MEAM Potential for the Fe-Mn system developed by Kim, Shin, Lee (2009) v002

Young-Min Kim; Young-Han Shin; Byeong-Joo Lee

doi:10.25950/a9c5adcc

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MEAM_LAMMPS_KimShinLee_2009_FeMn__MO_058735400462_002

Interatomic potential for Iron (Fe), Manganese (Mn).
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Title A single sentence description.	MEAM Potential for the Fe-Mn system developed by Kim, Shin, Lee (2009) 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.	Modified embedded-atom method (MEAM) interatomic potentials for pure Mn and the Fe–Mn binary system have been developed using a previously developed MEAM potential for Fe. In the original paper (Kim et al., Acta Materialia, 57(2), 2009) the potentials can describe various fundamental physical properties of pure Mn (cohesive energy, structural energy differences, lattice parameters, elastic constants, vacancy formation energy, surface energy, etc.) and alloy behaviors (enthalpy of mixing in face-centered cubic and liquid phases, composition dependency of lattice parameters in various solid solutions) in reasonable agreement with experimental information or other empirical approaches.
Species The supported atomic species.	Fe, Mn
Disclaimer A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.	None
Content Origin	http://cmse.postech.ac.kr/home_2nnmeam

Contributor	Joonho Ji
Maintainer	Joonho Ji
Developer	Young-Min Kim Young-Han Shin Byeong-Joo Lee
Published on KIM	2023
How to Cite	This Model originally published in [1] is archived in OpenKIM [2-5]. [1] Kim Y-M, Shin Y-H, Lee B-J. Modified embedded-atom method interatomic potentials for pure Mn and the Fe–Mn system. Acta Materialia. 2009;57(2):474–82. doi:10.1016/j.actamat.2008.09.031 — (Primary Source) A primary source is a reference directly related to the item documenting its development, as opposed to other sources that are provided as background information. [2] Kim Y-M, Shin Y-H, Lee B-J. MEAM Potential for the Fe-Mn system developed by Kim, Shin, Lee (2009) v002. OpenKIM; 2023. doi:10.25950/a9c5adcc [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. 61 Citations (40 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 M.-G. Jo, Y. Koo, and S. Kwon, “Determination of the deformation mechanism of Fe-Mn alloys,” Metals and Materials International. 2015. link Times cited: 14 F. Ulomek and V. Mohles, “Molecular dynamics simulations of grain boundary mobility in Al, Cu and γ-Fe using a symmetrical driving force,” Modelling and Simulation in Materials Science and Engineering. 2014. link Times cited: 13 Abstract: We present a new artificial driving force for the determinat… read more Abstract: We present a new artificial driving force for the determination of grain boundary mobility by molecular dynamics. The new driving force is a symmetric version of the synthetic driving force formerly introduced by Janssens et al 2006 Nature Mater. 5 124–7. The new version depends on two orientation parameters instead of one. We analyze the advantages and disadvantages of these two driving force methods. Grain boundary mobilities are simulated for eight symmetric CSL tilt grain boundaries in Al, Cu and γ-Fe, and two MD potentials for each of these materials. Boundary conditions are kept as similar as possible to show the influence of the different materials and to compare to the influence of the different MD potential types on simulated GB mobilities. We find that the newly introduced artificial driving force is a slight improvement, but it cannot remove the shortcomings of the original approach. Also, it is found that the differences in calculated MD mobilities between different materials are of the same order as those between different MD potentials of any one element. Sources for such differences are identified and classified by severity. read less D. Zeng, K. Chung, and S. Bae, “Thermomigration-induced magnetic degradation of current perpendicular to the plane giant magnetoresistance spin-valve read sensors operating at high current density,” Journal of Applied Physics. 2009. link Times cited: 4 Abstract: The theoretically analyzed physical mechanism of thermomigra… read more Abstract: The theoretically analyzed physical mechanism of thermomigration (TM)-induced magnetic degradation that occurred in the current perpendicular to the plane (CPP) Ir20Mn80 exchange biased giant magnetoresistance spin-valve (EBGMR SV) read sensors is presented. The device size was changed from 60×60 to 140×140 nm2 at the fixed aspect ratio of 1(L):1(W), and the operating current density was varied from J=1×108 A/cm2 to J=5×108 A/cm2 in a current control mode. It was numerically confirmed that the Mn atomic interdiffusion through the Ir20Mn80/Co80Fe20 interface due to the thermally induced mass transport and the “Villari magnetic reversal” of the CoFe pinned layer due to the thermally induced stress are mainly responsible for the serious degradation of exchange bias and magnetoresistance. Furthermore, the TM-induced magnetic degradation of CPP EBGMR SV read sensors was found to become severe by increasing the operating current density. However, interestingly, this undesirable magnetic degradation was dramatic... read less H.-S. Jang and B. Lee, “A Modified Embedded-Atom Method Interatomic Potential for the Mg–Mn Binary System,” MATERIALS TRANSACTIONS. 2022. link Times cited: 0 A. K. Pandey, C. K. Dixit, and S. Srivastava, “Theoretical model for the prediction of lattice energy of diatomic metal halides,” Journal of Mathematical Chemistry. 2023. link Times cited: 2 A. Jacob, E. Povoden-Karadeniz, P. Retzl, and E. Kozeschnik, “Reassessment of low-temperature Gibbs energies of BCC and FCC in steel for T0-temperature evaluation,” Calphad. 2023. link Times cited: 2 K. Wang et al., “Multiscale Analysis of Wheel-Rail Rolling Contact Wear and Damage Mechanisms using Molecular Dynamics and Explicit Finite Elements,” Tribology International. 2023. link Times cited: 2 J. Ji and B.-J. Lee, “Analyzing the effect of Li/Ni intermixing on Ni-rich layered cathode structures using atomistic simulation of the Li–Ni–Mn–Co–O quinary system,” Journal of Power Sources. 2023. link Times cited: 1 W. Liu, T. Han, L. Wang, B. Zhu, J. Jiang, and J. Zhou, “Molecular Dynamics Simulation Study on the Effect of Mn on the Tensile Behavior of a Ferrite/Austenite Iron Bicrystal,” Journal of Materials Engineering and Performance. 2022. link Times cited: 0 Y. Wang, F. Wang, W. Yu, Y.-T. Wang, and Z. Qi, “Effects of MnS inclusions on mechanical behavior and damage mechanism of free-cutting steel: A molecular dynamics study.,” Journal of molecular graphics & modelling. 2022. link Times cited: 2 Y. Jiao, L. C. Xu, W. Dan, Y. Xu, and W.-gang Zhang, “Atomic-scale study of the mechanical properties of dual-phase fcc/bcc crystallites: influences of alloying elements and phase boundaries,” Journal of Materials Science. 2022. link Times cited: 0 Y. Jiao, W. Dan, Y. Xu, and W.-gang Zhang, “Roles of Mn content and nanovoid defects in the plastic deformation mechanism of Fe–Mn twin crystals from molecular dynamics simulations,” Journal of Materials Research. 2022. link Times cited: 1 Abstract: In this study, the roles of alloying element Mn and nanovoid… read more Abstract: In this study, the roles of alloying element Mn and nanovoid defects in the deformation behaviour of Fe–Mn twin crystals are investigated with molecular dynamics (MD) tensile test simulations. The results for the supercells with various Mn contents (5–30 at% Mn) show that Mn addition can reduce the elastic constant and improve the strength of twin crystals. In addition, with increasing Mn content, the plastic deformation mechanism transitions from martensitic transformation to dislocation slip. The mechanical properties of supercells containing 20 at% Mn, i.e. the elastic constant and critical stress of plastic deformation, decrease as the nanovoid diameter increases from 20 to 60 Å. The effect of twin boundaries (TBs) on plastic deformation is analysed in detail, revealing that TBs can effectively block the transmission of dislocations through twins, thereby improving the strength of the material. Representative snapshots of the interactions between dislocations and TBs and the dislocation nucleation mechanism on the TB plane read less Y. Kim and B.-J. Lee, “Second nearest-neighbor modified embedded atom method interatomic potentials for Na-M−Sn (M = Cu, Mn, Ni) ternary systems,” Computational Materials Science. 2022. link Times cited: 2 W. Xue, H. Zhang, Y. Shen, and N. Jia, “Manganese controlled transformation and twinning of the nanoscale austenite in low-carbon-medium-Mn steel,” Materials Science and Engineering: A. 2022. link Times cited: 10 S. Chen, Z. Aitken, V. Sorkin, Z. Yu, Z. Wu, and Y.-W. Zhang, “Modified Embedded‐Atom Method Potentials for the Plasticity and Fracture Behaviors of Unary HCP Metals,” Advanced Theory and Simulations. 2021. link Times cited: 3 Abstract: Modified embedded‐atom method (MEAM) potentials have been wi… read more Abstract: Modified embedded‐atom method (MEAM) potentials have been widely used in molecular dynamics (MD) simulations to describe the interatomic interactions in metallic systems. However, conventional MEAM potentials are almost exclusively fit to a limited number of key single‐value properties, limiting the predictability of MD simulations, especially for complex hexagonal‐close‐packed (HCP) metals with multiple slip systems. Here, three MEAM potentials for unary HCP metals (Mg, Co, and Ti) are fit to conventional target properties, as well as continuous‐energy curves and their gradients obtained from density‐functional theory calculations. These targets include the lattice parameters, cohesive energy, elastic constants, and surface energies as well as the cohesive energy curve, basal plane decohesion energy curve, and generalized stacking fault energy curves for basal, prismatic, pyramidal I, and pyramidal II planes. These interatomic potentials demonstrate excellent reproduction of relevant properties and enable accurate MD simulations of volumetric and plastic deformations, as well as fracture in Mg, Co, and Ti HCP metals. Importantly, the interatomic potentials demonstrate better performance than all existing EAM/MEAM potentials readily available from the literature. read less G. Poletaev and V. Kovalenko, “Development of Potentials for Description of Interatomic Interactions in Hadfield Steel for Molecular Dynamic Simulation,” Himičeskaâ fizika i mezoskopiâ. 2021. link Times cited: 0 Abstract: Summary. Hadfield steel, due to its excellent work hardening… read more Abstract: Summary. Hadfield steel, due to its excellent work hardening ability read less M. Meesa, K. Gupta, and K. R. Mangipudi, “A molecular dynamics study of the influence of nucleation conditions on the phase selection in Fe50Mn30Cr10Co10 high entropy alloy,” Materialia. 2021. link Times cited: 1 W. Choi et al., “Computational design of V-CoCrFeMnNi high-entropy alloys: An atomistic simulation study,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2021. link Times cited: 12 S. Khan, M. Mushtaq, G. Berdiyorov, and N. Tit, “Relevance of metal (Ca versus Mn) embedded C2N for energy-storage applications: Atomic-scale study,” International Journal of Hydrogen Energy. 2020. link Times cited: 7 K. Hsieh, Y.-Y. Lin, C.-H. Lu, J. Yang, P. Liaw, and C.-L. Kuo, “Atomistic simulations of the face-centered-cubic-to-hexagonal-close-packed phase transformation in the equiatomic CoCrFeMnNi high entropy alloy under high compression,” Computational Materials Science. 2020. link Times cited: 21 Abstract: We performed the modified-embedded-atom-method (MEAM) based … read more Abstract: We performed the modified-embedded-atom-method (MEAM) based molecular dynamics (MD) simulations to investigate the plastic deformation and phase transformation behaviors in the CoCrFeMnNi HEA under high compression at room temperature. Our MD simulations revealed that the stress-induced phase transformations in the CoCrFeMnNi HEA are strongly crystal orientation-dependent. The [0 0 1] uniaxial compression can induce the significant face-centered-cubic (fcc) -to-hexagonal-close-packed (hcp) phase transformation via successive emissions of partial dislocations from the extended stacking faults, twin boundaries and hcp-lamellas created during the early stage of deformation. As for the [1 1 0] and [1 1 1] uniaxial compressions, however, the transformed hcp atoms can simply form the intrinsic/extrinsic stacking faults. Although the [0 0 1] uniaxial compression produced a much lower dislocation density than the other two systems, it induced much more constituents transformed into the hcp atoms at the end of phase transformation. Our results clearly indicated that the deformation twin boundaries and extended hcp-lamellas play a critical role in facilitating the stress-induced fcc-to-hcp phase transformation in the CoCrFeMnNi HEA. Furthermore, it was found that the phase transformation in the CoCrFeMnNi HEA can be effectively facilitated by a large deviatoric compressive stress while it may tend to be significantly retarded by a hydrostatic compression. Our results also showed that the plastic deformation behaviors in Ni under high compression are very similar to those occurred in the CoCrFeMnNi HEA though nearly all the hcp atoms can simply constitute the intrinsic/extrinsic stacking faults without the formation of any bulk hcp phase in the fcc lattice. The main discrepancy in the phase transformation behaviors between the Ni and CoCrFeMnNi HEA can be largely attributed to the much lower stacking fault energy of the CoCrFeMnNi HEA than other fcc metals. read less S. Raman, J. Hoyt, P. Saidi, and M. Asta, “Molecular dynamics study of the thermodynamic and kinetic properties of the solid-liquid interface in FeMn,” Computational Materials Science. 2020. link Times cited: 14 K. Sugita, N. Matsuoka, M. Mizuno, and H. Araki, “Vacancy formation enthalpy in CoCrFeMnNi high-entropy alloy,” Scripta Materialia. 2020. link Times cited: 37 I. Aslam et al., “Thermodynamic and kinetic behavior of low-alloy steels: An atomic level study using an Fe-Mn-Si-C modified embedded atom method (MEAM) potential,” Materialia. 2019. link Times cited: 12 Z. Dong, S. Schönecker, D. Chen, W. Li, S. Lu, and L. Vitos, “Influence of Mn content on the intrinsic energy barriers of paramagnetic FeMn alloys from longitudinal spin fluctuation theory,” International Journal of Plasticity. 2019. link Times cited: 16 S. Bigdeli and M. Selleby, “A thermodynamic assessment of the binary Fe-Mn system for the third generation of Calphad databases,” Calphad. 2019. link Times cited: 25 E. Lee, K.-R. Lee, and B.-J. Lee, “An interatomic potential for the Li-Co-O ternary system,” Computational Materials Science. 2018. link Times cited: 16 J. Schuler and T. Rupert, “Materials selection rules for amorphous complexion formation in binary metallic alloys.” 2017. link Times cited: 68 C.-jun Wu, B.-J. Lee, and X. Su, “Modified embedded-atom interatomic potential for Fe-Ni, Cr-Ni and Fe-Cr-Ni systems,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2017. link Times cited: 60 W. Choi, Y. Kim, D. Seol, and B.-J. Lee, “Modified embedded-atom method interatomic potentials for the Co-Cr, Co-Fe, Co-Mn, Cr-Mn and Mn-Ni binary systems,” Computational Materials Science. 2017. link Times cited: 62 A. P. Moore, B. Beeler, C. Deo, M. Baskes, and M. Okuniewski, “Atomistic modeling of high temperature uranium–zirconium alloy structure and thermodynamics,” Journal of Nuclear Materials. 2015. link Times cited: 41 B. Zhao, L. Shvindlerman, and G. Gottstein, “On the orientation dependence of grain boundary triple line energy in Cu,” International Journal of Materials Research. 2014. link Times cited: 5 Abstract: Triple lines are the lines of intersection of three interfac… read more Abstract: Triple lines are the lines of intersection of three interfaces, either external interfaces or internal interfaces of a bulk material. They have been recognized as important microstructural features with specific kinetic and thermodynamic properties. Utilizing atomic force microscopy, the line tensions, i.e. the energy of grain boundary-free surface triple lines and grain boundary triple junctions for different crystallographic systems in copper were determined. The line tension of grain boundary triple junctions in copper was found to be positive and of the order of 10−9 J m−1. Junctions including low energy boundaries, twin boundaries and low angle boundaries revealed a substantially lower line tension than triple junctions comprised only of random high angle boundaries. A simple model based on a constant grain boundary energy density is proposed to account for the orientation dependence of triple line energy. read less T. A. Timmerscheidt, J. Appen, and R. Dronskowski, “A molecular-dynamics study on carbon diffusion in face-centered cubic iron,” Computational Materials Science. 2014. link Times cited: 14 R. Xiong, H. Peng, H. Si, W. Zhang, and Y. Wen, “Thermodynamic calculation of stacking fault energy of the Fe–Mn–Si–C high manganese steels,” Materials Science and Engineering A-structural Materials Properties Microstructure and Processing. 2014. link Times cited: 61 J. Zhang, R. Rynko, J. Frenzel, C. Somsen, and G. Eggeler, “Ingot metallurgy and microstructural characterization of Ti–Ta alloys,” International Journal of Materials Research. 2014. link Times cited: 25 Abstract: In the present work we perform a detailed investigation of i… read more Abstract: In the present work we perform a detailed investigation of ingot metallurgy processing routes of Ti-30Ta, a shape memory alloy with a good potential for applications at higher temperatures. There is currently considerable interest in high temperature shape memory alloys, both in industry (automotive and aerospace applications) and in academia. By means of scanning electron microscopy, we provide recommendations on the number of remelting cycles in the vacuum arc melting process, and on annealing temperatures/times in order to obtain chemical homogeneity. It is also shown that this is required to obtain well defined differential scanning calorimeter charts, which facilitates characterization and investigations of martensitic transformation in this alloy. Areas in need of further work are identified. read less G. Bonny et al., “On the thermal stability of late blooming phases in reactor pressure vessel steels: An atomistic study,” Journal of Nuclear Materials. 2013. link Times cited: 77 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 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 J. Nakano and P. Jacques, “Effects of the thermodynamic parameters of the hcp phase on the stacking fault energy calculations in the Fe–Mn and Fe–Mn–C systems,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2010. link Times cited: 122 Y.-M. Kim, N. Kim, and B.-J. Lee, “Atomistic Modeling of pure Mg and Mg―Al systems,” Calphad-computer Coupling of Phase Diagrams and Thermochemistry. 2009. link Times cited: 119 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 B. Lv, C. Chen, F. Zhang, G. Poletaev, and R. Rakitin, “Potentials for Describing Interatomic Interactions in γFe-Mn-C-N System,” Metals. 2022. link Times cited: 1 Abstract: Potentials for describing interatomic interactions in a γFe-… read more Abstract: Potentials for describing interatomic interactions in a γFe-Mn-C-N multicomponent system, modified Hadfield steel, where face-centered cubic (f.c.c.) iron is the main component, are proposed. To describe the Fe-Fe interactions in austenite, it is proposed to use Lau EAM potential. For all other interactions, Morse potentials are proposed, the parameters of which were found from various experimental characteristics: in particular, the energy of dissolution and migration of an impurity in an f.c.c. iron crystal, the radius of atoms, their electronegativity, mutual binding energy, etc. The found potentials are intended for modeling the atomic structures and processes occurring at the atomic level in Hadfield steel using relatively large computational cells by the molecular dynamics method. read less A. Daramola, G. Bonny, G. Adjanor, C. Domain, G. Monnet, and A. Fraczkiewicz, “Development of a plasticity-oriented interatomic potential for CrFeMnNi high entropy alloys,” Computational Materials Science. 2022. link Times cited: 4 J. Li et al., “Unveiling the atomic-scale origins of high damage tolerance of single-crystal high entropy alloys,” Physical Review Materials. 2020. link Times cited: 13 Abstract: High entropy alloys (HEAs) exhibit an unusual combination of… read more Abstract: High entropy alloys (HEAs) exhibit an unusual combination of high fracture strength and ductility. However, atomic mechanisms responsible for crack propagation in HEAs are still not clear, which limits further improving the damage tolerance. Here we investigate effect of crystal orientation on the crack-tip behaviors in single-crystal HEA CrMnFeCoNi using atomic simulations to explore fracture micromechanism. The formation of deformation twinning and activation of multislip systems are observed during the propagation crack with the $(001)\ensuremath{\langle}110\ensuremath{\rangle}$ orientation, consistent with the previous experiments. Under the $(\overline{1}10)\ensuremath{\langle}110\ensuremath{\rangle}$ orientation, the amorphous region takes place throughout the crack growth, and is difficult to occur in traditional metal materials. Dissimilarly, for the $(1\overline{1}\overline{1})\ensuremath{\langle}110\ensuremath{\rangle}$ orientation, the blunting and slip bands occur at the front of the crack tip by switching the slip mode from the planar to wavy slip, observed in recent transmission electron microscopy experiments. The chemical disorder leads to the obvious fluctuation of flow stress, but hardly affects the deformation mechanism at the crack tip. Compared to traditional metals and alloys, the high local stress concentration induced by coupling effect of severe lattice distortion and tension strain leads to the structure transformation from crystallization to amorphization at the crack tip in HEA. While the presented atomic simulations and the associated conclusions are based on CrMnFeCoNi HEA, it is believed that the current deformation mechanism at crack tip could also be applied to other face-centered-cubic HEA. read less J. Mianroodi, P. Shanthraj, A. K. da Silva, B. Svendsen, and D. Raabe, “Combined modeling and experimental characterization of Mn segregation and spinodal decomposition along dislocation lines in Fe-Mn alloys,” Acta Materialia. 2022. link Times cited: 2 V. Turlo and T. Rupert, “Interdependent Linear Complexion Structure and Dislocation Mechanics in Fe-Ni,” Crystals. 2020. link Times cited: 4 Abstract: Using large-scale atomistic simulations, dislocation mechani… read more Abstract: Using large-scale atomistic simulations, dislocation mechanics in the presence of linear complexions are investigated in an Fe-Ni alloy, where the complexions appear as nanoparticle arrays along edge dislocation lines. When mechanical shear stress is applied to drive dislocation motion, a strong pinning effect is observed where the defects are restricted by their own linear complexion structures. This pinning effect becomes weaker after the first dislocation break-away event, leading to a stress-strain curve with a profound initial yield point, similar to the static strain aging behavior observed experimentally for Fe-Mn alloys with the same type of linear complexions. The existence of such a response can be explained by local diffusion-less and lattice distortive transformations corresponding to L10-to-B2 phase transitions within the linear complexion nanoparticles. As such, an interdependence between a linear complexion structure and dislocation mechanics is found. read less J. Kundu, A. Chakraborty, and S. Kundu, “Bonding pressure effects on characteristics of microstructure, mechanical properties, and mass diffusivity of Ti-6Al-4V and TiAlNb diffusion-bonded joints,” Welding in the World. 2020. link Times cited: 3 Z. Aitken, V. Sorkin, and Y.-W. Zhang, “Atomistic modeling of nanoscale plasticity in high-entropy alloys,” Journal of Materials Research. 2019. link Times cited: 32 Abstract: Lattice structures, defect structures, and deformation mecha… read more Abstract: Lattice structures, defect structures, and deformation mechanisms of high-entropy alloys (HEAs) have been studied using atomistic simulations to explain their remarkable mechanical properties. These atomistic simulation techniques, such as first-principles calculations and molecular dynamics allow atomistic-level resolution of structure, defect configuration, and energetics. Following the structure–property paradigm, such understandings can be useful for guiding the design of high-performance HEAs. Although there have been a number of atomistic studies on HEAs, there is no comprehensive review on the state-of-the-art techniques and results of atomistic simulations of HEAs. This article is intended to fill the gap, providing an overview of the state-of-the-art atomistic simulations on HEAs. In particular, we discuss how atomistic simulations can elucidate the nanoscale mechanisms of plasticity underlying the outstanding properties of HEAs, and further present a list of interesting problems for forthcoming atomistic simulations of HEAs. read less L. N. Abdulkadir, K. Abou-El-Hossein, A. I. Jumare, M. Liman, T. A. Olaniyan, and P. B. Odedeyi, “Review of molecular dynamics/experimental study of diamond-silicon behavior in nanoscale machining,” The International Journal of Advanced Manufacturing Technology. 2018. link Times cited: 38 L. N. Abdulkadir, K. Abou-El-Hossein, A. I. Jumare, M. Liman, T. A. Olaniyan, and P. B. Odedeyi, “Review of molecular dynamics/experimental study of diamond-silicon behavior in nanoscale machining,” The International Journal of Advanced Manufacturing Technology. 2018. link Times cited: 0 W. Choi, Y. Jo, S. Sohn, S. Lee, and B.-J. Lee, “Understanding the physical metallurgy of the CoCrFeMnNi high-entropy alloy: an atomistic simulation study,” npj Computational Materials. 2018. link Times cited: 436 P. Chowdhury, D. Canadinc, and H. Sehitoglu, “On deformation behavior of Fe-Mn based structural alloys,” Materials Science & Engineering R-reports. 2017. link Times cited: 95 E. Lee, K.-R. Lee, and B.-J. Lee, “Interatomic Potential of Li–Mn–O and Molecular Dynamics Simulations on Li Diffusion in Spinel Li1–xMn2O4,” Journal of Physical Chemistry C. 2017. link Times cited: 12 Abstract: An interatomic potential of the Li–Mn–O ternary system has b… read more Abstract: An interatomic potential of the Li–Mn–O ternary system has been developed on the basis of the second-nearest-neighbor modified embedded-atom method (2NN MEAM) formalism combined with a charge equilibration (Qeq) concept. The potential reproduces fundamental physical properties (structural, elastic, thermodynamic and migration properties) of various compounds well, including lithium oxides, manganese oxides, and lithium manganese ternary oxides. Through molecular dynamics (MD) simulations using the developed potential, lithium diffusion properties (activation energy for lithium migration and diffusion coefficient) in spinel Li1–xMn2O4 are also reproduced in good agreement with experiments. We have found that the effect of the lithium vacancy concentration is marginal on the activation energy for lithium diffusion in the Li1–xMn2O4 cathode, but it is significant in the lithium diffusion coefficient. The potential can be further utilized for atomistic simulations of various materials phenomena (phase transit... read less S. Bigdeli, H. Ehtehsami, Q. Chen, H. Mao, P. Korzhavy, and M. Selleby, “New description of metastable hcp phase for unaries Fe and Mn: Coupling between first‐principles calculations and CALPHAD modeling,” physica status solidi (b). 2016. link Times cited: 31 Abstract: The main focus in developing the third generation of CALPHAD… read more Abstract: The main focus in developing the third generation of CALPHAD databases is to model thermodynamic properties of materials by using models which are more physically based and valid down to 0 K. First‐principles calculations are helpful to choose and validate those models. Reliable calculation results, for example, at very low temperatures or on metastable systems reveal physical facts which might be inaccessible by experiments. Following our earlier work for modeling thermodynamic properties of pure elements (i.e., Fe and Mn) in third‐generation CALPHAD databases, the ε (hcp) phase was modeled as a metastable phase in the present work. Although hcp phase is just observed in these two elements under ultra‐high pressure, in the binary Fe–Mn this phase is metastable at ambient temperatures and pressures. Therefore, it should be properly modeled in unaries for later optimization of binary systems. Based on density functional theory (DFT) calculations, the magnetic ground state and the magnetic properties of ε ‐Fe, ε ‐Mn, and their binary solution phase were calculated. It was found that ε ‐Fe is anti‐ferromagnetic (type II) while ε ‐Mn has a paramagnetic ground state. Accordingly, magnetic contributions to thermodynamic properties were accurately modeled. Moreover, by means of the extrapolation of experimental data for the thermodynamic properties of binary systems and high‐pressure data for unaries, the metastable hcp phases at ambient pressure were modeled for the third‐generation CALPHAD database, consistently with other stable phases in the elements Fe and Mn. read less S. Bigdeli, H. Mao, and M. Selleby, “On the third‐generation Calphad databases: An updated description of Mn,” physica status solidi (b). 2015. link Times cited: 49 Abstract: Aiming for better extrapolations and predictabilities of the… read more Abstract: Aiming for better extrapolations and predictabilities of thermodynamic properties of materials, new thermodynamic models are implemented in the third‐generation Calphad databases. In these models, each term contributing to the Gibbs energy has an explicit physical meaning. Furthermore, descriptions of thermodynamic properties of materials are valid from 0 K up to high temperatures far above the melting point. As a starting point for the development of large self‐consistent third‐generation database, the new models in the present work are applied to the unary manganese system. Taking into account both the calculated first principles results and experimental data, thermodynamic model parameters are evaluated. Thermodynamic properties predicted using this description, agree very well with available data. The calculated properties vary smoothly in the whole temperature range, which is another important improvement compared to the second‐generation databases. read less J. Chun and B. Lee, “Atomistic calculations of mechanical properties of Ni-Ti-C metallic glass systems,” Journal of Mechanical Science and Technology. 2013. link Times cited: 3 J. Chun and B. Lee, “Atomistic calculations of mechanical properties of Ni-Ti-C metallic glass systems,” Journal of Mechanical Science and Technology. 2013. link Times cited: 0 E. Lee and B.-J. Lee, “Modified embedded-atom method interatomic potential for the Fe–Al system,” Journal of Physics: Condensed Matter. 2010. link Times cited: 100 Abstract: An interatomic potential for the Fe–Al binary system has bee… read more Abstract: An interatomic potential for the Fe–Al binary system has been developed based on the modified embedded-atom method (MEAM) potential formalism. The potential can describe various fundamental physical properties of Fe–Al binary alloys—structural, elastic and thermodynamic properties, defect formation behavior and interactions between defects—in reasonable agreement with experimental data or higher-level calculations. The applicability of the potential to atomistic investigations of various defect formation behaviors and their effects on the mechanical properties of high aluminum steels as well as Fe–Al binary alloys is demonstrated. read less B.-J. Lee, “A Semi-Empirical Atomistic Approach in Materials Research,” Journal of Phase Equilibria and Diffusion. 2009. link Times cited: 3 E. C. Do, Y.-H. Shin, and B.-J. Lee, “Atomistic modeling of III–V nitrides: modified embedded-atom method interatomic potentials for GaN, InN and Ga1−xInxN,” Journal of Physics: Condensed Matter. 2009. link Times cited: 26 Abstract: Modified embedded-atom method (MEAM) interatomic potentials … read more Abstract: Modified embedded-atom method (MEAM) interatomic potentials for the Ga–N and In–N binary and Ga–In–N ternary systems have been developed based on the previously developed potentials for Ga, In and N. The potentials can describe various physical properties (structural, elastic and defect properties) of both zinc-blende and wurtzite-type GaN and InN as well as those of constituent elements, in good agreement with experimental data or high-level calculations. The potential can also describe the structural behavior of Ga1−xInxN ternary nitrides reasonably well. The applicability of the potentials to atomistic investigations of atomic/nanoscale structural evolution in Ga1−xInxN multi-component nitrides during the deposition of constituent element atoms is discussed. read less N. Razmara and R. Mohammadzadeh, “Molecular dynamics study of nitrogen diffusion in nanocrystalline iron,” Journal of Molecular Modeling. 2016. link Times cited: 6
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_058735400462_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_KimShinLee_2009_FeMn__MO_058735400462_002
DOI	10.25950/a9c5adcc https://doi.org/10.25950/a9c5adcc https://commons.datacite.org/doi.org/10.25950/a9c5adcc
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_KimShinLee_2009_FeMn__MO_058735400462_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
A The letter grade A was assigned because the normalized error in the computation was 2.32023e-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
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: Fe

Species: Mn

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

Species: Mn

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

Species: Mn

Dislocation Core Energies

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

(No matching species)

FCC Elastic Constants

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

Species: 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: Mn

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

Species: Mn

Cubic Crystal Basic Properties Table

Species: Fe

Species: Mn

Tests

CohesiveEnergyVsLatticeConstant__TD_554653289799_003

Cohesive energy versus lattice constant curve for monoatomic cubic lattices v003

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

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

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Cohesive energy versus lattice constant curve for bcc Fe v004	view	9220
Cohesive energy versus lattice constant curve for bcc Mn v004	view	11117
Cohesive energy versus lattice constant curve for diamond Fe v004	view	9638
Cohesive energy versus lattice constant curve for diamond Mn v004	view	9260
Cohesive energy versus lattice constant curve for fcc Fe v004	view	10969
Cohesive energy versus lattice constant curve for fcc Mn v004	view	8872
Cohesive energy versus lattice constant curve for sc Fe v004	view	9419
Cohesive energy versus lattice constant curve for sc Mn v004	view	12363

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	51381
Elastic constants for diamond Fe at zero temperature v001	view	57926
Elastic constants for fcc Fe at zero temperature v006	view	47701
Elastic constants for sc Fe at zero temperature v006	view	29154

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	90411
Equilibrium crystal structure and energy for Mn in AFLOW crystal prototype A_cF4_225_a v002	view	91510
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_cI2_229_a v002	view	62401
Equilibrium crystal structure and energy for Mn in AFLOW crystal prototype A_cI58_217_ac2g v002	view	277552
Equilibrium crystal structure and energy for Mn in AFLOW crystal prototype A_cP20_213_cd v002	view	143560
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_hP2_194_c v002	view	82234
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_tP28_136_f2ij v002	view	71028

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 bcc Fe v001	view	7505719
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in bcc Fe v001	view	22461579
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in bcc Fe v001	view	12614442
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in bcc Fe v001	view	46427689
Relaxed energy as a function of tilt angle for a 100 symmetric tilt grain boundary in fcc Fe v001	view	19876246
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Fe v001	view	75897409
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Fe v001	view	34362505

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	17336
Equilibrium zero-temperature lattice constant for bcc Mn v007	view	19509
Equilibrium zero-temperature lattice constant for diamond Fe v007	view	27092
Equilibrium zero-temperature lattice constant for diamond Mn v007	view	22030
Equilibrium zero-temperature lattice constant for fcc Fe v007	view	16729
Equilibrium zero-temperature lattice constant for fcc Mn v007	view	14650
Equilibrium zero-temperature lattice constant for sc Fe v007	view	16481
Equilibrium zero-temperature lattice constant for sc Mn v007	view	16749

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	189278
Equilibrium lattice constants for hcp Mn v005		view	214764

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	1476017

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	70577

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	295365

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	3367623

Errors

ElasticConstantsCubic__TD_011862047401_006

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

ElasticConstantsHexagonal__TD_612503193866_004

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

VacancyFormationEnergyRelaxationVolume__TD_647413317626_001

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

VacancyFormationMigration__TD_554849987965_001

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

No Driver

Verification Check	Error Categories	Link to Error page
DimerContinuityC1__VC_303890932454_005	other	view

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

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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_KimShinLee_2009_FeMn__MO_058735400462_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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