MEAM Potential for the Fe-P system developed by Ko, Kim, and Lee (2012) v002

Won-Seok Ko; Nack J. Kim; Byeong-Joo Lee

doi:10.25950/b3425ab9

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MEAM_LAMMPS_KoJimLee_2012_FeP__MO_179420363944_002

Interatomic potential for Iron (Fe), Phosphorus (P).
Use this Potential

Title A single sentence description.	MEAM Potential for the Fe-P system developed by Ko, Kim, and Lee (2012) 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.	The second-nearest-neighbor modified embedded-atom method (2NN MEAM) is employed to reproduce Fe–P binary system describing various physical properties of intermetallic compounds, bcc and liquid alloys, and also the segregation tendency of phosphorus on grain boundaries of bcc iron, in good agreement with experimental information. In the original paper (Ko et al., Journal of Physics: Condensed Matter, 24(22), 2012), the suitability of the present potential and the parameterization process for atomic scale investigations about the effects of various non-metallic impurity elements on metal properties is demonstrated.
Species The supported atomic species.	Fe, P
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	Won-Seok Ko Nack J. Kim Byeong-Joo Lee
Published on KIM	2023
How to Cite	This Model originally published in [1] is archived in OpenKIM [2-5]. [1] Ko W-S, Kim NJ, Lee B-J. Atomistic modeling of an impurity element and a metal–impurity system: pure P and Fe–P system. Journal of Physics: Condensed Matter. 2012;24(22):225002. doi:10.1088/0953-8984/24/22/225002 — (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] Ko W-S, Kim NJ, Lee B-J. MEAM Potential for the Fe-P system developed by Ko, Kim, and Lee (2012) v002. OpenKIM; 2023. doi:10.25950/b3425ab9 [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. 23 Citations (19 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 W. Ko, J. Jeon, C.-H. Lee, J.-K. Lee, and B.-J. Lee, “Intergranular embrittlement of iron by phosphorus segregation: an atomistic simulation,” Modelling and Simulation in Materials Science and Engineering. 2013. link Times cited: 14 Abstract: The intergranular embrittlement in bcc iron by the grain bou… read more Abstract: The intergranular embrittlement in bcc iron by the grain boundary (GB) segregation of phosphorus is investigated using an atomistic simulation. The inhibition of the nucleation of dislocations near the crack tip is found to be the governing mechanism of the intergranular embrittlement in phosphorus-containing iron, in contrast to the conventional reasoning that focuses on the GB decohesion. The correlation between the nucleation of dislocations and dislocation transfer across a GB (GB strengthening) is discussed. Experimental evidence and supplementary simulation results that support the new finding in terms of the GB strengthening are also demonstrated. read less S. R. Maalouf and S. Vel, “Nonlinear elastic behavior of 2D materials using molecular statics and comparisons with first principles calculations,” Physica E: Low-dimensional Systems and Nanostructures. 2023. link Times cited: 2 H. L. Mai, X. Cui, D. Scheiber, L. Romaner, and S. Ringer, “Phosphorus and transition metal co-segregation in ferritic iron grain boundaries and its effects on cohesion,” Acta Materialia. 2023. link Times cited: 2 P. Olsson, P. Hiremath, and S. Melin, “Atomistic investigation of the impact of phosphorus impurities on the tungsten grain boundary decohesion,” Computational Materials Science. 2023. link Times cited: 2 H. Lu et al., “The change of glass transition temperature under general stress state in amorphous materials,” Extreme Mechanics Letters. 2022. link Times cited: 3 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 Y. Tang et al., “Tailoring microstructure of metallic glass for delocalized plasticity by pressure annealing: Forward and inverse studies,” Acta Materialia. 2021. link Times cited: 7 P. Lejček, S. Hofmann, M. Všianská, and M. Šob, “Entropy matters in grain boundary segregation,” Acta Materialia. 2021. link Times cited: 19 S. Attarian and S. Xiao, “Development of a 2NN-MEAM potential for boron.” 2021. link Times cited: 2 Abstract: In this paper, we present the first work in developing a sec… read more Abstract: In this paper, we present the first work in developing a second nearest-neighbor modified embedded atom method (2NN-MEAM) potential function that can be used to model interatomic interactions in bo... read less C. Zhang et al., “Crystallization of the P3Sn4 Phase upon Cooling P2Sn5 Liquid by Molecular Dynamics Simulation Using a Machine Learning Interatomic Potential,” Journal of Physical Chemistry C. 2021. link Times cited: 3 Abstract: We performed molecular dynamics simulations to study the cry… read more Abstract: We performed molecular dynamics simulations to study the crystallization of the P3Sn4 phase from P2Sn5 liquid using a machine learning (ML) interatomic potential with desirable efficiency and accur... read less P. Lejček and S. Hofmann, “Entropy-dominated grain boundary segregation,” Journal of Materials Science. 2021. link Times cited: 5 P. Paranjape, P. Gopal, and S. G. Srinivasan, “First-principles study of diffusion and interactions of hydrogen with silicon, phosphorus, and sulfur impurities in nickel,” Journal of Applied Physics. 2019. link Times cited: 4 Abstract: Using density functional theory (DFT), we systematically stu… read more Abstract: Using density functional theory (DFT), we systematically study the effect of Si, P, and S impurities on the diffusion and binding of an H atom in a face-centered-cubic (FCC) Ni lattice. First, we quantify binding energies of an H atom to a vacancy, an impurity atom, and a vacancy-impurity atom defect pair. The energetics of H interactions show that a vacancy-impurity atom defect pair with larger binding energy traps the H atom more strongly and correlates with electronic bonding. Next, we study how the impurities influence diffusion of an H atom by using the Climbing Image Nudged Elastic band method to evaluate the Minimum Energy Path and the energy barrier for diffusion. The H atom preferentially diffuses between tetrahedral to octahedral (T-O) interstitial positions in pure Ni and when impurities are present. However, the activation energy significantly decreases from 0.95 eV in pure Ni to 0.47 eV, 0.52 eV, and 0.46 eV, respectively, in the presence of Si, P, and S impurities, which speeds up H diffusion. We rationalize this by comparing the bonding character of the saddle point configuration and changes in the electronic structure of Ni for each system. Notably, these analyses correlate the lower values of the activation energies to a local atomic strain in a Ni lattice. Our DFT study also validates the hypothesis of Berkowitz and Kane that P increases the H diffusion and, thereby, significantly increases H embrittlement susceptibility of Ni. We report a similar effect for Si and S impurities in Ni.Using density functional theory (DFT), we systematically study the effect of Si, P, and S impurities on the diffusion and binding of an H atom in a face-centered-cubic (FCC) Ni lattice. First, we quantify binding energies of an H atom to a vacancy, an impurity atom, and a vacancy-impurity atom defect pair. The energetics of H interactions show that a vacancy-impurity atom defect pair with larger binding energy traps the H atom more strongly and correlates with electronic bonding. Next, we study how the impurities influence diffusion of an H atom by using the Climbing Image Nudged Elastic band method to evaluate the Minimum Energy Path and the energy barrier for diffusion. The H atom preferentially diffuses between tetrahedral to octahedral (T-O) interstitial positions in pure Ni and when impurities are present. However, the activation energy significantly decreases from 0.95 eV in pure Ni to 0.47 eV, 0.52 eV, and 0.46 eV, respectively, in the presence of Si, P, and S impurities, which speeds up H diffusio... read less A. V. Verkhovykh, A. Mirzoev, and D. Mirzaev, “Interaction of Phosphorus with Impurity Atoms in BCC Iron,” Solid State Phenomena. 2018. link Times cited: 0 Abstract: The paper presents the results of modelling of phosphorus in… read more Abstract: The paper presents the results of modelling of phosphorus interaction with substitutional (Cr, Mn, P) and interstitial (C) impurity atoms in bcc iron in the framework of density functional theory using WIEN2k software. It is found that a repulsion exists of a phosphorus atom in the three first spheres of coordination of carbon, chromium and phosphorus atoms, while for manganese such repulsion of phosphorus takes place only in the second sphere. This repulsion is a consequence of an abrupt change of magnetic moment of manganese atom, so the solution energy of phosphorus almost does not change. On the contrary, chromium decreases phosphorus solubility in iron, in agreement with other data. read less P. Lejček, M. Šob, and V. Paidar, “Interfacial segregation and grain boundary embrittlement: An overview and critical assessment of experimental data and calculated results,” Progress in Materials Science. 2017. link Times cited: 146 B. Liu, H. Zhang, J. Tao, Z. R. Liu, X. Chen, and Y. Zhang, “Development of a second-nearest-neighbor modified embedded atom method potential for silicon–phosphorus binary system,” Computational Materials Science. 2016. link Times cited: 8 K.-M. Kim et al., “100 texture evolution in bcc Fe sheets - Computational design and experiments,” Acta Materialia. 2016. link Times cited: 21 W. Ko, J. Park, J. Byun, L. Jaekon, N. Kim, and B.-J. Lee, “Manipulation of surface energy anisotropy in iron using surface segregation of phosphorus: An atomistic simulation,” Scripta Materialia. 2013. link Times cited: 14 H. Bhadeshia, “Chapter 11 – The Embrittlement and Fracture of Steels.” 2017. link Times cited: 3 A. Markidonov, D. Lubyanoi, V. Kovalenko, and M. Starostenkov, “Calculation of the Thermodynamic Characteristics of Fe–P System by the Molecular Dynamics Method,” Steel in Translation. 2019. link Times cited: 0 A. Mirzoev, Y. M. Ridnyi, and A. V. Verkhovykh, “Ab initio Computer Simulation of the Energy Parameters and the Magnetic Effects in Ternary Fe–X–C (X = Si, P, S, Cr, Mn) Systems,” Russian Metallurgy (Metally). 2019. link Times cited: 4 P. Lejček, M. Všianská, and M. Šob, “Recent trends and open questions in grain boundary segregation,” Journal of Materials Research. 2018. link Times cited: 44 Abstract: Recently, significant progress in the field of grain boundar… read more Abstract: Recently, significant progress in the field of grain boundary segregation was achieved, for example, in better understanding and modeling the stabilization of nanocrystalline structures by grain boundary segregation, searching for more advanced approaches to theoretical calculation of segregation energies and development of the complexion approach. Nevertheless, with each progress, new important questions appear which need to be solved. Here, we focus on two basic questions appearing recently: How can be the experimental results on the grain boundary segregation compared reliably to their theoretical counterparts? Is the preferred segregation site of a solute in the grain boundary core substitutional or interstitial? We also show that the entropy of grain boundary segregation is a very important quantity which cannot be neglected in thermodynamic considerations as it plays a crucial role, for example, in prediction of thermodynamic characteristics of grain boundary segregation and in the preference of the segregation site at the boundary. read less H. Bhadeshia and D. Suh, “Is low phosphorus content in steel a product requirement?,” Ironmaking & Steelmaking. 2015. link Times cited: 17 Abstract: An attempt is made, on the basis to published literature, to… read more Abstract: An attempt is made, on the basis to published literature, to assess the amount of phosphorus that might be present in the steels without making it susceptible to grain boundary embrittlement. Embrittlement occurs when the general resistance to plastic flow is comparable to the stress required to separate crystals at their boundaries. A criterion is developed that enables a simple assessment to be made of the tendency to embrittle as a function of yield strength and the fraction of grain boundary sites that are covered by phosphorus. The latter is also sensitive to chemical composition, since some elements such as carbon segregate preferentially to phosphorus, giving rise to site competition that can permit a greater tolerance to the impurity. Other solutes affect the embrittling potency by different mechanisms, not all of which are clear. read less
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_179420363944_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_KoJimLee_2012_FeP__MO_179420363944_002
DOI	10.25950/b3425ab9 https://doi.org/10.25950/b3425ab9 https://commons.datacite.org/doi.org/10.25950/b3425ab9
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_KoJimLee_2012_FeP__MO_179420363944_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 4.88694e-09 compared with a machine precision of 2.22045e-16. The letter grade was based on 'score=log10(error/eps)', with ranges A=[0, 7.5], B=(7.5, 10.0], C=(10.0, 12.5], D=(12.5, 15.0), F>15.0. 'A' is the best grade, and 'F' indicates failure.	vc-forces-numerical-derivative	consistency	Forces computed by the model agree with numerical derivatives of the energy; see full description.	Results	Files
F The model is C^0 continuous. This means that the model has continuous energy, but a discontinuous first derivative.	vc-dimer-continuity-c1	informational	The energy versus separation relation of a pair of atoms is C1 continuous (i.e. the function and its first derivative are continuous); see full description.	Results	Files
P Model energy and forces are invariant with respect to rigid-body motion (translation and rotation) for all configurations the model was able to compute.	vc-objectivity	informational	Total energy is unchanged and forces transform correctly under rigid-body translation and rotation; see full description.	Results	Files
P Model energy has inversion symmetry for all configurations the model was able to compute.	vc-inversion-symmetry	informational	Total energy is unchanged and forces change sign when inverting a configuration through the origin; see full description.	Results	Files
P No memory leak detected.	vc-memory-leak	informational	The model code does not have memory leaks (i.e. it releases all allocated memory at the end); see full description.	Results	Files
P All threads give identical results for tested case. Model appears to be thread-safe.	vc-thread-safe	mandatory	The model returns the same energy and forces when computed in serial and when using parallel threads for a set of configurations. Note that this is not a guarantee of thread safety; see full description.	Results	Files
P Unit conversion successful	vc-unit-conversion	mandatory	The model is able to correctly convert its energy and/or forces to different unit sets; see full description.	Results	Files

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

Species: P

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

Species: P

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: P

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

Species: P

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: P

Species: Fe

Cubic Crystal Basic Properties Table

Species: Fe

Species: P

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	10454
Cohesive energy versus lattice constant curve for bcc P v004	view	10215
Cohesive energy versus lattice constant curve for diamond Fe v004	view	11117
Cohesive energy versus lattice constant curve for diamond P v004	view	9807
Cohesive energy versus lattice constant curve for fcc Fe v004	view	11264
Cohesive energy versus lattice constant curve for fcc P v004	view	10749
Cohesive energy versus lattice constant curve for sc Fe v004	view	10969
Cohesive energy versus lattice constant curve for sc P v004	view	8882

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	44835
Elastic constants for fcc Fe at zero temperature v006	view	50565
Elastic constants for sc Fe at zero temperature v006	view	33203

EquilibriumCrystalStructure__TD_457028483760_001

Equilibrium structure and energy for a crystal structure at zero temperature and pressure v001

Creators:
Contributor: ilia
Publication Year: 2023
DOI: https://doi.org/10.25950/e8a7ed84

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	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 crystal structure and energy for P in AFLOW crystal prototype A_mC16_12_2ij v001		view	113007

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 FeP in AFLOW crystal prototype A2B_hP9_189_fg_ad v002	view	56628
Equilibrium crystal structure and energy for FeP in AFLOW crystal prototype A3B_tI32_82_3g_g v002	view	97884
Equilibrium crystal structure and energy for P in AFLOW crystal prototype A_aP24_2_12i v002	view	179667
Equilibrium crystal structure and energy for P in AFLOW crystal prototype A_cP1_221_a v002	view	84148
Equilibrium crystal structure and energy for P in AFLOW crystal prototype A_oC8_64_f v002	view	99903
Equilibrium crystal structure and energy for P in AFLOW crystal prototype A_tI4_139_e v002	view	80614
Equilibrium crystal structure and energy for FeP in AFLOW crystal prototype AB2_oP6_58_a_g v002	view	47271
Equilibrium crystal structure and energy for FeP in AFLOW crystal prototype AB4_mC40_15_ae_4f v002	view	233524
Equilibrium crystal structure and energy for FeP in AFLOW crystal prototype AB4_mP30_14_ae_6e v002	view	119393
Equilibrium crystal structure and energy for FeP in AFLOW crystal prototype AB4_oC20_20_a_2c v002	view	94381
Equilibrium crystal structure and energy for FeP in AFLOW crystal prototype AB_oP8_62_c_c v002	view	150746

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	474496
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_cI2_229_a v003	view	157429
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_hP2_194_c v003	view	178637
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_tP28_136_f2ij v003	view	450839

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	27711674
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in bcc Fe v001	view	47467762
Relaxed energy as a function of tilt angle for a 100 symmetric tilt grain boundary in fcc Fe v001	view	32693666

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	23841
Equilibrium zero-temperature lattice constant for bcc P v007	view	24507
Equilibrium zero-temperature lattice constant for diamond Fe v007	view	24358
Equilibrium zero-temperature lattice constant for diamond P v007	view	26871
Equilibrium zero-temperature lattice constant for fcc Fe v007	view	25694
Equilibrium zero-temperature lattice constant for fcc P v007	view	23383
Equilibrium zero-temperature lattice constant for sc Fe v007	view	24442
Equilibrium zero-temperature lattice constant for sc P v007	view	24810

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	221468
Equilibrium lattice constants for hcp P v005		view	214953

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	5013429

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	94427

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	743714

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	760058

Errors

ElasticConstantsCubic__TD_011862047401_006

Test	Error Categories	Link to Error page
Elastic constants for bcc P at zero temperature v006	other	view
Elastic constants for diamond Fe at zero temperature v001	other	view
Elastic constants for diamond P at zero temperature v001	other	view
Elastic constants for fcc P at zero temperature v006	other	view
Elastic constants for sc P 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 P at zero temperature v004	other	view

EquilibriumCrystalStructure__TD_457028483760_000

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_cF4_225_a v000	other	view
Equilibrium crystal structure and energy for P in AFLOW crystal prototype A_oC8_64_f v000	other	view
Equilibrium crystal structure and energy for Fe in AFLOW crystal prototype A_tP28_136_f2ij v000	other	view

EquilibriumCrystalStructure__TD_457028483760_002

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for FeP in AFLOW crystal prototype A2B_oC18_38_abde_ae v002	other	view
Equilibrium crystal structure and energy for FeP in AFLOW crystal prototype A4B_tP5_123_ace_b v002	other	view
Equilibrium crystal structure and energy for P in AFLOW crystal prototype A_hR2_166_c v002	other	view
Equilibrium crystal structure and energy for P in AFLOW crystal prototype A_mC16_12_2ij v002	other	view
Equilibrium crystal structure and energy for P in AFLOW crystal prototype A_oI4_74_e v002	other	view

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

GrainBoundaryCubicCrystalSymmetricTiltRelaxedEnergyVsAngle__TD_410381120771_003

Test	Error Categories	Link to Error page
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in bcc Fe v001	other	view
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in bcc Fe v001	other	view
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Fe v001	other	view
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Fe v001	other	view
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Fe v001	other	view

LinearThermalExpansionCoeffCubic__TD_522633393614_001

Test	Error Categories	Link to Error page
Linear thermal expansion coefficient of bcc Fe at 293.15 K under a pressure of 0 MPa v001	other	view

SurfaceEnergyCubicCrystalBrokenBondFit__TD_955413365818_004

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

Files

CMakeLists.txt
FeP.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_KoJimLee_2012_FeP__MO_179420363944_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

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Errors

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