in this study: Fe modelled with a modified embedded atom method (MEAM) potential, Cu modelled with an MEAM and Si modelled with a Tersoff potential. We demonstrate the robust nature of EPFT in determining excess entropy for diverse systems with many-body interactions. These are steps toward a universal Entropy Pair Functional, EPF, that can be applied with confidence to determine the entropy associated with sophisticated optimized potentials and first principles simulations of liquids, crystals, engineered structures, and defects. read less Y. Xu, G. Wang, P. Qian, and Y. Su, “Element segregation and thermal stability of Ni–Rh nanoparticles,” Journal of Solid State Chemistry. 2022. link Times cited: 6 S. A. Etesami, M. Laradji, and E. Asadi, “The influence of Pb content on the interfacial free energy of solid Sn in eutectic Pb–Sn liquid mixtures using molecular dynamics simulations,” Molecular Simulation. 2022. link Times cited: 2 Abstract: ABSTRACT The solid–liquid interfacial free energy (γ) for bi… read more Abstract: ABSTRACT The solid–liquid interfacial free energy (γ) for binary Pb–Sn systems at different concentrations and crystal orientations is calculated using molecular dynamics (MD) simulation that employs a modified-embedded atom method interatomic potential. First, the solid–liquid interface is constructed in MD simulations according to its calculated phase diagram. Then, the capillary fluctuation method (CFM) is employed for the calculation of the solid–liquid interfacial stiffness. A novel systematic approach is proposed that eliminates the error in the linear approximation of the CFM. The results show that orientation of the solid Sn crystal does not have a significant influence on the value of the stiffness, which explains the experimentally observed spherical shape of Sn particles in eutectic liquid Pb–Sn mixtures. The calculated γ for pure Sn is in good agreement with experimental counterparts. In addition, this study finds that γ slightly increases with increasing the concentration of Pb in the eutectic liquid Pb–Sn mixture, which agrees with available experimental data. read less F. Gao, Q. Peng, and D. Huang, “Abnormal radiation resistance via direct-amorphization-induced defect recovery in HgTe,” Applied Physics Letters. 2022. link Times cited: 0 Z. Yan, B. Xu, J. Li, and L. Kong, “Defect-mediated crystal growth from deeply undercooled melts,” Computational Materials Science. 2022. link Times cited: 2 I. Balyakin and A. A. Rempel, “Atomistic Calculation of the Melting Point of the High-Entropy Cantor Alloy CoCrFeMnNi,” Doklady Physical Chemistry. 2022. link Times cited: 1 G. Skarbalius et al., “Molecular Dynamics Study on Water Flow Behaviour inside Planar Nanochannel Using Different Temperature Control Strategies,” Energies. 2021. link Times cited: 1 Abstract: In the present paper, molecular dynamics simulations were pe… read more Abstract: In the present paper, molecular dynamics simulations were performed to study the influence of two temperature control strategies on water flow behaviour inside planar nanochannel. In the simulations, the flow was induced by the force acting on each water molecule in the channel. Two temperature control strategies were considered: (a) frozen wall simulations, in which the dynamics of confining wall atoms was not solved and the thermostat was applied to the water, and (b) dynamic wall simulations, in which the dynamics of confining wall atoms was solved, and the thermostat was applied to walls while water was simulated in the microcanonical ensemble. The simulation results show that the considered temperature control strategies has no effect on the shape of the water flow profile, and flow behaviour in the channel is well described by the Navier–Stokes equation solution with added slip velocity. Meanwhile, the slip velocity occurring at the boundaries of the channel is linearly dependent on the magnitude of the flow inducing force in both frozen wall and dynamic wall simulations. However, the slip velocity is considerably greater in simulations when the wall dynamics are solved in contrast to the frozen wall simulations. read less S. Paul, M. Muralles, D. Schwen, M. Short, and K. Momeni, “A Modified Embedded-Atom Potential for Fe-Cr-Si Alloys,” The Journal of Physical Chemistry C. 2021. link Times cited: 5 Y. Zhou, G. Luo, Y. Hu, D. Wu, and Z. Yao, “Interaction properties between molten metal and quartz by molecular dynamics simulation,” Journal of Molecular Liquids. 2021. link Times cited: 2 Y. Shin, Y. Gao, D. Shin, and A. Duin, “Impact of three-body interactions in a ReaxFF force field for Ni and Cr transition metals and their alloys on the prediction of thermal and mechanical properties,” Computational Materials Science. 2021. link Times cited: 8 S. Shuang et al., “Effects of high entropy and twin boundary on the nanoindentation of CoCrNiFeMn high-entropy alloy: A molecular dynamics study,” Computational Materials Science. 2021. link Times cited: 29 C. Canbay and S. Kazanç, “Fe Elementinin Kristal ve Camsı Faza Dönüşümünün Hidrostatik Basınç Altında İncelenmesi: Moleküler Dinamik Benzetim Çalışması.” 2021. link Times cited: 0 S. Starikov et al., “Angular-dependent interatomic potential for large-scale atomistic simulation of iron: Development and comprehensive comparison with existing interatomic models,” Physical Review Materials. 2021. link Times cited: 16 Abstract: The development of classical interatomic potential for iron … read more Abstract: The development of classical interatomic potential for iron is a quite demanding task with a long history background. A new interatomic potential for simulation of iron was created with a focus on description of crystal defects properties. In contrast with previous studies, here the potential development was based on force-matching method that requires only ab initio data as reference values. To verify our model, we studied various features of body-centered-cubic iron including the properties of point defects (vacancy and self-interstitial atom), the Peierls energy barrier for dislocations (screw and mix types), and the formation energies of planar defects (surfaces, grain boundaries, and stacking fault). The verification also implies thorough comparison of a potential with 11 other interatomic potentials reported in literature. This potential correctly reproduces the largest number of iron characteristics which ensures its advantage and wider applicability range compared to the other considered classical potentials. Here application of the model is illustrated by estimation of self-diffusion coefficients and the calculation of fcc lattice properties at high temperature. read less F. Iesari, H. Setoyama, and T. Okajima, “Extracting Local Symmetry of Mono-Atomic Systems from Extended X-ray Absorption Fine Structure Using Deep Neural Networks,” Symmetry. 2021. link Times cited: 1 Abstract: In recent years, neural networks have become a new method fo… read more Abstract: In recent years, neural networks have become a new method for the analysis of extended X-ray absorption fine structure data. Due to its sensitivity to local structure, X-ray absorption spectroscopy is often used to study disordered systems and one of its more interesting property is the sensitivity not only to pair distribution function, but also to three-body distribution, which contains information on the local symmetry. In this study, by considering the case of Ni, we show that by using neural networks, it is possible to obtain not only the radial distribution function, but also the bond angle distribution between the first nearest-neighbors. Additionally, by adding appropriate configurations in the dataset used for training, we show that the neural network is able to analyze also data from disordered phases (liquid and undercooled state), detecting small changes in the local ordering compatible with results obtained through other methods. read less S. Kumar, M.-W. Liu, K.-A. Wu, and M. Gururajan, “Anisotropy in interface stress at the bcc-iron solid–melt interface: Molecular dynamics and phase field crystal modelling,” Computational Materials Science. 2021. link Times cited: 2 M. O’Masta, C. CloughEric, and J. H. Martin, “Island formation and the heterogeneous nucleation of aluminum,” Computational Materials Science. 2021. link Times cited: 4 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 Y. Lysogorskiy et al., “Performant implementation of the atomic cluster expansion (PACE) and application to copper and silicon,” npj Computational Materials. 2021. link Times cited: 84 A. Agrawal and R. Mirzaeifar, “Copper-graphene composites; developing the MEAM potential and investigating their mechanical properties,” Computational Materials Science. 2021. link Times cited: 9 R. Wu, X. Zhao, and Y. Liu, “Atomic Insights of Cu Nanoparticles Melting and Sintering Behavior in Cu — Cu Direct Bonding,” Energy Engineering (Energy) eJournal. 2020. link Times cited: 27 S. A. Etesami, M. Laradji, and E. Asadi, “Reliability of molecular dynamics interatomic potentials for modeling of titanium in additive manufacturing processes,” Computational Materials Science. 2020. link Times cited: 5 R. Meyer et al., “Vibrational and magnetic signatures of extended defects in Fe,” The European Physical Journal B. 2020. link Times cited: 5 K. Li et al., “Determination of the accuracy and reliability of molecular dynamics simulations in estimating the melting point of iron: Roles of interaction potentials and initial system configurations,” Journal of Molecular Liquids. 2019. link Times cited: 8 M. Hazarika and S. N. Chakraborty, “Study of structural stability of copper crystal with voids from molecular dynamics simulations,” Chemical Physics Letters. 2019. link Times cited: 3 S. Zhevnenko, “Ordering of cobalt surface particles by moving grain boundaries in copper,” Applied Surface Science. 2019. link Times cited: 1 S. A. Etesami, M. Baskes, M. Laradji, and E. Asadi, “Thermodynamics of solid Sn and Pb Sn liquid mixtures using molecular dynamics simulations,” Acta Materialia. 2018. link Times cited: 21 A. Nourian-Avval and E. Asadi, “Thermodynamics of FCC metals at melting point in one-mode phase-field crystals model,” Computational Materials Science. 2018. link Times cited: 7 M. Melnykov and R. Davidchack, “Characterization of melting properties of several Fe-C model potentials,” Computational Materials Science. 2018. link Times cited: 8 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 S. Y. Korostelev, E. E. Slyadnikov, and I. Turchanovsky, “The resistance of amorphous metals to thermal effects. Molecular dynamics modeling,” PHYSICAL MESOMECHANICS OF CONDENSED MATTER: Physical Principles of Multiscale Structure Formation and the Mechanisms of Nonlinear Behavior: MESO2022. 2023. link Times cited: 0 Z. Yan, H. Sheng, E. Ma, B. Xu, J. Li, and L. Kong, “Intermediate structural evolution preceding growing BCC crystal interface in deeply undercooled monatomic metallic liquids,” Acta Materialia. 2021. link Times cited: 6 C. Lapointe, T. Swinburne, L. Proville, C. Becquart, N. Mousseau, and M. Marinica, “Machine learning surrogate models for strain-dependent vibrational properties and migration rates of point defects,” Physical Review Materials. 2022. link Times cited: 2 Abstract: ,… read more Abstract: , read less K. Jurkiewicz, M. Kamiński, A. Bródka, and A. Burian, “Atomistic origin of nano-silver paracrystalline structure: molecular dynamics and x-ray diffraction studies,” Journal of Physics: Condensed Matter. 2022. link Times cited: 0 Abstract: Classical molecular dynamics (MD) and x-ray diffraction (XRD… read more Abstract: Classical molecular dynamics (MD) and x-ray diffraction (XRD) have been used to establish the origin of the paracrystalline structure of silver nanoparticles at the atomic scale. Models based on the face-centred cubic structure have been computer generated and their atomic arrangements have been optimized by the MD with the embedded-atom model (EAM) potential and its modified version (MEAM). The simulation results are compared with the experimental XRD data in reciprocal and real spaces, i.e. the structure factor and the pair distribution function. The applied approach returns the structural models, defined by the Cartesian coordinates of the constituent atoms. It has been found that most of the structural features of Ag nanoparticles are better reproduced by the MEAM. The presence of vacancy defects in the structure of the Ag nanoparticles has been considered and the average concentration of vacancies is estimated to be 3 at.%. The average nearest-neighbour Ag–Ag distances and the coordination numbers are determined and compared with the values predicted for the bulk Ag, demonstrating a different degree of structural disorder on the surface and in the core, compared to the bulk crystalline counterpart. It has been shown that the paracrystalline structure of the Ag nanoparticles has origin in the surface disorder and the disorder generated by the presence of the vacancy defects. Both sources lead to network distortion that propagates proportionally to the square root of the interatomic distances. read less S. Kazanç and C. Canbay, “Cu’nun Mekanik Özelliklerine Tek Eksenli Germe Zorlanmasının Etkisi: Moleküler Dinamik Yöntemi,” Fırat Üniversitesi Mühendislik Bilimleri Dergisi. 2021. link Times cited: 0 S. Kazanç and C. Canbay, “Fe elementindeki αγδ Katı-Katı Faz Geçişlerinin Moleküler Dinamik Benzetimi ile İncelenmesi,” Fırat Üniversitesi Mühendislik Bilimleri Dergisi. 2021. link Times cited: 0 Abstract: When the phase diagram of the element Fe is examined, it is … read more Abstract: When the phase diagram of the element Fe is examined, it is seen that it has different crystal structures at different temperatures below its melting temperature. In this study, the solid-solid phase transformations occurring at different temperatures in the Fe model system consisting of 4000 atoms were investigated using molecular dynamic simulation method. The Embedded Atom Method(EAM), which includes many body interactions, was used to calculate interactions between atoms. For the element Fe, the α, γ and δ phases formed below the melting temperature and the transformation temperatures for these phases were determined and the results were compared with the experimental values. Radial distribution function, changes in thermodynamic quantities and Ackland-Jones analysis method were used in the structural analysis of the model system. read less H. Zou, Y. Feng, L. Qiu, and X. Zhang, “Effect of the loading amount and arrangement of iodine chains on the interfacial thermal transport of carbon nanotubes: a molecular dynamics study,” RSC Advances. 2020. link Times cited: 7 Abstract: Due to their excellent electrical and thermal conductivity p… read more Abstract: Due to their excellent electrical and thermal conductivity properties, the nano-scale characteristics of carbon nanotubes (CNTs) are expected to be suitable for very large-scale integrated circuits and for next-generation micro interconnected devices. Consequently, CNT–metal composite materials have been widely researched, and have shown excellent performance in terms of thermal conductivity, electrical conductivity, thermal expansion, and adaptability to microelectronic devices. However, there are few studies on halogen–CNT composite materials with characteristics similar to CNT–metal composites, including regarding the remarkable electrical compatibility of the halogen and CNT and the large number of low-frequency phonons that are beneficial for thermal transport. In this work, iodine chains were considered to explore the halogen effect on CNTs. Variation of the interfacial thermal conductance of CNTs as a function of the iodine chains loading amount and arrangement was explored by a molecular dynamics method. The heat transfer mechanism was further analyzed based on the phonon state difference. This research is expected to provide a new pathway for the application of CNT composite materials in the field of next-generation microelectronics. read less L. Morrissey and S. Nakhla, “Considerations when calculating the mechanical properties of single crystals and bulk polycrystals from molecular dynamics simulations,” Molecular Simulation. 2020. link Times cited: 4 Abstract: ABSTRACT The choice of a proper interatomic potential is cri… read more Abstract: ABSTRACT The choice of a proper interatomic potential is critical to obtaining accurate and realistic molecular dynamics results. However, previous studies that have tested the suitability of a potential to predict mechanical properties often do so using elastic constants from a triaxial stress state that ignores Poisson’s effect. While this method is suitable it is not consistent with macroscale experimental methods and cannot provide the complete loading behaviour. Further, there is a lack of knowledge as to whether accuracy in predicting elastic constants from a fixed volume condition indicates accuracy for elastic moduli from uniaxial tensile simulations. Moreover, those studies that did account for Poisson’s effect studied only one crystal orientation and thus assumed potential accuracy is independent of crystal orientation. Results from the current study demonstrated that accuracy of a potential is dependent on the crystal direction. Further, the most accurate potentials for elastic constants calculated using a fixed volume condition were not necessarily the most accurate at predicting elastic moduli from a physically realisable tension test. Finally, the Voigt Reuss Hill (VRH) method was shown to accurately predict polycrystalline mechanical properties from single crystal data as a function of temperature. read less W. Jiang, Y. Zhang, L. Zhang, and H. Wang, “Accurate Deep Potential model for the Al–Cu–Mg alloy in the full concentration space,” arXiv: Materials Science. 2020. link Times cited: 24 Abstract: Combining first-principles accuracy and empirical-potential … read more Abstract: Combining first-principles accuracy and empirical-potential efficiency for the description of the potential energy surface (PES) is the philosopher's stone for unraveling the nature of matter via atomistic simulation. This has been particularly challenging for multi-component alloy systems due to the complex and non-linear nature of the associated PES. In this work, we develop an accurate PES model for the Al-Cu-Mg system by employing Deep Potential (DP), a neural network based representation of the PES, and DP Generator (DP-GEN), a concurrent-learning scheme that generates a compact set of ab initio data for training. The resulting DP model gives predictions consistent with first-principles calculations for various binary and ternary systems on their fundamental energetic and mechanical properties, including formation energy, equilibrium volume, equation of state, interstitial energy, vacancy and surface formation energy, as well as elastic moduli. Extensive benchmark shows that the DP model is ready and will be useful for atomistic modeling of the Al-Cu-Mg system within the full range of concentration. read less C. Lapointe et al., “Machine learning surrogate models for prediction of point defect vibrational entropy,” Physical Review Materials. 2020. link Times cited: 5 Abstract: The temperature variation of the defect densities in a cryst… read more Abstract: The temperature variation of the defect densities in a crystal depends on vibrational entropy. This contribution to the system thermodynamics remains computationally challenging as it requires a diagonalization of the system's Hessian which scales as $O({N}^{3})$ for a crystal made of $N$ atoms. Here, to circumvent such a heavy computational task and make it feasible even for systems containing millions of atoms, the harmonic vibrational entropy of point defects is estimated directly from the relaxed atomic positions through a linear-in-descriptor machine learning approach of order $O(N)$. With a size-independent descriptor dimension and fixed model parameters, an excellent predictive power is demonstrated on a wide range of defect configurations, supercell sizes, and external deformations well outside the training database. In particular, formation entropies in a range of $250{k}_{B}$ are predicted with less than $1.6{k}_{B}$ error from a training database whose formation entropies span only $25{k}_{B}$ (training error less than $1.0{k}_{B}$). This exceptional transferability is found to hold even when the training is limited to a low-energy superbasin in the phase space while the tests are performed for a different liquid-like superbasin at higher energies. read less J. Zhang, J. Cui, Z. Yang, and S. Shen, “Thermodynamic properties and thermoelastic constitutive relation for cubic crystal structures based on improved free energy,” Computational Mechanics. 2020. link Times cited: 1 J.-H. Fu, C. Zhang, T. Liu, and J. Liu, “Room temperature liquid metal: its melting point, dominating mechanism and applications,” Frontiers in Energy. 2020. link Times cited: 27 J.-H. Fu, C. Zhang, T. Liu, and J. Liu, “Room temperature liquid metal: its melting point, dominating mechanism and applications,” Frontiers in Energy. 2019. link Times cited: 0 J. Zhang, J. Cui, Z. Yang, and S. Shen, “Thermodynamic properties and thermoelastic constitutive relation for cubic crystal structures based on improved free energy,” Computational Mechanics. 2019. link Times cited: 0 S. Kavousi, B. R. Novak, M. Baskes, M. A. Zaeem, and D. Moldovan, “Modified embedded-atom method potential for high-temperature crystal-melt properties of Ti–Ni alloys and its application to phase field simulation of solidification,” Modelling and Simulation in Materials Science and Engineering. 2019. link Times cited: 21 Abstract: We developed new interatomic potentials, based on the second… read more Abstract: We developed new interatomic potentials, based on the second nearest-neighbor modified embedded-atom method (2NN-MEAM) formalism, for Ti, Ni, and the binary Ti–Ni system. These potentials were fit to melting points, latent heats, the binary phase diagrams for the Ti rich and Ni rich regions, and the liquid phase enthalpy of mixing for binary alloys, therefore they are particularly suited for calculations of crystal-melt (CM) interface thermodynamic and transport properties. The accuracy of the potentials for pure Ti and pure Ni were tested against both 0 K and high temperature properties by comparing various properties obtained from experiments or density functional theory calculations including structural properties, elastic constants, point-defect properties, surface energies, temperatures and enthalpies of phase transformations, and diffusivity and viscosity in the liquid phase. The fitted binary potential for Ti–Ni was also tested against various non-fitted properties at 0 K and high temperatures including lattice parameters, formation energies of different intermetallic compounds, and the temperature dependence of liquid density at various concentrations. The CM interfacial free energies obtained from simulations, based on the newly developed Ti–Ni potential, show that the bcc alloys tend to have smaller anisotropy compared with fcc alloys which is consistent with the finding from the previous studies comparing single component bcc and fcc materials. Moreover, the interfacial free energy and its anisotropy for Ti-2 atom% Ni were also used to parameterize a 2D phase field (PF) model utilized in solidification simulations. The PF simulation predictions of microstructure development during solidification are in good agreement with a geometric model for dendrite primary arm spacing. read less S. M. Handrigan, L. Morrissey, and S. Nakhla, “Investigating various many-body force fields for their ability to predict reduction in elastic modulus due to vacancies using molecular dynamics simulations,” Molecular Simulation. 2019. link Times cited: 6 Abstract: ABSTRACT Molecular dynamics simulations are more frequently … read more Abstract: ABSTRACT Molecular dynamics simulations are more frequently being utilised to predict macroscale mechanical properties as a result of atomistic defects. However, the interatomic force field can significantly affect the resulting mechanical properties. While several studies exist which demonstrate the ability of various force fields to predict mechanical properties, the investigation into which is most accurate for the investigation of vacancies is limited. To obtain meaningful predictions of mechanical properties, a clear understanding of force field parameterisation is required. As such, the current study evaluates various many-body force fields to demonstrate the reduction in mechanical properties of iron and iron–chromium due to the presence of vacancies while undergoing room temperature atomistic uniaxial tension. Reduction was normalised in each case with the zero-vacancy elastic modulus, removing the need to predict an accurate nominal elastic modulus. Comparisons were made to experimental data and an empirical model from literature. It was demonstrated that accurate fitting to vacancy formation and migration energy allowed for accurate predictions. In addition, bond-order based force fields showed enhanced predictions regardless of fitting procedure. Overall, these findings highlight the need to understand capabilities and limitations of available force fields, as well as the need for enhanced parameterisation of force fields. read less L. Morrissey, S. M. Handrigan, S. Subedi, and S. Nakhla, “Atomistic uniaxial tension tests: investigating various many-body potentials for their ability to produce accurate stress strain curves using molecular dynamics simulations,” Molecular Simulation. 2019. link Times cited: 13 Abstract: ABSTRACT Molecular dynamics simulations, which take place on… read more Abstract: ABSTRACT Molecular dynamics simulations, which take place on the atomistic scale, are now being used to predict the influence of atomistic processes on macro-scale mechanical properties. However, there is a lack of clear understanding on which potential should be used when attempting to obtain these properties. Moreover, many MD studies that do test mechanical properties do not actually simulate the macro-scale laboratory tension tests used to obtain them. As such, the purpose of the current study was to evaluate the various types of potentials for their accuracy in predicting the mechanical properties of iron from an atomistic uniaxial tension test at room temperature. Results demonstrated that while EAM and MEAM potentials all under predicted the elastic modulus at room temperature, the Tersoff and ReaxFF potentials were significantly more accurate. Unlike EAM and MEAM, both the Tersoff and ReaxFF potentials are bond order based. Therefore, these results demonstrate the importance of considering bonding between atoms when modelling tensile tests. In addition, the ReaxFF potential also accurately predicted the Poisson's ratio, allowing for complete characterisation of the material's behaviour. Overall, these findings highlight the need to understand the capabilities and limitations of each potential before application to a problem outside of the initial intended use. read less S. A. Etesami, M. Laradji, and E. Asadi, “Transferability of interatomic potentials in predicting the temperature dependency of elastic constants for titanium, zirconium and magnesium,” Modelling and Simulation in Materials Science and Engineering*. 2019. link Times cited: 4 Abstract: We present our investigation of the current state of the art… read more Abstract: We present our investigation of the current state of the art for the transferability of molecular dynamics (MD) interatomic potentials for high temperature simulations of material processes in terms of elastic constants. With the current advancement of computer power, nanoscale computational models such as MD have the potential to accelerate optimization and development of high temperature material processes provided a robust and transferable interatomic potential. Temperature dependency of elastic constants, despite the low temperature elastic constants, is not commonly used as one of the target material properties to develop interatomic potentials for metals; thus, it is a reliable index to determine the transferability of interatomic potentials for high temperature simulations. We consider all five independent elastic constants and their temperature dependency as an index for our evaluations of available interatomic potentials for titanium (Ti), zirconium (Zr), and magnesium (Mg) as representative metals with a relatively complex crystal structure (hcp). The calculated elastic constants and their deviation from their corresponding experimental values are presented. We provide a through discussion on the transferability of each potential and summarize with the most suitable potentials for high temperature material process simulations for each considered material. read less
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_549900287421_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_EtesamiAsadi_2018_Fe__MO_549900287421_002
DOI	10.25950/88bf887e https://doi.org/10.25950/88bf887e https://commons.datacite.org/doi.org/10.25950/88bf887e
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_EtesamiAsadi_2018_Fe__MO_549900287421_001

Verification Check Dashboard

(Click here to learn more about Verification Checks)

Grade	Name	Category	Brief Description	Full Results	Aux File(s)
P All elements claimed by model are supported in at least one of the tested configurations.	vc-species-supported-as-stated	mandatory	The model supports all species it claims to support; see full description.	Results	Files
P Periodic boundary conditions were correctly supported for all configurations that the model was able to compute.	vc-periodicity-support	mandatory	Periodic boundary conditions are handled correctly; see full description.	Results	Files
P Model energy has permutation symmetry for all configurations the model was able to compute.	vc-permutation-symmetry	mandatory	Total energy and forces are unchanged when swapping atoms of the same species; see full description.	Results	Files
B The letter grade B was assigned because the normalized error in the computation was 7.83908e-09 compared with a machine precision of 2.22045e-16. The letter grade was based on 'score=log10(error/eps)', with ranges A=[0, 7.5], B=(7.5, 10.0], C=(10.0, 12.5], D=(12.5, 15.0), F>15.0. 'A' is the best grade, and 'F' indicates failure.	vc-forces-numerical-derivative	consistency	Forces computed by the model agree with numerical derivatives of the energy; see full description.	Results	Files
F The model is C^0 continuous. This means that the model has continuous energy, but a discontinuous first derivative.	vc-dimer-continuity-c1	informational	The energy versus separation relation of a pair of atoms is C1 continuous (i.e. the function and its first derivative are continuous); see full description.	Results	Files
P Model energy and forces are invariant with respect to rigid-body motion (translation and rotation) for all configurations the model was able to compute.	vc-objectivity	informational	Total energy is unchanged and forces transform correctly under rigid-body translation and rotation; see full description.	Results	Files
P Model energy has inversion symmetry for all configurations the model was able to compute.	vc-inversion-symmetry	informational	Total energy is unchanged and forces change sign when inverting a configuration through the origin; see full description.	Results	Files
P No memory leak detected.	vc-memory-leak	informational	The model code does not have memory leaks (i.e. it releases all allocated memory at the end); see full description.	Results	Files
P All threads give identical results for tested case. Model appears to be thread-safe.	vc-thread-safe	mandatory	The model returns the same energy and forces when computed in serial and when using parallel threads for a set of configurations. Note that this is not a guarantee of thread safety; see full description.	Results	Files
P Unit conversion successful	vc-unit-conversion	mandatory	The model is able to correctly convert its energy and/or forces to different unit sets; see full description.	Results	Files

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

Species: Fe

Cohesive Energy Graph

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

Species: Fe

Diamond Lattice Constant

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

Species: Fe

Dislocation Core Energies

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

(No matching species)

FCC Elastic Constants

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

Species: Fe

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: Fe

FCC Stacking Fault Energies

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

(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: Fe

Cubic Crystal Basic Properties Table

Species: Fe

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 Fe v004	view	4712
Cohesive energy versus lattice constant curve for diamond Fe v004	view	4734
Cohesive energy versus lattice constant curve for fcc Fe v004	view	4655
Cohesive energy versus lattice constant curve for sc Fe v004	view	4147

ElasticConstantsCubic__TD_011862047401_006

Elastic constants for cubic crystals at zero temperature and pressure v006

Creators: Junhao Li and Ellad Tadmor
Contributor: tadmor
Publication Year: 2019
DOI: https://doi.org/10.25950/5853fb8f

Computes the cubic elastic constants for some common crystal types (fcc, bcc, sc, diamond) by calculating the hessian of the energy density with respect to strain. An estimate of the error associated with the numerical differentiation performed is reported.

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Elastic constants for bcc Fe at zero temperature v006	view	17445
Elastic constants for diamond Fe at zero temperature v001	view	56414
Elastic constants for fcc Fe at zero temperature v006	view	16908
Elastic constants for sc Fe at zero temperature v006	view	17177

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 Fe in AFLOW crystal prototype A_cF4_225_a v002	view	149597
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_cI2_229_a v002	view	61368
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_hP2_194_c v002	view	51646
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_tP28_136_f2ij v002	view	60152

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 110 symmetric tilt grain boundary in bcc Fe v001	view	27941357
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in bcc Fe v001	view	16534479
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in bcc Fe v001	view	62074170
Relaxed energy as a function of tilt angle for a 100 symmetric tilt grain boundary in fcc Fe v001	view	19529419

LatticeConstantCubicEnergy__TD_475411767977_007

Equilibrium lattice constant and cohesive energy of a cubic lattice at zero temperature and pressure v007

Creators: Daniel S. Karls and Junhao Li
Contributor: karls
Publication Year: 2019
DOI: https://doi.org/10.25950/2765e3bf

Equilibrium lattice constant and cohesive energy of a cubic lattice at zero temperature and pressure.

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Equilibrium zero-temperature lattice constant for bcc Fe v007	view	18332
Equilibrium zero-temperature lattice constant for diamond Fe v007	view	6111
Equilibrium zero-temperature lattice constant for fcc Fe v007	view	10055
Equilibrium zero-temperature lattice constant for sc Fe v007	view	9939

LatticeConstantHexagonalEnergy__TD_942334626465_005

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

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

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Equilibrium lattice constants for hcp Fe v005		view	71117

LinearThermalExpansionCoeffCubic__TD_522633393614_002

Linear thermal expansion coefficient of cubic crystal structures v002

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

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Linear thermal expansion coefficient of bcc Fe at 293.15 K under a pressure of 0 MPa v002		view	1617370

SurfaceEnergyCubicCrystalBrokenBondFit__TD_955413365818_004

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

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

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

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

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

In Python, these two fits take the following form:

def BrokenBondFCC(params, index):

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

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

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

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

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Broken-bond fit of high-symmetry surface energies in bcc Fe v004		view	72357

VacancyFormationEnergyRelaxationVolume__TD_647413317626_001

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

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

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Monovacancy formation energy and relaxation volume for bcc Fe		view	441208

VacancyFormationMigration__TD_554849987965_001

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

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

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Vacancy formation and migration energy for bcc Fe		view	5158883

Errors

ElasticConstantsHexagonal__TD_612503193866_004

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

EquilibriumCrystalStructure__TD_457028483760_002

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

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 bcc Fe v001	other	view
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Fe v001	other	view
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Fe v001	other	view
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Fe v001	other	view

SurfaceEnergyCubicCrystalBrokenBondFit__TD_955413365818_004

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

Files

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

Download

MEAM_LAMMPS_EtesamiAsadi_2018_Fe__MO_549900287421_002.txz	Tar+XZ	Linux and OS X archive
MEAM_LAMMPS_EtesamiAsadi_2018_Fe__MO_549900287421_002.zip	Zip	Windows archive

Download Dependency

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

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

Wiki

Wiki is ready to accept new content.

MEAM_LAMMPS_EtesamiAsadi_2018_Fe__MO_549900287421_002

Verification Check Dashboard

Visualizers (in-page)

BCC Lattice Constant

Cohesive Energy Graph

Diamond Lattice Constant

Dislocation Core Energies

FCC Elastic Constants

FCC Lattice Constant

FCC Stacking Fault Energies

FCC Surface Energies

SC Lattice Constant

Cubic Crystal Basic Properties Table

Tests

Errors

Files

Download

Download Dependency

Wiki