EAM potential (LAMMPS cubic hermite tabulation) for Pd-Ag-H ternary alloy system developed by Hale et al. (2013) (Morse Pd-Ag interactions) v005

Lucas Hale; Bryan M. Wong; Jonathan A. Zimmerman; Xiaowang Zhou

doi:10.25950/ebe6d53c

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EAM_Dynamo_HaleWongZimmerman_2008PairMorse_PdAgH__MO_108983864770_005

Interatomic potential for Hydrogen (H), Palladium (Pd), Silver (Ag).
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Title A single sentence description.	EAM potential (LAMMPS cubic hermite tabulation) for Pd-Ag-H ternary alloy system developed by Hale et al. (2013) (Morse Pd-Ag interactions) v005
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.	EAM alloy potential developed by Hale et al. (2013) to accurately reproduce properties of the Pd-Ag-H alloy system (Morse F2 Pd-Ag pair function).
Species The supported atomic species.	Ag, H, Pd
Disclaimer A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.	Potential developed for the Pd-Ag-H system, where Ag is substitutional for Pd, and H is interstitial. Application of this potential to pure H, or other Pd-Ag-H compounds is not recommended.

Contributor	Ryan S. Elliott
Maintainer	Ryan S. Elliott
Developer	Lucas Hale Bryan M. Wong Jonathan A. Zimmerman Xiaowang Zhou
Published on KIM	2018
How to Cite	This Model originally published in [1-2] is archived in OpenKIM [3-6]. [1] Hale LM, Wong BM, Zimmerman JA, Zhou XW. Atomistic potentials for palladium–silver hydrides. Modelling and Simulation in Materials Science and Engineering. 2013;21(4):045005. doi:10.1088/0965-0393/21/4/045005 — (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] Zhou XW, Zimmerman JA, Wong BM, Hoyt JJ. An embedded-atom method interatomic potential for Pd–H alloys. Journal of Materials Research. 2008;23(3):704–18. doi:10.1557/JMR.2008.0090 [3] Hale L, Wong BM, Zimmerman JA, Zhou X. EAM potential (LAMMPS cubic hermite tabulation) for Pd-Ag-H ternary alloy system developed by Hale et al. (2013) (Morse Pd-Ag interactions) v005. OpenKIM; 2018. doi:10.25950/ebe6d53c [4] Foiles SM, Baskes MI, Daw MS, Plimpton SJ. EAM Model Driver for tabulated potentials with cubic Hermite spline interpolation as used in LAMMPS v005. OpenKIM; 2018. doi:10.25950/68defa36 [5] 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 [6] 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. 26 Citations (17 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 . C. Liu et al., “Size-dependent methanol oxidation behavior of Pd-Ag synthesized by the high-temperature shock method,” Science China Materials. 2023. link Times cited: 0 N. Nakamura, K. Matsuura, A. Ishii, and H. Ogi, “Restructuring in bimetallic core-shell nanoparticles: Real-time observation,” Physical Review B. 2022. link Times cited: 0 Abstract: The formation process of core–shell bimetallic nanoparticles… read more Abstract: The formation process of core–shell bimetallic nanoparticles synthesized by sputtering onto a substrate is observed in real time using an originally developed acoustic technique. The technique enables us to evaluate the structural change of nanoparticles at room temperature without contacting the nanoparticles or substrate. In the experiments, the sputtering of metal A followed by metal B tended to form B-shell/A-core nanoparticles. However, in Pd–Au alloy system, notable restructuring occurred during synthesis, resulting in the formation of A-shell/B-core nanoparticles. The formation process is analyzed using the molecular dynamics simulation, revealing that this restructuring occurs on a short timescale, and high diffusivity of Au plays an important role. read less M. Ghosh and S. Das, “Molecular dynamics and Brownian dynamics-based studies on interfacial heat conduction from a heat source to a nanofluid for estimating the enhancement in thermal conductivity of the nanofluid,” Applied Physics A. 2020. link Times cited: 1 A. M. Igoshkin, “Molecular Dynamics Study of the Deposition of Palladium-Silver Films on a Silver Substrate,” Journal of Structural Chemistry. 2019. link Times cited: 0 J. Lim, N. Molinari, K. Duanmu, P. Sautet, and B. Kozinsky, “Automated Detection and Characterization of Surface Restructuring Events in Bimetallic Catalysts,” The Journal of Physical Chemistry C. 2019. link Times cited: 9 Abstract: Surface restructuring in bimetallic systems has recently bee… read more Abstract: Surface restructuring in bimetallic systems has recently been shown to play a crucial role in heterogeneous catalysis. In particular, the segregation in binary alloys can be reversed in the presence of strongly bound adsorbates. Mechanistic characterization of such restructuring phenomena at the atomic level remains scarce and challenging due to the large configurational space that must be explored. To this end, we propose an automated method to discover elementary surface restructuring processes in an unbiased fashion, using Pd/Ag as an example. We employ high-temperature classical molecular dynamics (MD) to rapidly detect restructuring events, isolate them, and optimize using density functional theory (DFT). In addition to confirming the known exchange descent mechanism, our systematic approach has revealed three new predominant classes of events at step edges of close-packed surfaces that have not been considered before: (1) vacancy insertion; (2) direct exchange; (3) interlayer exchange. The discovered events enable us to construct the complete set of mechanistic pathways by which Pd is incorporated into the Ag host in vacuum. These atomistic insights provide a step toward systematic understanding and engineering of surface segregation dynamics in bimetallic catalysts. read less A. Leonardi and M. Engel, “Particle Shape Control via Etching of Core@Shell Nanocrystals.,” ACS nano. 2018. link Times cited: 9 Abstract: The application of nanocrystals as heterogeneous catalysts a… read more Abstract: The application of nanocrystals as heterogeneous catalysts and plasmonic nanoparticles requires fine control of their shape and chemical composition. A promising idea to achieve synergistic effects is to combine two distinct chemical and/or physical functionalities in bimetallic core@shell nanocrystals. Although techniques for the synthesis of single-component nanocrystals with spherical or anisotropic shape are well-established, new methods are sought to tailor multicomponent nanocrystals. Here, we probe etching in a controlled redox environment as a synthesis technique for multicomponent nanocrystals. Our Monte Carlo computer simulations demonstrate the appearance of characteristic non-equilibrium intermediate microstructures that are further thermodynamically tested and analyzed with molecular dynamics. Convex platelet, concave polyhedron, pod, cage, and strutted-cage shapes are obtained at room temperature with fully coherent structure exposing crystallographic facets and chemical elements along distinct particle crystallographic directions. We observe that structural and dynamic properties are markedly modified compared to the untreated compact nanocrystal. read less N. Nakamura, K. Matsuura, and A. Ishii, “In situ observation of morphological change of Pd-based bimetallic nanoparticles synthesized by co-sputtering,” Journal of Applied Physics. 2023. link Times cited: 0 Abstract: The formation process of Pd-based bimetallic nanoparticles s… read more Abstract: The formation process of Pd-based bimetallic nanoparticles synthesized by co-sputtering is investigated by performing in situ morphological observation using resistive spectroscopy. The segregation of the metal with lower surface energy on the nanoparticle surface is observed, and it is found that the formation process of the alloy nanoparticles tends to be similar to that of the nanoparticles composed of the core metal even when the atomic fraction of the shell metal is higher than that of the core metal. The co-sputtering process is simulated by the molecular dynamics analysis, and the observed formation process is theoretically confirmed. read less J. Wang et al., “Lattice Strain and Surface Activity of Dislocation‐Distorted AgPd Nanoalloys Under Preoxidation and Catalysis Condition,” Small Structures. 2023. link Times cited: 0 Abstract: Although line defects endow excellent catalytic performance … read more Abstract: Although line defects endow excellent catalytic performance by undercoordinated sites with compressive tensile strain, few studies have systematically unraveled the relationship between dislocation, strain, and electrochemical activity for formate oxidation reactions (FOR). Herein, a novel approach for synthesizing defect‐rich nanomaterials at room temperature is proposed for the first time. The heated and dealloyed AgPd nanoparticles (hd‐AgPd NPs) substantially improve the intrinsic electrocatalytic activity by introducing compressive strain to tune its electronic structure. Electrochemical experiments show that the mass activity of hd‐AgPd NPs for FOR is 5.3 times higher than that of pure Pd nanoparticle catalysts. Following a 3600 s chronoamperometric process, a portion of the dislocation vanishes, but the strain persists on the AgPd (111) facet. The mechanisms for activity enhancement are further explored through density functional theory and molecular dynamics calculations, which show that compressive strain effectively alters its electronic structure and decreases the energy of the rate‐determining step during the reaction, significantly enhancing the FOR performance and stability. The results of electrochemical performance and physical characterization show that lattice strain has a more significant impact on FOR performance than alloying and preoxidation. This study presents a new approach to produce high‐performance catalysts by inducing strain into nanoparticles. read less L. Guo et al., “Structural transformations in single-crystalline AgPd nanoalloys from multiscale deep potential molecular dynamics.,” The Journal of chemical physics. 2023. link Times cited: 1 Abstract: AgPd nanoalloys often undergo structural evolution during ca… read more Abstract: AgPd nanoalloys often undergo structural evolution during catalytic reactions; the mechanism underlying such restructuring remains largely unknown due to the use of oversimplified interatomic potentials in simulations. Herein, a deep-learning potential is developed for AgPd nanoalloys based on a multiscale dataset spanning from nanoclusters to bulk configurations, exhibits precise predictions of mechanical properties and formation energies with near-density functional theory accuracy, calculates the surface energies closer to experimental values compared to those obtained by Gupta potentials, and is applied to investigate the shape reconstruction of single-crystalline AgPd nanoalloys from cuboctahedron (Oh) to icosahedron (Ih) geometries. The Oh to Ih shape restructuring is thermodynamically favorable and occurs at 11 and 92 ps for Pd55@Ag254 and Ag147@Pd162 nanoalloys, respectively. During the shape reconstruction of Pd@Ag nanoalloys, concurrent surface restructuring of the (100) facet and internal multi-twinned phase change are observed with collaborative displacive characters. The presence of vacancies can influence the final product and reconstructing rate of Pd@Ag core-shell nanoalloys. The Ag outward diffusion on Ag@Pd nanoalloys is more pronounced in Ih geometry compared to Oh geometry and can be further accelerated by the Oh to Ih deformation. The deformation of single-crystalline Pd@Ag nanoalloys is characterized by a displacive transformation involving the collaborative displacement of a large number of atoms, distinguishing it from the diffusion-coupled transformation of Ag@Pd nanoalloys. read less Q. Tang et al., “Stable Strain State of Single‐Twinned AgPdF Nanoalloys under Formate Oxidation Reaction,” Small Structures. 2023. link Times cited: 0 Abstract: Surface reconstruction as common phenomenon during catalysis… read more Abstract: Surface reconstruction as common phenomenon during catalysis complicates the prediction and modeling on catalytic activity of the nanoalloy, hence developing a stable structure to be resistant to surface restructuring would provide an ideal prototype for substantial and reliable mechanism analysis. Herein, the single‐twinned structure in inverse AgPdF catalyst is constructed to enhance the catalytic activity and stability for the formate oxidation reaction (FOR). The single‐twinned AgPdF nanoalloy (t‐AgPdF) catalyst exhibits an enhanced peak current density of 4.6 A mgPd−1, a reduced onset potential of 0.44 V, a higher activity retention of 55.7% after 600 cycles, and a longer activity retention time of 55.9 h. Additionally, the t‐AgPdF catalyst presents a higher hydrogen generation rate of 1.11 mL mgPd−1 than that of single‐crystalline AgPd nanoalloy (AgPd) catalyst, and density functional theory calculations reveal that t‐AgPdF(111) surface exhibits a reduced activation energy of 0.59 eV for formate decomposition reaction. Impressively, the t‐AgPdF maintains compressive and tensile strain state along the Σ3 twin boundaries before and after the FOR, in contrast to AgPd. This is the first time to reveal that the nanotwinned structures contribute inverse t‐AgPdF catalysts the catalytic active sites with stable strain state since starting reaction for the FOR. read less D. Angell, B. B. Bourgeois, M. Vadai, and J. A. Dionne, “Lattice-Resolution, Dynamic Imaging of Hydrogen Absorption into Bimetallic AgPd Nanoparticles.,” ACS nano. 2022. link Times cited: 2 Abstract: Palladium's strong reactivity and absorption affinity t… read more Abstract: Palladium's strong reactivity and absorption affinity to H2 makes it a prime material for hydrogen-based technologies. Alloying of Pd has been used to tune its mechanical stability, catalytic activity, and absorption thermodynamics. However, atomistic mechanisms of hydrogen dissociation and intercalation are informed predominantly by theoretical calculations, owing to the difficulty in imaging dynamic metal-gas interactions at the atomic scale. Here, we use in situ environmental high resolution transmission electron microscopy to directly track the hydrogenation-induced lattice expansion within AgPd triangular nanoprisms. We investigate the thermodynamics of the system at the single particle level and show that, contrary to pure Pd nanoparticles, the AgPd system exhibits α/β coexistence within single crystalline nanoparticles in equilibrium; the nanoparticle system also moves to a solid-solution loading mechanism at lower Ag content than bulk. By tracking the lattice expansion in real time during a phase transition, we see surface-limited β phase growth, as well as rapid reorientation of the α/β interface within individual particles. This secondary rate corresponds to the speed with which the β phase can restructure and, according to our atomistic calculations, emerges from lattice strain minimization. We also observe no preferential nucleation at the sharpest nanoprism corners, contrary to classical nucleation theory. Our results achieve atomic lattice plane resolution─crucial for exploring the role of crystal defects and single atom sites on catalytic hydrogen splitting and absorption. read less H. N. Pishkenari, F. S. Yousefi, and A. Taghibakhshi, “Determination of surface properties and elastic constants of FCC metals: a comparison among different EAM potentials in thin film and bulk scale,” Materials Research Express. 2018. link Times cited: 22 Abstract: Three independent elastic constants C11, C12, and C44 were c… read more Abstract: Three independent elastic constants C11, C12, and C44 were calculated and compared using available potentials of eight different metals with FCC crystal structure; Gold, Silver, Copper, Nickel, Platinum, Palladium, Aluminum and Lead. In order to calculate the elastic constants, the second derivative of the energy density of each system was calculated with respect to different directions of strains. Each set of the elastic constants of the metals in bulk scale was compared with experimental results, and the average relative error was for each was calculated and compared with other available potentials. Then, using the Voigt-Reuss-Hill method, approximated values for Young and shear moduli and Poisson’s ratio of the FCC metals in the bulk scale were found for each potential. Furthermore, to observe the surface effects on the metals in nanoscale, surface elastic constants of the thin films of the metals have been calculated. In the study of the thin films of materials in nanoscale, the number of surface atoms is considerable compared to all atoms of the object. This leads to an increase in the surface effects, which influence the elastic properties. By considering this fact and employing related definitions and equations, the properties of the thin films of the metals were calculated, and the surface effects for different crystallographic directions were compared. Subsequently, in some cases, comparisons among characteristics of the metals in the thin film and bulk material were made. read less C. Pan et al., “Study on optical films with AgNWs using UV laser patterning,” Optical Materials. 2018. link Times cited: 8 X. Y. Chen et al., “Effect of dynamic evolution of misfit dislocation pattern on dislocation nucleation and shear sliding at semi-coherent bimetal interfaces,” Acta Materialia. 2018. link Times cited: 43 K. Liu, R. Zhang, I. Beyerlein, X. Y. Chen, H. Yang, and T. Germann, “Cooperative dissociations of misfit dislocations at bimetal interfaces,” APL Materials. 2016. link Times cited: 18 Abstract: Using atomistic simulations, several semi-coherent cube-on-c… read more Abstract: Using atomistic simulations, several semi-coherent cube-on-cube bimetal interfaces are comparatively investigated to unravel the combined effect of the character of misfit dislocations, the stacking fault energy difference between bimetal pairs, and their lattice mismatch on the dissociation of interfacial misfit dislocations. Different dissociation paths and features under loadings provide several unique deformation mechanisms that are critical for understanding interface strengthening. In particular, applied strains can cause either the formation of global interface coherency by the migration of misfit dislocations from an interface to an adjoining crystal interior or to an alternate packing of stacking faults connected by stair-rod dislocations. read less A. G. Pourkermani, B. Azizi, and H. N. Pishkenari, “Vibrational analysis of Ag, Cu and Ni nanobeams using a hybrid continuum-atomistic model,” International Journal of Mechanical Sciences. 2020. link Times cited: 9 K. Nishimura and K. Miyake, “Molecular Dynamics Study on Hydrogen Diffusion in Pd and Pd-Ag Alloys,” Journal of The Society of Materials Science, Japan. 2018. link Times cited: 0 Abstract: Hydrogen diffusion in Pd with various H concentrations and P… read more Abstract: Hydrogen diffusion in Pd with various H concentrations and Pd-Ag alloys with various Ag and H concentrations is investigated using molecular dynamics simulations. At H concentration of 0.5 in Pd, the miscibility gap caused by the spinodal decomposition is observed. The diffusion coefficient of H in Pd is kept constant at H concentration less than 0.1, then increases with increasing H concentration until the phase transition occurs, and after reaching a maximum it decreases with increasing H concentration. The simulations of varying a temperature predict the activation energy for H diffusion of 0.163 eV at H concentration of 0.05, which agrees well with that reported in the literature, and minimum activation energy of 0.144 eV at H concentration of 0.5. Moreover, our results indicate that the addition of Ag to Pd leads to the dissipation of the miscibility gap. The diffusion coefficient of H in Pd-Ag alloys significantly decreases with increasing Ag concentration. The minimum activation energy for H diffusion in Pd-Ag alloys is estimated to be 0.135 eV when Ag and H concentration are 0.1 and 0.5, respectively. read less B. Yao, Z. R. Liu, D. Legut, and R. F. Zhang, “Hybrid potential model with high feasibility and flexibility for metallic and covalent solids,” Physical Review B. 2023. link Times cited: 0 B. Yao, Z. R. Liu, and R. F. Zhang, “EAPOTc: An integrated empirical interatomic potential optimization platform for compound solids,” Computational Materials Science. 2022. link Times cited: 1 I. Hijazi, Y. Zhang, and R. Fuller, “A Simple Palladium Hydride Embedded Atom Method Potential for Hydrogen Energy Applications,” Journal of Energy Resources Technology. 2019. link Times cited: 3 Abstract: When hydrogen is produced from a biomass or coal gasifier, i… read more Abstract: When hydrogen is produced from a biomass or coal gasifier, it is necessary to purify it from syngas streams containing components such as CO, CO2, N2, CH4, and other products. Therefore, a challenge related to hydrogen purification is the development of hydrogen-selective membranes that can operate at elevated temperatures and pressures, provide high fluxes, long operational lifetime, and resistance to poisoning while still maintaining reasonable cost. Palladium-based membranes have been shown to be well suited for these types of high-temperature applications and have been widely utilized for hydrogen separation. Palladium's unique ability to absorb a large quantity of hydrogen can also be applied in various clean energy technologies, like hydrogen fuel cells. In this paper, a fully analytical interatomic embedded atom method (EAM) potential for the Pd-H system has been developed, that is easily extendable to ternary Palladium-based hydride systems, such as Pd-Cu-H and Pd-Ag-H. The new potential has fewer fitting parameters than previously developed EAM Pd-H potentials and is able to accurately predict the cohesive energy, lattice constant, bulk modulus, elastic constants, melting temperature, and the stable Pd-H structures in molecular dynamics (MD) simulations with various hydrogen concentrations. The EAM potential also well predicts the miscibility gap, the segregation of the palladium hydride system into dilute (α), and concentrated (β) phases. read less N. V. Ilawe, J. Zimmerman, and B. M. Wong, “Breaking Badly: DFT-D2 Gives Sizeable Errors for Tensile Strengths in Palladium-Hydride Solids.,” Journal of chemical theory and computation. 2015. link Times cited: 72 Abstract: Dispersion interactions play a crucial role in noncovalently… read more Abstract: Dispersion interactions play a crucial role in noncovalently bound molecular systems, and recent studies have shown that dispersion effects are also critical for accurately describing covalently bound solids. While most studies on bulk solids have solely focused on equilibrium properties (lattice constants, bulk moduli, and cohesive energies), there has been little work on assessing the importance of dispersion effects for solid-state properties far from equilibrium. In this work, we present a detailed analysis of both equilibrium and highly nonequilibrium properties (tensile strengths leading to fracture) of various palladium-hydride systems using representative DFT methods within the LDA, GGA, DFT-D2, DFT-D3, and nonlocal vdw-DFT families. Among the various DFT methods, we surprisingly find that the empirically constructed DFT-D2 functional gives extremely anomalous and qualitatively incorrect results for tensile strengths in palladium-hydride bulk solids. We present a detailed analysis of these effects and discuss the ramifications of using these methods for predicting solid-state properties far from equilibrium. Most importantly, we suggest caution in using DFT-D2 (or other coarse-grained parametrizations obtained from DFT-D2) for computing material properties under large stress/strain loads or for evaluating solid-state properties under extreme structural conditions. read less N. V. Ilawe, M. Groulx, and B. M. Wong, “Density Functional Theory Methods for Computing and Predicting Mechanical Properties.” 2016. link Times cited: 0 M. Wagih and C. Schuh, “The spectrum of interstitial solute energies in polycrystals,” Scripta Materialia. 2023. link Times cited: 2 C. Zhang, R. Fuller, and I. Hijazi, “Quaternary Hydrides Pd1-y-zAgyCuzHx Embedded Atom Method Potentials for Hydrogen Energy Applications,” Journal of Energy and Power Technology. 2021. link Times cited: 0 Abstract: The Pd-H system has attracted extensive attention. Pd can ab… read more Abstract: The Pd-H system has attracted extensive attention. Pd can absorb considerable amount of H at room temperature, this ability is reversible, so it is suitable for multiple energy applications. Pd-Ag alloys possess higher H permeability, solubility and narrower miscibility gap with better mechanical properties than pure Pd, but sulfur poisoning remains an issue. Pd-Cu alloys have excellent resistance to sulfur and carbon monoxide poisoning and hydrogen embrittlement, good mechanical properties, and broader temperature working environments over pure Pd, but relatively lower hydrogen permeability and solubility than pure Pd and Pd-Ag alloys. This suggests that alloying Pd with Ag and Cu to create Pd-Ag-Cu ternary alloys can optimize the overall performance and substantially lowers the cost. Thus, in this paper, we provide the first embedded atom method potentials for the quaternary hydrides Pd1-y-zAgyCuzHx. The fully analytical potentials are fitted utilizing the central atom method without performing time-consuming molecular dynamics simulations. read less S. M. Rassoulinejad-Mousavi and Y. Zhang, “Interatomic Potentials Transferability for Molecular Simulations: A Comparative Study for Platinum, Gold and Silver,” Scientific Reports. 2018. link Times cited: 33 L. Hale, J. Zimmerman, and B. M. Wong, “Large-scale atomistic simulations of helium-3 bubble growth in complex palladium alloys.,” The Journal of chemical physics. 2016. link Times cited: 11 Abstract: Palladium is an attractive material for hydrogen and hydroge… read more Abstract: Palladium is an attractive material for hydrogen and hydrogen-isotope storage applications due to its properties of large storage density and high diffusion of lattice hydrogen. When considering tritium storage, the material's structural and mechanical integrity is threatened by both the embrittlement effect of hydrogen and the creation and evolution of additional crystal defects (e.g., dislocations, stacking faults) caused by the formation and growth of helium-3 bubbles. Using recently developed inter-atomic potentials for the palladium-silver-hydrogen system, we perform large-scale atomistic simulations to examine the defect-mediated mechanisms that govern helium bubble growth. Our simulations show the evolution of a distribution of material defects, and we compare the material behavior displayed with expectations from experiment and theory. We also present density functional theory calculations to characterize ideal tensile and shear strengths for these materials, which enable the understanding of how and why our developed potentials either meet or confound these expectations. read less
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_108983864770_005
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_Dynamo_HaleWongZimmerman_2008PairMorse_PdAgH__MO_108983864770_005
DOI	10.25950/ebe6d53c https://doi.org/10.25950/ebe6d53c https://commons.datacite.org/doi.org/10.25950/ebe6d53c
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_Dynamo__MD_120291908751_005
Driver	EAM_Dynamo__MD_120291908751_005
KIM API Version	2.0
Potential Type	eam

Previous Version	EAM_Dynamo_HaleWongZimmerman_2008PairMorse_PdAgH__MO_108983864770_004

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Grade	Name	Category	Brief Description	Full Results	Aux File(s)
P All elements claimed by model are supported in at least one of the tested configurations.	vc-species-supported-as-stated	mandatory	The model supports all species it claims to support; see full description.	Results	Files
P Periodic boundary conditions were correctly supported for all configurations that the model was able to compute.	vc-periodicity-support	mandatory	Periodic boundary conditions are handled correctly; see full description.	Results	Files
P Model energy has permutation symmetry for all configurations the model was able to compute.	vc-permutation-symmetry	mandatory	Total energy and forces are unchanged when swapping atoms of the same species; see full description.	Results	Files
B The letter grade B was assigned because the normalized error in the computation was 2.89243e-08 compared with a machine precision of 2.22045e-16. The letter grade was based on 'score=log10(error/eps)', with ranges A=[0, 7.5], B=(7.5, 10.0], C=(10.0, 12.5], D=(12.5, 15.0), F>15.0. 'A' is the best grade, and 'F' indicates failure.	vc-forces-numerical-derivative	consistency	Forces computed by the model agree with numerical derivatives of the energy; see full description.	Results	Files
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
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
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: H

Species: Pd

Species: Ag

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: Ag

Species: Pd

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: Pd

Species: H

Species: Ag

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: H

Species: Ag

Species: Pd

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: Pd

Species: H

Species: Ag

FCC Stacking Fault Energies

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

Species: Ag

Species: Pd

FCC Surface Energies

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

Species: Pd

Species: Ag

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: Ag

Species: Pd

Species: H

Cubic Crystal Basic Properties Table

Species: Ag

Species: H

Species: Pd

Tests

Disclaimer From Model Developer

Potential developed for the Pd-Ag-H system, where Ag is substitutional for Pd, and H is interstitial. Application of this potential to pure H, or other Pd-Ag-H compounds is not recommended.

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 Ag v004	view	5703
Cohesive energy versus lattice constant curve for bcc Pd v004	view	3859
Cohesive energy versus lattice constant curve for diamond Ag v004	view	4038
Cohesive energy versus lattice constant curve for diamond Pd v004	view	3859
Cohesive energy versus lattice constant curve for fcc Ag v004	view	4344
Cohesive energy versus lattice constant curve for fcc Pd v004	view	3491
Cohesive energy versus lattice constant curve for sc Ag v004	view	4196
Cohesive energy versus lattice constant curve for sc Pd v004	view	3959

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 Ag at zero temperature v006	view	1759
Elastic constants for bcc H at zero temperature v006	view	2303
Elastic constants for bcc Pd at zero temperature v006	view	2143
Elastic constants for fcc Ag at zero temperature v006	view	1887
Elastic constants for fcc H at zero temperature v006	view	2175
Elastic constants for fcc Pd at zero temperature v006	view	1887
Elastic constants for sc Ag at zero temperature v006	view	5758
Elastic constants for sc H at zero temperature v006	view	1727
Elastic constants for sc Pd at zero temperature v006	view	5662

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	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 Ag at zero temperature v004	view	2579
Elastic constants for hcp H at zero temperature v004	view	2069
Elastic constants for hcp Pd at zero temperature v004	view	1624

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	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 Ag in AFLOW crystal prototype A_cF4_225_a v001	view	77154
Equilibrium crystal structure and energy for Ag in AFLOW crystal prototype A_hP2_194_c v001	view	71706
Equilibrium crystal structure and energy for Ag in AFLOW crystal prototype A_hP4_194_ac v001	view	72001

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 Pd in AFLOW crystal prototype A_cF4_225_a v002	view	55656
Equilibrium crystal structure and energy for H in AFLOW crystal prototype A_cI2_229_a v002	view	56871
Equilibrium crystal structure and energy for H in AFLOW crystal prototype A_hP2_194_c v002	view	145916
Equilibrium crystal structure and energy for H in AFLOW crystal prototype A_hP4_194_f v002	view	94455
Equilibrium crystal structure and energy for HPd in AFLOW crystal prototype AB_cF8_225_a_b v002	view	62765

GrainBoundaryCubicCrystalSymmetricTiltRelaxedEnergyVsAngle__TD_410381120771_003

Relaxed energy as a function of tilt angle for a symmetric tilt grain boundary within a cubic crystal v003

Creators:
Contributor: brunnels
Publication Year: 2022
DOI: https://doi.org/10.25950/2c59c9d6

Computes grain boundary energy for a range of tilt angles given a crystal structure, tilt axis, and material.

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Relaxed energy as a function of tilt angle for a 100 symmetric tilt grain boundary in fcc Ag v000	view	7696950
Relaxed energy as a function of tilt angle for a 100 symmetric tilt grain boundary in fcc Pd v000	view	6209447
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Ag v000	view	26430201
Relaxed energy as a function of tilt angle for a 110 symmetric tilt grain boundary in fcc Pd v000	view	17343591
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Ag v000	view	15026459
Relaxed energy as a function of tilt angle for a 111 symmetric tilt grain boundary in fcc Pd v000	view	10203286
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Ag v000	view	50185917
Relaxed energy as a function of tilt angle for a 112 symmetric tilt grain boundary in fcc Pd v000	view	38824801

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 Ag v007	view	1599
Equilibrium zero-temperature lattice constant for bcc H v007	view	1919
Equilibrium zero-temperature lattice constant for bcc Pd v007	view	1823
Equilibrium zero-temperature lattice constant for diamond Ag v007	view	1791
Equilibrium zero-temperature lattice constant for diamond H v007	view	3423
Equilibrium zero-temperature lattice constant for diamond Pd v007	view	2879
Equilibrium zero-temperature lattice constant for fcc Ag v007	view	3903
Equilibrium zero-temperature lattice constant for fcc H v007	view	3199
Equilibrium zero-temperature lattice constant for fcc Pd v007	view	2047
Equilibrium zero-temperature lattice constant for sc Ag v007	view	2303
Equilibrium zero-temperature lattice constant for sc H v007	view	1983
Equilibrium zero-temperature lattice constant for sc Pd v007	view	1919

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	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 Ag v005	view	17160
Equilibrium lattice constants for hcp H v005	view	28493
Equilibrium lattice constants for hcp Pd v005	view	21585

LinearThermalExpansionCoeffCubic__TD_522633393614_001

Linear thermal expansion coefficient of cubic crystal structures v001

Creators: Mingjian Wen
Contributor: mjwen
Publication Year: 2019
DOI: https://doi.org/10.25950/fc69d82d

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Linear thermal expansion coefficient of fcc Ag at 293.15 K under a pressure of 0 MPa v001		view	3618692

LinearThermalExpansionCoeffCubic__TD_522633393614_002

Linear thermal expansion coefficient of cubic crystal structures v002

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

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Linear thermal expansion coefficient of fcc Pd at 293.15 K under a pressure of 0 MPa v002		view	477452

PhononDispersionCurve__TD_530195868545_004

Phonon dispersion relations for an fcc lattice v004

Creators: Matt Bierbaum
Contributor: mattbierbaum
Publication Year: 2019
DOI: https://doi.org/10.25950/64f4999b

Calculates the phonon dispersion relations for fcc lattices and records the results as curves.

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Phonon dispersion relations for fcc Ag v004		view	53518
Phonon dispersion relations for fcc Pd v004		view	47728

StackingFaultFccCrystal__TD_228501831190_002

Stacking and twinning fault energies of an fcc lattice at zero temperature and pressure v002

Creators:
Contributor: SubrahmanyamPattamatta
Publication Year: 2019
DOI: https://doi.org/10.25950/b4cfaf9a

Intrinsic and extrinsic stacking fault energies, unstable stacking fault energy, unstable twinning energy, stacking fault energy as a function of fractional displacement, and gamma surface for a monoatomic FCC lattice at zero temperature and pressure.

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Stacking and twinning fault energies for fcc Ag v002		view	6088658
Stacking and twinning fault energies for fcc Pd v002		view	8402231

SurfaceEnergyCubicCrystalBrokenBondFit__TD_955413365818_004

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

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

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

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

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

In Python, these two fits take the following form:

def BrokenBondFCC(params, index):

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

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

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

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

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Broken-bond fit of high-symmetry surface energies in fcc Ag v004		view	25719
Broken-bond fit of high-symmetry surface energies in fcc Pd v004		view	27511

VacancyFormationEnergyRelaxationVolume__TD_647413317626_001

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

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

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Monovacancy formation energy and relaxation volume for fcc Ag		view	354188
Monovacancy formation energy and relaxation volume for fcc Pd		view	366998

VacancyFormationMigration__TD_554849987965_001

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

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

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

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Vacancy formation and migration energy for fcc Ag		view	2949384
Vacancy formation and migration energy for fcc Pd		view	3197191

Errors

ElasticConstantsCubic__TD_011862047401_006

Test	Error Categories	Link to Error page
Elastic constants for diamond Ag at zero temperature v001	other	view
Elastic constants for diamond H at zero temperature v001	other	view
Elastic constants for diamond Pd at zero temperature v001	other	view

EquilibriumCrystalStructure__TD_457028483760_002

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

LatticeConstantCubicEnergy__TD_475411767977_006

Test	Error Categories	Link to Error page
Equilibrium zero-temperature lattice constant for diamond Ag	other	view

No Driver

Verification Check	Error Categories	Link to Error page
MemoryLeak__VC_561022993723_004	other	view

Files

CMakeLists.txt
LICENSE.CDDL
PdAgH_MorsePd3Ag.eam
kimprovenance.edn
kimspec.edn

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EAM_Dynamo_HaleWongZimmerman_2008PairMorse_PdAgH__MO_108983864770_005.txz	Tar+XZ	Linux and OS X archive
EAM_Dynamo_HaleWongZimmerman_2008PairMorse_PdAgH__MO_108983864770_005.zip	Zip	Windows archive

Download Dependency

This Model requires a Model Driver. Archives for the Model Driver EAM_Dynamo__MD_120291908751_005 appear below.

EAM_Dynamo__MD_120291908751_005.txz	Tar+XZ	Linux and OS X archive
EAM_Dynamo__MD_120291908751_005.zip	Zip	Windows archive

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EAM_Dynamo_HaleWongZimmerman_2008PairMorse_PdAgH__MO_108983864770_005

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

Disclaimer From Model Developer

Errors

Files

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Download Dependency

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