EAM potential (2nd gen magnetic, quintic tabulation) for magnetic Fe developed by Chiesa et al. (2011) v002

Samuele Chiesa; Helena van Swygenhoven; Sergei Dudarev; Peter Derlet

doi:10.25950/ce6a5ce5

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EAM_Magnetic2GQuintic_ChiesaDerletDudarev_2011_Fe__MO_140444321607_002

Interatomic potential for Iron (Fe).
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Title A single sentence description.	EAM potential (2nd gen magnetic, quintic tabulation) for magnetic Fe developed by Chiesa et al. (2011) v002
Description A short description of the Model describing its key features including for example: type of model (pair potential, 3-body potential, EAM, etc.), modeled species (Ac, Ag, ..., Zr), intended purpose, origin, and so on.	A second generation of empirical potentials is produced for α-Fe within the framework of the magnetic potential formalism (Dudarev and Derlet 2005 J. Phys.: Condens. Matter 17 7097). This is a parameterization for bcc Fe fitted to a database of material parameters, including ab initio-derived point defect formation energies, third-order elastic constants, and ab initio-derived string potential data, the final two controlling, respectively, the thermal expansion properties and the core structure of the 1/2<111> screw dislocation. The potential produces a non-degenerate configuration for the relaxed 1/2<111> screw dislocation.
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

Contributor	Mark R. Gilbert
Maintainer	Mark R. Gilbert
Developer	Samuele Chiesa Helena van Swygenhoven Sergei Dudarev Peter Derlet
Published on KIM	2018
How to Cite	This Model originally published in [1] is archived in OpenKIM [2-5]. [1] Chiesa S, Derlet PM, Dudarev SL, Swygenhoven HV. Optimization of the magnetic potential for α-Fe. Journal of Physics: Condensed Matter. 2011;23(20):206001. doi:10.1088/0953-8984/23/20/206001 — (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] Chiesa S, Swygenhoven H van, Dudarev S, Derlet P. EAM potential (2nd gen magnetic, quintic tabulation) for magnetic Fe developed by Chiesa et al. (2011) v002. OpenKIM; 2018. doi:10.25950/ce6a5ce5 [3] Gilbert MR, Chiesa S, Derlet P, Dudarev S, Swygenhoven H van. Second generation EAM potential within the magnetic potential formalism with quintic interpolation v002. OpenKIM; 2018. doi:10.25950/ed3ceac9 [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. 42 Citations (22 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 . J. J. Möller and E. Bitzek, “BDA: A novel method for identifying defects in body-centered cubic crystals,” MethodsX. 2016. link Times cited: 17 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 E. Angelova and H. Chamati, “Dynamic Simulation of the Energy Spectrum of Phonons in the Magnetic BCC Iron,” Proceedings of the Bulgarian Academy of Sciences. 2022. link Times cited: 1 Abstract: We used the symplectic and scalable algorithm for spin … read more Abstract: We used the symplectic and scalable algorithm for spin lattice dynamics embedded in LAMMPS to model the coupled relaxation processes of the spin and lattice subsystems to investigate the phonon dispersion of bcc Fe at T = 300 K. The atomic interactions were modelled via three semi-empirical many-body potentials within the embedded atom method, while the distance-dependent spin coupling relied on the Heisenberg-type Hamiltonian. In the state of mutual equilibrium of the spin and atom ensembles, we have calculated the dynamical matrix and the phonon spectra in bcc iron. We found that for a small to moderate wavevector absolute values, the phonon dispersion curves agree well with the experimental results obtained from inelastic neutron scattering, while discrepancies between theory and experiment were observed for larger wavevector values, particularly near the zone boundaries. Moreover, the impact of magnons on the phonon spectra is pronounced for all employed potentials. read less P. Derlet and S. Dudarev, “Microscopic structure of a heavily irradiated material,” Physical Review Materials. 2020. link Times cited: 48 Abstract: New generation nuclear fission and future fusion reactors pr… read more Abstract: New generation nuclear fission and future fusion reactors provide one approach to address the world's increasing energy requirements. The irradiation of fission/fusion components can lead to fundamental changes in material properties that affect the stability and performance of not only the material component but that of the entire reactor. How does the material state evolve with respect to the irradiation dose, and can there exist a microstructure resistant to further irradiation? The present work develops a new computationally efficient approach to answer these questions. read less J. J. Moller et al., “110 planar faults in strained bcc metals: Origins and implications of a commonly observed artifact of classical potentials,” Physical Review Materials. 2018. link Times cited: 18 Abstract: Large-scale atomistic simulations with classical potentials … read more Abstract: Large-scale atomistic simulations with classical potentials can provide valuable insights into microscopic deformation mechanisms and defect-defect interactions in materials. Unfortunately, these assets often come with the uncertainty of whether the observed mechanisms are based on realistic physical phenomena or whether they are artifacts of the employed material models. One such example is the often reported occurrence of stable planar faults (PFs) in body-centered cubic (bcc) metals subjected to high strains, e.g., at crack tips or in strained nano-objects. In this paper, we study the strain dependence of the generalized stacking fault energy (GSFE) of {110} planes in various bcc metals with material models of increasing sophistication, i.e., (modified) embedded atom method, angular-dependent, Tersoff, and bond-order potentials as well as density functional theory. We show that under applied tensile strains the GSFE curves of many classical potentials exhibit a local minimum which gives rise to the formation of stable PFs. These PFs do not appear when more sophisticated material models are used and have thus to be regarded as artifacts of the potentials. We demonstrate that the local GSFE minimum is not formed for reasons of symmetry and we recommend including the determination of the strain-dependent (110) GSFE as a benchmark for newly developed potentials. read less V. V. Pogorelko and A. Mayer, “Dynamic tensile fracture of iron: Molecular dynamics simulations and micromechanical model based on dislocation plasticity,” International Journal of Plasticity. 2023. link Times cited: 4 L. Ventelon, D. Caillard, B. Lüthi, E. Clouet, D. Rodney, and F. Willaime, “Mobility of carbon-decorated screw dislocations in bcc iron,” Acta Materialia. 2023. link Times cited: 1 R. S. Varanasi, M. Lipińska-Chwałek, J. Mayer, B. Gault, and D. Ponge, “Mechanisms of austenite growth during intercritical annealing in medium manganese steels,” Scripta Materialia. 2022. link Times cited: 21 Z. Wu, R. Wang, L. Zhu, S. Pattamatta, and D. Srolov, “Revealing and Controlling the Core of Screw Dislocations in BCC Metals.” 2021. link Times cited: 0 Abstract: Body-centred-cubic (BCC) transition metals (TMs) tend to b… read more Abstract: Body-centred-cubic (BCC) transition metals (TMs) tend to be brittle at low temperatures, posing significant challenges in their processing and major concerns for damage tolerance in critical load-carrying applications. The brittleness is largely dictated by the screw dislocation core structure; the nature and control of which has remained a puzzle for nearly a century. Here, we introduce a universal model and a physics-based material index χ that guides the manipulation of dislocation core structure in all pure BCC metals and alloys. We show that the core structure, commonly classified as degenerate (D) or non-degenerate (ND), is governed by the energy difference between BCC and face-centred cubic (FCC) structures and χ robustly captures this key quantity. For BCC TMs alloys, the core structure transition from ND to D occurs when χ drops below a threshold, as seen in atomistic simulations based on nearly all extant interatomic potentials and density functional theory (DFT) calculations of W-Re/Ta alloys. In binary W-TMs alloys, DFT calculations show that χ is related to the valence electron concentration at low to moderate solute concentrations, and can be controlled via alloying. χ can be quantitatively and efficiently predicted via rapid, low-cost DFT calculations for any BCC metal alloys, providing a robust, easily applied tool for the design of ductile and tough BCC alloys. read less A. Mayer, “Micromechanical model of nanoparticle compaction and shock waves in metal powders,” International Journal of Plasticity. 2021. link Times cited: 11 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 J. Wang, Q. Hou, and B. L. Zhang, “Migration behavior of self-interstitial defects in tungsten and iron,” Solid State Communications. 2021. link Times cited: 4 S. Starikov, M. Mrovec, and R. Drautz, “Study of Grain Boundary Self-Diffusion in Iron with Different Atomistic Models,” MatSciRN: Computational Studies of Inorganic & Organic Materials (Topic). 2019. link Times cited: 22 K. Lai, H. Wen, J. Liu, Y. Wu, and Y. Zheng, “Ferromagnetic effects on non-Arrhenius diffusion of single interstitial helium solute in BCC Fe,” Journal of Nuclear Materials. 2019. link Times cited: 7 T. Suzudo, T. Onitsuka, and K. Fukumoto, “Analyzing the cross slip motion of screw dislocations at finite temperatures in body-centered-cubic metals: molecular statics and dynamics studies,” Modelling and Simulation in Materials Science and Engineering. 2019. link Times cited: 13 Abstract: The plasticity of body-centered-cubic metals at low temperat… read more Abstract: The plasticity of body-centered-cubic metals at low temperatures is substantially determined by the screw-dislocation kinetics. Because the core of screw dislocations in these metals has a non-planar structure, its motion is complex. For example, although density functional theory predicts slip on a {110} plane, the actual slip plane at elevated temperatures differs from the prediction. In this work, we explored state-of-the-art atomistic modeling methods and successfully reproduced the transition of the slip plane through a temperature increase. We then devised an algorithm to analyze the activation of dislocation jump over the Peierls barrier and discovered a possible origin of this unexpected phenomenon: thermal fluctuation leads to the kink-pair nucleation for cross slip jumps with no transition of the dislocation core structure. read less C. Gao, D. Tian, M. Li, and D.-zhi Qian, “Comparative study of displacement cascades simulated with ‘magnetic’ potentials and Mendelev-type potential in α-Fe,” Journal of Nuclear Materials. 2017. link Times cited: 7 J. Bach, J. J. Möller, M. Göken, E. Bitzek, and H. Höppel, “On the transition from plastic deformation to crack initiation in the high- and very high-cycle fatigue regimes in plain carbon steels,” International Journal of Fatigue. 2016. link Times cited: 23 A. Al-Motasem, N. Mai, S. Choi, and M. Posselt, “Atomistic study on mixed-mode fracture mechanisms of ferrite iron interacting with coherent copper and nickel nanoclusters,” Journal of Nuclear Materials. 2016. link Times cited: 10 H. Wen and C. Woo, “Quantum statistics in the spin-lattice dynamics simulation of formation and migration of mono-vacancy in BCC iron,” Journal of Nuclear Materials. 2016. link Times cited: 14 J. J. Möller and E. Bitzek, “On the influence of crack front curvature on the fracture behavior of nanoscale cracks,” Engineering Fracture Mechanics. 2015. link Times cited: 26 S. M. H. Haghighat et al., “Influence of the dislocation core on the glide of the ½ 110 edge dislocation in bcc-iron: An embedded atom method study,” Computational Materials Science. 2014. link Times cited: 14 P. Staikov and N. Djourelov, “Simulations of 〈1 0 0〉 edge and 1/2〈1 1 1〉 screw dislocations in α-iron and tungsten and positron lifetime calculations,” Physica B-condensed Matter. 2013. link Times cited: 23 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. M. Woryk et al., “Geometrically necessary dislocation fingerprints of dislocation loop absorption at grain boundaries,” Physical Review Materials. 2022. link Times cited: 0 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 T. Shimada, K. Ouchi, I. Ikeda, Y. Ishii, and T. Kitamura, “Magnetic instability criterion for spin–lattice systems,” Computational Materials Science. 2015. link Times cited: 12 D. Duffy, “Energy Generation: Nuclear Energy.” 2013. link Times cited: 0 J. J. Möller and E. Bitzek, “Atomic-scale modeling of elementary processes during the fatigue of metallic materials: from crack initiation to crack-microstructure interactions.” 2018. link Times cited: 1 R. Meyer et al., “Vibrational and magnetic signatures of extended defects in Fe,” The European Physical Journal B. 2020. link Times cited: 5 H. Wen, Y. Wu, J. Liu, and Y. Zheng, “Ferromagnetic effects on helium-vacancy complex formation in BCC Fe,” Journal of Physics: Condensed Matter. 2019. link Times cited: 3 Abstract: The substitution of helium atom inside BCC Fe results in (1)… read more Abstract: The substitution of helium atom inside BCC Fe results in (1) lattice distortion, (2) the resonance phonon modes, and (3) the scattering center, enhancing the anharmonicity of phonon and magnon. The ferromagnetic effects are analyzed by comparing results in the ferromagnetic and non-magnetic systems using spin-lattice dynamics simulations based on quantum fluctuation dissipation relation. The ferromagnetic effects are subtracted into static and dynamic contributions, where the former is found to be dominant. Neglecting ferromagnetic effects would bring with unexpected large error in the description of kinetics of helium in metals. read less A. Mutter, B. Wang, J. Meiser, P. Umstätter, and H. Urbassek, “Magnetic structure of [0 0 1] tilt grain boundaries in bcc Fe studied via magnetic potentials,” Philosophical Magazine. 2017. link Times cited: 4 Abstract: Using magnetic potentials and a molecular statics approach, … read more Abstract: Using magnetic potentials and a molecular statics approach, we study the changes in the magnetic structure of bcc Fe in the vicinity of grain boundaries (GBs). We focus on symmetric tilt GBs around the [0 0 1] axis with a tilt angle between 7 and 53. We find that immediately in the GB plane, the deviations in the magnetic moments from the bulk value are most pronounced. The distribution of moments in the GB plane is modulated according to the periodicity of the coincidence site lattice. In the direction perpendicular to the GB plane, the moments decay exponentially towards the bulk value; the decay length increases with decreasing tilt angle. This dependence can be explained by the well-known stress field around GBs. read less D. Dragoni, T. Daff, G. Csányi, and N. Marzari, “Achieving DFT accuracy with a machine-learning interatomic potential: thermomechanics and defects in bcc ferromagnetic iron,” arXiv: Materials Science. 2017. link Times cited: 167 Abstract: We show that the Gaussian Approximation Potential machine le… read more Abstract: We show that the Gaussian Approximation Potential machine learning framework can describe complex magnetic potential energy surfaces, taking ferromagnetic iron as a paradigmatic challenging case. The training database includes total energies, forces, and stresses obtained from density-functional theory in the generalized-gradient approximation, and comprises approximately 150,000 local atomic environments, ranging from pristine and defected bulk configurations to surfaces and generalized stacking faults with different crystallographic orientations. We find the structural, vibrational and thermodynamic properties of the GAP model to be in excellent agreement with those obtained directly from first-principles electronic-structure calculations. There is good transferability to quantities, such as Peierls energy barriers, which are determined to a large extent by atomic configurations that were not part of the training set. We observe the benefit and the need of using highly converged electronic-structure calculations to sample a target potential energy surface. The end result is a systematically improvable potential that can achieve the same accuracy of density-functional theory calculations, but at a fraction of the computational cost. read less C. Angelie and J. Soudan, “Nanothermodynamics of iron clusters: Small clusters, icosahedral and fcc-cuboctahedral structures.,” The Journal of chemical physics. 2017. link Times cited: 3 Abstract: The study of the thermodynamics and structures of iron clust… read more Abstract: The study of the thermodynamics and structures of iron clusters has been carried on, focusing on small clusters and initial icosahedral and fcc-cuboctahedral structures. Two combined tools are used. First, energy intervals are explored by the Monte Carlo algorithm, called σ-mapping, detailed in the work of Soudan et al. [J. Chem. Phys. 135, 144109 (2011), Paper I]. In its flat histogram version, it provides the classical density of states, gp(Ep), in terms of the potential energy of the system. Second, the iron system is described by a potential which is called "corrected EAM" (cEAM), explained in the work of Basire et al. [J. Chem. Phys. 141, 104304 (2014), Paper II]. Small clusters from 3 to 12 atoms in their ground state have been compared first with published Density Functional Theory (DFT) calculations, giving a complete agreement of geometries. The series of 13, 55, 147, and 309 atom icosahedrons is shown to be the most stable form for the cEAM potential. However, the 147 atom cluster has a special behaviour, since decreasing the energy from the liquid zone leads to the irreversible trapping of the cluster in a reproducible amorphous state, 7.38 eV higher in energy than the icosahedron. This behaviour is not observed at the higher size of 309 atoms. The heat capacity of the 55, 147, and 309 atom clusters revealed a pronounced peak in the solid zone, related to a solid-solid transition, prior to the melting peak. The corresponding series of 13, 55, and 147 atom cuboctahedrons has been compared, underscoring the unstability towards the icosahedral structure. This unstability occurs clearly in several steps for the 147 atom cluster, with a sudden transformation at a transition state. This illustrates the concerted icosahedron-cuboctahedron transformation of Buckminster Fuller-Mackay, which is calculated for the cEAM potential. Two other clusters of initial fcc structures with 24 and 38 atoms have been studied, as well as a 302 atom cluster. Each one relaxes towards a more stable structure without regularity. The 38 atom cluster exhibits a nearly glassy relaxation, through a cascade of six metastable states of long life. This behaviour, as that of the 147 atom cluster towards the amorphous state, shows that difficulties to reach ergodicity in the lower half of the solid zone are related to particular features of the potential energy landscape, and not necessarily to a too large size of the system. Comparisons of the cEAM iron system with published results about Lennard-Jones systems and DFT calculations are made. The results of the previous clusters have been combined with that of Paper II to plot the cohesive energy Ec and the melting temperature Tm in terms of the cluster atom number Nat. The Nat-1/3 linear dependence of the melting temperature (Pawlow law) is observed again for Nat > 150. In contrast, for Nat < 150, the curve diverges strongly from the Pawlow law, giving it an overall V-shape, with a linear increase of Tm when Nat goes from 55 to 13 atoms. Surprisingly, the 38 atom cluster is anomalously below the overall curve. read less M. G. D. V. Cuppari, R. Veiga, H. Goldenstein, J. E. G. Silva, and C. Becquart, “Lattice Instabilities and Phase Transformations in Fe from Atomistic Simulations,” Journal of Phase Equilibria and Diffusion. 2017. link Times cited: 2 C. P. Chui, W. Liu, Y. Xu, and Y. Zhou, “Molecular Dynamics Simulation of Iron — A Review.” 2015. link Times cited: 3 Abstract: Molecular dynamics (MD) is a technique of atomistic simulati… read more Abstract: Molecular dynamics (MD) is a technique of atomistic simulation which has facilitated scientific discovery of interactions among particles since its advent in the late 1950s. Its merit lies in incorporating statistical mechanics to allow for examination of varying atomic configurations at finite temperatures. Its contributions to materials science from modeling pure metal properties to designing nanowires is also remarkable. This review paper focuses on the progress of MD in understanding the behavior of iron — in pure metal form, in alloys, and in composite nanomaterials. It also discusses the interatomic potentials and the integration algorithms used for simulating iron in the literature. Furthermore, it reveals the current progress of MD in simulating iron by exhibiting some results in the literature. Finally, the review paper briefly mentions the development of the hardware and software tools for such large-scale computations. read less Z. Chen and J. Qu, “A fluctuation method to calculate the third order elastic constants in crystalline solids,” Journal of Applied Physics. 2015. link Times cited: 1 Abstract: This paper derives exact expressions of the isothermal third… read more Abstract: This paper derives exact expressions of the isothermal third order elastic constants (TOE) in crystalline solids in terms of the kinetic and potential energies of the system. These expressions reveal that the TOE constants consist of a Born component and a relaxation component. The Born component is simply the third derivative of the system's potential energy with respect to the deformation, while the relaxation component is related to the non-uniform rearrangements of the atoms when the system is subject to a macroscopic deformation. Further, based on the general expressions derived here, a direct (fluctuation) method of computing the isothermal TOE constants is developed. Numerical examples of using this fluctuation method are given to compute the TOE constants of single crystal iron. read less M. Basire, J. Soudan, and C. Angelie, “Nanothermodynamics of large iron clusters by means of a flat histogram Monte Carlo method.,” The Journal of chemical physics. 2014. link Times cited: 2 Abstract: The thermodynamics of iron clusters of various sizes, from 7… read more Abstract: The thermodynamics of iron clusters of various sizes, from 76 to 2452 atoms, typical of the catalyst particles used for carbon nanotubes growth, has been explored by a flat histogram Monte Carlo (MC) algorithm (called the σ-mapping), developed by Soudan et al. [J. Chem. Phys. 135, 144109 (2011), Paper I]. This method provides the classical density of states, gp(Ep) in the configurational space, in terms of the potential energy of the system, with good and well controlled convergence properties, particularly in the melting phase transition zone which is of interest in this work. To describe the system, an iron potential has been implemented, called "corrected EAM" (cEAM), which approximates the MEAM potential of Lee et al. [Phys. Rev. B 64, 184102 (2001)] with an accuracy better than 3 meV/at, and a five times larger computational speed. The main simplification concerns the angular dependence of the potential, with a small impact on accuracy, while the screening coefficients S(ij) are exactly computed with a fast algorithm. With this potential, ergodic explorations of the clusters can be performed efficiently in a reasonable computing time, at least in the upper half of the solid zone and above. Problems of ergodicity exist in the lower half of the solid zone but routes to overcome them are discussed. The solid-liquid (melting) phase transition temperature T(m) is plotted in terms of the cluster atom number N(at). The standard N(at)(-1/3) linear dependence (Pawlow law) is observed for N(at) >300, allowing an extrapolation up to the bulk metal at 1940 ±50 K. For N(at) <150, a strong divergence is observed compared to the Pawlow law. The melting transition, which begins at the surface, is stated by a Lindemann-Berry index and an atomic density analysis. Several new features are obtained for the thermodynamics of cEAM clusters, compared to the Rydberg pair potential clusters studied in Paper I. read less C. P. Chui and Y. Zhou, “Investigating the magnetovolume effect in isotropic body-centered-cubic iron using spin-lattice dynamics simulations,” AIP Advances. 2014. link Times cited: 2 Abstract: The understanding of the magnetovolume effect lacks explicit… read more Abstract: The understanding of the magnetovolume effect lacks explicit consideration of spin-lattice coupling at the atomic level, despite abundant theoretical and experimental studies throughout the years. This research gap is filled by the recently developed spin-lattice dynamics technique implemented in this study, which investigates the magnetovolume effect of isotropic body-centered-cubic (BCC) iron, a topic that has previously been subject to macroscopic analysis only. This approach demonstrates the magnetic anomaly followed by the volumetric changes associated with the effect, each characterized by the corresponding field-induced inflection temperature. The temperature of the heat capacity peaks is useful in determining the temperature for retarding the atomic volume increase. Moreover, this work shows the correlation between the effects of temperature and field strength in determining the equilibrium atomic volume of a ferromagnetic material under a magnetic field. read less J. J. Möller and E. Bitzek, “Comparative study of embedded atom potentials for atomistic simulations of fracture in α-iron,” Modelling and Simulation in Materials Science and Engineering. 2014. link Times cited: 50 Abstract: Atomistic simulations play a crucial role in advancing our u… read more Abstract: Atomistic simulations play a crucial role in advancing our understanding of the crack-tip processes that take place during fracture of semi-brittle materials like α-iron. As with all atomistic simulations, the results of such simulations however depend critically on the underlying atomic interaction model. Here, we present a systematic study of eight α-iron embedded atom method potentials used to model cracks subjected to plane strain mode-I loading conditions in six different crystal orientations. Molecular statics simulations are used to determine the fracture behavior (cleavage, dislocation emission, twinning) and the critical stress intensity factor KIc. The structural transformations in front of the crack tips, and in particular the occurrence of {1 1 0} planar faults, are analyzed in detail and related to the strain-dependent generalized stacking fault energy curve. The simulation results are discussed in terms of theoretical fracture criteria and compared to recent experimental data. The different potentials are ranked according to their capability to model the experimentally observed fracture behavior. read less M. Marinica et al., “Interatomic potentials for modelling radiation defects and dislocations in tungsten,” Journal of Physics: Condensed Matter. 2013. link Times cited: 258 Abstract: We have developed empirical interatomic potentials for study… read more Abstract: We have developed empirical interatomic potentials for studying radiation defects and dislocations in tungsten. The potentials use the embedded atom method formalism and are fitted to a mixed database, containing various experimentally measured properties of tungsten and ab initio formation energies of defects, as well as ab initio interatomic forces computed for random liquid configurations. The availability of data on atomic force fields proves critical for the development of the new potentials. Several point and extended defect configurations were used to test the transferability of the potentials. The trends predicted for the Peierls barrier of the 1 2 ⟨ 111 ⟩ ?> screw dislocation are in qualitative agreement with ab initio calculations, enabling quantitative comparison of the predicted kink-pair formation energies with experimental data. read less L. Ventelon, F. Willaime, E. Clouet, and D. Rodney, “Ab initio investigation of the Peierls potential of screw dislocations in bcc Fe and W,” Acta Materialia. 2013. link Times cited: 103 T. Lee, M. Baskes, S. Valone, and J. Doll, “Atomistic modeling of thermodynamic equilibrium and polymorphism of iron,” Journal of Physics: Condensed Matter. 2012. link Times cited: 52 Abstract: We develop two new modified embedded-atom method (MEAM) pote… read more Abstract: We develop two new modified embedded-atom method (MEAM) potentials for elemental iron, intended to reproduce the experimental phase stability with respect to both temperature and pressure. These simple interatomic potentials are fitted to a wide variety of material properties of bcc iron in close agreement with experiments. Numerous defect properties of bcc iron and bulk properties of the two close-packed structures calculated with these models are in reasonable agreement with the available first-principles calculations and experiments. Performance at finite temperatures of these models has also been examined using Monte Carlo simulations. We attempt to reproduce the experimental iron polymorphism at finite temperature by means of free energy computations, similar to the procedure previously pursued by Müller et al (2007 J. Phys.: Condens. Matter 19 326220), and re-examine the adequacy of the conclusion drawn in the study by addressing two critical aspects missing in their analysis: (i) the stability of the hcp structure relative to the bcc and fcc structures and (ii) the compatibility between the temperature and pressure dependences of the phase stability. Using two MEAM potentials, we are able to represent all of the observed structural phase transitions in iron. We discuss that the correct reproductions of the phase stability among three crystal structures of iron with respect to both temperature and pressure are incompatible with each other due to the lack of magnetic effects in this class of empirical interatomic potential models. The MEAM potentials developed in this study correctly predict, in the bcc structure, the self-interstitial in the 〈110〉 orientation to be the most stable configuration, and the screw dislocation to have a non-degenerate core structure, in contrast to many embedded-atom method potentials for bcc iron in the literature. read less
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_140444321607_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.	EAM_Magnetic2GQuintic_ChiesaDerletDudarev_2011_Fe__MO_140444321607_002
DOI	10.25950/ce6a5ce5 https://doi.org/10.25950/ce6a5ce5 https://commons.datacite.org/doi.org/10.25950/ce6a5ce5
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 EAM_Magnetic2GQuintic__MD_543355979582_002
Driver	EAM_Magnetic2GQuintic__MD_543355979582_002
KIM API Version	2.0
Potential Type	eam

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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 5.47678e-10 compared with a machine precision of 2.22045e-16. The letter grade was based on 'score=log10(error/eps)', with ranges A=[0, 7.5], B=(7.5, 10.0], C=(10.0, 12.5], D=(12.5, 15.0), F>15.0. 'A' is the best grade, and 'F' indicates failure.	vc-forces-numerical-derivative	consistency	Forces computed by the model agree with numerical derivatives of the energy; see full description.	Results	Files
F The model is C^-1 continuous. This means that the model has discontinuous energy.	vc-dimer-continuity-c1	informational	The energy versus separation relation of a pair of atoms is C1 continuous (i.e. the function and its first derivative are continuous); see full description.	Results	Files
P Model energy and forces are invariant with respect to rigid-body motion (translation and rotation) for all configurations the model was able to compute.	vc-objectivity	informational	Total energy is unchanged and forces transform correctly under rigid-body translation and rotation; see full description.	Results	Files
P Model energy has inversion symmetry for all configurations the model was able to compute.	vc-inversion-symmetry	informational	Total energy is unchanged and forces change sign when inverting a configuration through the origin; see full description.	Results	Files
N/A Unable to perform verification check due to an error.	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
F One or more threads gave different results than a single thread calculation. The model is not 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
N/A Unable to perform verification check due to an error.	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	2079
Cohesive energy versus lattice constant curve for diamond Fe v004	view	2534
Cohesive energy versus lattice constant curve for fcc Fe v004	view	3429
Cohesive energy versus lattice constant curve for sc Fe v004	view	1850

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	1695
Elastic constants for diamond Fe at zero temperature v001	view	3199
Elastic constants for fcc Fe at zero temperature v006	view	1759
Elastic constants for sc Fe at zero temperature v006	view	2079

ElasticConstantsHexagonal__TD_612503193866_004

Elastic constants for hexagonal crystals at zero temperature v004

Creators: Junhao Li
Contributor: jl2922
Publication Year: 2019
DOI: https://doi.org/10.25950/d794c746

Computes the elastic constants for hcp crystals 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	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Elastic constants for hcp Fe at zero temperature v004		view	1178

EquilibriumCrystalStructure__TD_457028483760_003

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

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

Computes the equilibrium crystal structure and energy for an arbitrary crystal at zero temperature and applied stress by performing symmetry-constrained relaxation. The crystal structure is specified using the AFLOW prototype designation. Multiple sets of free parameters corresponding to the crystal prototype may be specified as initial guesses for structure optimization. No guarantee is made regarding the stability of computed equilibria, nor that any are the ground state.

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_cF4_225_a v003	view	370940
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_cI2_229_a v003	view	139626
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_hP2_194_c v003	view	144913
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_tP28_136_f2ij v003	view	584032

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	4824935
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in bcc Fe v001	view	11713248
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in bcc Fe v001	view	5539141
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in bcc Fe v001	view	14253831
Relaxed energy as a function of tilt angle for a 100 symmetric tilt grain boundary in fcc Fe v001	view	13340022
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Fe v001	view	93924583
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Fe v001	view	73256737
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Fe v001	view	206570257

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	1919
Equilibrium zero-temperature lattice constant for diamond Fe v007	view	2879
Equilibrium zero-temperature lattice constant for fcc Fe v007	view	3071
Equilibrium zero-temperature lattice constant for sc Fe v007	view	1951

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	21235

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	458860

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	12188

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	255021

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	3082490

Errors

EquilibriumCrystalStructure__TD_457028483760_003

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_tP1_123_a v003	other	view

No Driver

Verification Check	Error Categories	Link to Error page
MemoryLeak__VC_561022993723_004	other	view
PeriodicitySupport__VC_895061507745_004	other	view

Files

CMakeLists.txt
ChiesaDerletDudarev_2011_Fe.params
LICENSE.CDDL
README
kimprovenance.edn
kimspec.edn

Download

EAM_Magnetic2GQuintic_ChiesaDerletDudarev_2011_Fe__MO_140444321607_002.txz	Tar+XZ	Linux and OS X archive
EAM_Magnetic2GQuintic_ChiesaDerletDudarev_2011_Fe__MO_140444321607_002.zip	Zip	Windows archive

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This Model requires a Model Driver. Archives for the Model Driver EAM_Magnetic2GQuintic__MD_543355979582_002 appear below.

EAM_Magnetic2GQuintic__MD_543355979582_002.txz	Tar+XZ	Linux and OS X archive
EAM_Magnetic2GQuintic__MD_543355979582_002.zip	Zip	Windows archive

Wiki

**Data used in fitting:**

This potential, denoted "CS3-33" in the article cited below, was fitted to experimental values of the BCC ($$\alpha$$-iron) equilibrium lattice constant and second-order elastic constants, but *not* its cohesive energy.  Experimental values for the third-order elastic constants of ferromagnetic BCC $$\alpha$$-iron were also used in fitting, as well as as ab-initio data for the relaxed formation energies of vacancy and single self-interstitials: <100>, <111>, and <110> dumbbell interstitials, octahedral and tetrahedral site interstitials, and the <111> crowdion interstitial.  Finally, a DFT-derived nearest-neighbor string potential curve (obtained by "...continually displacing a [111] string of atoms in the [111] direction without relaxing the surrounding lattice...") is used for fitting.

In addition to the above properties of ferromagnetic $$\alpha$$-iron, DFT values of the bulk equilibrium properties of non-magnetic $$\alpha$$-iron are included in the fitting database.  Finally, the average cohesive energy per atom in the ferromagnetic FCC ($$\gamma$$-iron) phase was required to be greater than that of the BCC phase during fitting.

**Cutoffs:**
Both the pair potential and the density function of this Finnis-Sinclair-type Model have a cutoff of 4.0 Angstroms. This means that the effective range for *atomic forces* is 8.0 Angstroms.  In practical terms, the pair potential decays to an absolute value of less than 0.01 eV at 3.48 Angstroms and the density decays to an absolute value of 0.01 at 3.403 Angstroms, yielding an effective force cutoff of 6.883 Angstroms.

EAM_Magnetic2GQuintic_ChiesaDerletDudarev_2011_Fe__MO_140444321607_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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Wiki