SW_LeeHwang_2012GGA_Si__MO_040570764911_001
| Title
A single sentence description.
|
Stillinger-Weber potential for Si optimized for thermal conductivity due to Lee and Hwang (1985); GGA parameterization v001 |
|---|---|
| Description
A short description of the Model describing its key features including for example: type of model (pair potential, 3-body potential, EAM, etc.), modeled species (Ac, Ag, ..., Zr), intended purpose, origin, and so on.
|
A force-matching method is employed to optimize the parameters of the Stillinger–Weber (SW) interatomic potential for calculation of the lattice thermal conductivity of silicon. The parameter fitting is based on first-principles density functional calculations of the restoring forces for atomic displacements. The thermal conductivities of bulk crystalline Si at 300–500 K estimated using nonequilibrium molecular dynamics with the modified parameter set show excellent agreement with existing experimental data. The force-matching-based parameterization is shown to provide improved estimation of thermal conductivity, as compared to the original SW parameter set, through analysis of phonon density of states and phonon dispersion relations. Two parameterizations are provided in the paper. one fit to DFT/LDA and the other to DFT/GGA. This model is the GGA parameterization. |
| Species
The supported atomic species.
| Si |
| Disclaimer
A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.
|
None |
| Contributor |
Ellad B. Tadmor |
| Maintainer |
Ellad B. Tadmor |
| Implementer | Ellad B. Tadmor |
| Developer |
Yongjin Lee G.S. Hwang |
| Published on KIM | 2021 |
| How to Cite |
This Model originally published in [1] is archived in OpenKIM [2-5]. [1] Lee Y, Hwang GS. Force-matching-based parameterization of the Stillinger-Weber potential for thermal conduction in silicon. Phys Rev B. 2012;85(12):125204. doi:10.1103/PhysRevB.85.125204 — (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] Tadmor EB, Lee Y, Hwang GS. Stillinger-Weber potential for Si optimized for thermal conductivity due to Lee and Hwang (1985); GGA parameterization v001. OpenKIM; 2021. doi:10.25950/d84bb56f [3] Wen M, Afshar Y, Stillinger FH, Weber TA. Stillinger-Weber (SW) Model Driver v005. OpenKIM; 2021. doi:10.25950/934dca3e [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. 
36 Citations (12 used)
Help us to determine which of the papers that cite this potential actually used it to perform calculations. If you know, click the .
USED (definite) L. de Sousa Oliveira, V. Vargiamidis, and N. Neophytou, “Modeling Thermoelectric Performance in Nanoporous Nanocrystalline Silicon,” IEEE Transactions on Nanotechnology. 2019. link Times cited: 5 Abstract: Introducing hierarchical disorder from multiple defects into… read more USED (definite) L. de Sousa Oliveira, V. Vargiamidis, and N. Neophytou, “Transport simulations in hierarchically disordered nanostructures for thermoelectric material design,” 2018 IEEE 13th Nanotechnology Materials and Devices Conference (NMDC). 2018. link Times cited: 0 Abstract: Hierarchically nanostructured materials, where disorder is i… read more USED (high confidence) C. Lortaraprasert and J. Shiomi, “Robust combined modeling of crystalline and amorphous silicon grain boundary conductance by machine learning,” npj Computational Materials. 2022. link Times cited: 1 USED (high confidence) T. Ichikawa, E. Minamitani, Y. Shigesato, M. Kashiwagi, and T. Shiga, “How mass disorder affects heat conduction in ternary amorphous alloys,” AIP Advances. 2021. link Times cited: 1 Abstract: Thermal management is critical in devices that use amorphous… read more USED (high confidence) D. Wang, L. Liu, M. Chen, and H. Zhuang, “Electrical and thermal transport properties of medium-entropy Si Ge Sn alloys,” Acta Materialia. 2020. link Times cited: 10 USED (high confidence) C. Melis, R. Rurali, X. Cartoixà, and F. X. Alvarez, “Indications of Phonon Hydrodynamics in Telescopic Silicon Nanowires,” Physical Review Applied. 2019. link Times cited: 9 Abstract: Heat flow at the nanoscale is still a topic full of unsolved… read more USED (high confidence) Y. Lee and G. Hwang, “Molecular dynamics investigation of the thermal conductivity of ternary silicon–germanium–tin alloys,” Journal of Physics D: Applied Physics. 2017. link Times cited: 9 Abstract: A further reduction of the thermal conductivity (κ) of silic… read more USED (high confidence) R. Frieling, M. Radek, S. Eon, H. Bracht, and D. Wolf, “Phonon coherence in isotopic silicon superlattices,” Applied Physics Letters. 2014. link Times cited: 10 Abstract: Recent experimental and theoretical investigations have conf… read more USED (high confidence) S. Ju and X.-gang Liang, “Thermal conductivity of nanocrystalline silicon by direct molecular dynamics simulation,” Journal of Applied Physics. 2012. link Times cited: 38 Abstract: The thermal conductivity simulation of nanocrystalline silic… read more USED (low confidence) D. Liu, “Investigation on thermal conductivity of graphene/Si heterostructure with different defect ratios and sizes,” Physics Letters A. 2020. link Times cited: 5 USED (low confidence) F. G. VanGessel and P. Chung, “Phonon backscatter, trapping, and misalignment effects on microscale thermal conductance below the Casimir limit,” International Journal of Heat and Mass Transfer. 2019. link Times cited: 4 USED (low confidence) E. Lampin, “Recrystallization of Silicon by Classical Molecular Dynamics.” 2015. link Times cited: 0 NOT USED (low confidence) S. Lin, Y. Liu, Z. Cai, and C. Zhao, “High-Throughput Screening of Aperiodic Superlattices Based on Atomistic Simulation-Informed Effective Medium Theory and Genetic Algorithm,” SSRN Electronic Journal. 2023. link Times cited: 3 NOT USED (low confidence) S. Wyant, A. Rohskopf, and A. Henry, “Machine learned interatomic potentials for modeling interfacial heat transport in Ge/GaAs,” Computational Materials Science. 2021. link Times cited: 4 NOT USED (low confidence) A. Rohskopf, S. Wyant, K. Gordiz, H. R. Seyf, M. G. Muraleedharan, and A. Henry, “Fast & accurate interatomic potentials for describing thermal vibrations,” Computational Materials Science. 2020. link Times cited: 7 NOT USED (low confidence) 黄建平 and 唐婧, “硅晶体原子间相互作用力常数的计算与负热膨胀机制的研究 Calculations of the Interatomic Force Constants and Study on the Mechanism of Negative Thermal Expansion of Silicon Crystal,” Open Journal of Nature Science. 2017. link Times cited: 0 Abstract: 本文根据Rignanese等人基于第一性原理得到的硅晶体中原子间的力常数矩阵元，计算了两体和三体线性力常数，再将这些线性… read more NOT USED (low confidence) L. Koziol, L. Fried, and N. Goldman, “Using Force Matching To Determine Reactive Force Fields for Water under Extreme Thermodynamic Conditions.,” Journal of chemical theory and computation. 2017. link Times cited: 24 Abstract: We present a method for the creation of classical force fiel… read more NOT USED (low confidence) Y. Lee, A. Pak, and G. Hwang, “What is the thermal conductivity limit of silicon germanium alloys?,” Physical chemistry chemical physics : PCCP. 2016. link Times cited: 14 Abstract: The lowest possible thermal conductivity of silicon-germaniu… read more NOT USED (low confidence) X. Cartoixà, L. Colombo, and R. Rurali, “Thermal Rectification by Design in Telescopic Si Nanowires.,” Nano letters. 2015. link Times cited: 65 Abstract: We show that thermal rectification by design is possible by … read more NOT USED (low confidence) M. Wang, X. Shan, and N. Yang, “Understanding length dependences of effective thermal conductivity of nanowires,” Physics Letters A. 2012. link Times cited: 24 NOT USED (low confidence) D. Liang, R. Ma, S. Jiao, G. Pang, and S. Feng, “A facile synthetic approach for copper iron sulfide nanocrystals with enhanced thermoelectric performance.,” Nanoscale. 2012. link Times cited: 87 Abstract: Chalcopyrite CuFeS(2) nanocrystals with a diameter of 6.4 nm… read more NOT USED (low confidence) Y. Lee and G. Hwang, “Fundamental insight into control of thermal conductivity in silicon-germanium alloy nanowires,” MRS Proceedings. 2014. link Times cited: 0 NOT USED (high confidence) Y. Luo, M. Li, H. Yuan, H. Liu, and Y. Fang, “Predicting lattice thermal conductivity via machine learning: a mini review,” npj Computational Materials. 2023. link Times cited: 11 NOT USED (high confidence) D. Chen, X.-Y. Jiang, D. Wang, J. I. Vidallon, H. Zhuang, and Y. Jiao, “Multihyperuniform long-range order in medium-entropy alloys,” Acta Materialia. 2021. link Times cited: 6 NOT USED (high confidence) M. Morita and T. Shiga, “Surface phonons limit heat conduction in thin films,” Physical Review B. 2020. link Times cited: 3 Abstract: Understanding microscopic heat conduction in thin films is im… read more NOT USED (high confidence) Y. Lee and G. Hwang, “Strong thermal conductivity dependence on arsenic-vacancy complex formation in arsenic-doped silicon,” Journal of Applied Physics. 2019. link Times cited: 1 Abstract: High-concentration doping of silicon (Si)-based materials is… read more NOT USED (high confidence) F. G. VanGessel, J. Peng, and P. Chung, “A review of computational phononics: the bulk, interfaces, and surfaces,” Journal of Materials Science. 2018. link Times cited: 22 NOT USED (high confidence) A. Pak and G. Hwang, “Theoretical Analysis of Thermal Transport in Graphene Supported on Hexagonal Boron Nitride: The Importance of Strong Adhesion Due to π -Bond Polarization,” Physical review applied. 2016. link Times cited: 15 Abstract: One important attribute of graphene that makes it attractive… read more NOT USED (high confidence) J. Hattori, V. Poborchii, and T. Tada, “Axial strain effects on ballistic phonon thermal transport in silicon nanowires,” Japanese Journal of Applied Physics. 2016. link Times cited: 1 Abstract: We study the effects of axial strain on phonon thermal trans… read more NOT USED (high confidence) R. Frieling, S. Eon, D. Wolf, and H. Bracht, “Molecular dynamics simulations of thermal transport in isotopically modulated semiconductor nanostructures,” physica status solidi (a). 2016. link Times cited: 9 Abstract: In this paper, we investigate the effect of isotopic modulat… read more NOT USED (high confidence) T. Tadano, Y. Gohda, and S. Tsuneyuki, “Anharmonic force constants extracted from first-principles molecular dynamics: applications to heat transfer simulations,” Journal of Physics: Condensed Matter. 2014. link Times cited: 337 Abstract: A systematic method to calculate anharmonic force constants … read more NOT USED (high confidence) X. A. Deng, Y. Song, J. Li, and Y. Pu, “Parametrization of the Stillinger-Weber potential for Si/N/H system and its application to simulations of silicon nitride film deposition with SiH4/NH3,” Journal of Applied Physics. 2014. link Times cited: 1 Abstract: We determined the Stillinger-Weber interatomic potential par… read more NOT USED (high confidence) Y. Lee and G. Hwang, “Microsegregation effects on the thermal conductivity of silicon-germanium alloys,” Journal of Applied Physics. 2013. link Times cited: 12 Abstract: A silicon-germanium (SiGe) alloy is a promising candidate fo… read more NOT USED (high confidence) Y. Jing, M. Hu, and L. Guo, “Thermal conductivity of hybrid graphene/silicon heterostructures,” Journal of Applied Physics. 2013. link Times cited: 23 Abstract: The success of fabricating single layer graphene and silicon… read more NOT USED (high confidence) P. Howell, “Comparison of molecular dynamics methods and interatomic potentials for calculating the thermal conductivity of silicon.,” The Journal of chemical physics. 2012. link Times cited: 74 Abstract: We compare the molecular dynamics Green-Kubo and direct meth… read more |
| Funding | Not available |
| Short KIM ID
The unique KIM identifier code.
| MO_040570764911_001 |
| 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.
| SW_LeeHwang_2012GGA_Si__MO_040570764911_001 |
| DOI |
10.25950/d84bb56f https://doi.org/10.25950/d84bb56f https://commons.datacite.org/doi.org/10.25950/d84bb56f |
| 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 SW__MD_335816936951_005 |
| Driver | SW__MD_335816936951_005 |
| KIM API Version | 2.0 |
| Potential Type | sw |
| Previous Version | SW_LeeHwang_2012GGA_Si__MO_040570764911_000 |
| Grade | Name | Category | Brief Description | Full Results | Aux File(s) |
|---|---|---|---|---|---|
| P | vc-species-supported-as-stated | mandatory | The model supports all species it claims to support; see full description. |
Results | Files |
| P | vc-periodicity-support | mandatory | Periodic boundary conditions are handled correctly; see full description. |
Results | Files |
| P | vc-permutation-symmetry | mandatory | Total energy and forces are unchanged when swapping atoms of the same species; see full description. |
Results | Files |
| A | vc-forces-numerical-derivative | consistency | Forces computed by the model agree with numerical derivatives of the energy; see full description. |
Results | Files |
| P | 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 | vc-objectivity | informational | Total energy is unchanged and forces transform correctly under rigid-body translation and rotation; see full description. |
Results | Files |
| P | 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 | 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 | 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 | 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 |
BCC Lattice Constant
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.
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.
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.
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.
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.
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.
Cubic Crystal Basic Properties Table
Species: SiCreators: Daniel S. Karls
Contributor: karls
Publication Year: 2019
DOI: https://doi.org/10.25950/b47dd4c4
Given an xyz file corresponding to a finite cluster of atoms, this Test Driver computes the total potential energy and atomic forces on the configuration. The positions are then relaxed using conjugate gradient minimization and the final positions and forces are recorded. These results are primarily of interest for training machine-learning algorithms.
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 | 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) |
|---|---|---|---|
| Cohesive energy versus lattice constant curve for bcc Si v004 | view | 2218 | |
| Cohesive energy versus lattice constant curve for diamond Si v004 | view | 2307 | |
| Cohesive energy versus lattice constant curve for fcc Si v004 | view | 2208 | |
| Cohesive energy versus lattice constant curve for sc Si v004 | view | 2503 |
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 | Test Results | Link to Test Results page | Benchmark time
Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run.
Measured in Millions of Whetstone Instructions (MWI) |
|---|---|---|---|
| Elastic constants for bcc Si at zero temperature v006 | view | 3164 | |
| Elastic constants for diamond Si at zero temperature v001 | view | 4292 | |
| Elastic constants for fcc Si at zero temperature v006 | view | 2882 | |
| Elastic constants for sc Si at zero temperature v006 | view | 2757 |
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.
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 | 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 zero-temperature lattice constant for bcc Si v007 | view | 1566 | |
| Equilibrium zero-temperature lattice constant for diamond Si v007 | view | 2287 | |
| Equilibrium zero-temperature lattice constant for fcc Si v007 | view | 2287 | |
| Equilibrium zero-temperature lattice constant for sc Si v007 | view | 2036 |
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 diamond Si at 293.15 K under a pressure of 0 MPa v002 | view | 698879 |
Creators: Daniel S. Karls
Contributor: karls
Publication Year: 2019
DOI: https://doi.org/10.25950/c3dca28e
Given an extended xyz file corresponding to a non-orthogonal periodic box of atoms, use LAMMPS to compute the total potential energy and atomic forces.
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 diamond Si | view | 85694 |
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 diamond Si | view | 3986697 |
| Test | Error Categories | Link to Error page |
|---|---|---|
| Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_oC92_63_ce2f2g3h v000 | other | view |
EquilibriumCrystalStructure__TD_457028483760_002
| Test | Error Categories | Link to Error page |
|---|---|---|
| Equilibrium crystal structure and energy for Si in AFLOW crystal prototype A_hR8_148_cf v002 | other | view |
LatticeConstantHexagonalEnergy__TD_942334626465_005
| Test | Error Categories | Link to Error page |
|---|---|---|
| Equilibrium lattice constants for hcp Si v005 | other | view |
| SW_LeeHwang_2012GGA_Si__MO_040570764911_001.txz | Tar+XZ | Linux and OS X archive |
| SW_LeeHwang_2012GGA_Si__MO_040570764911_001.zip | Zip | Windows archive |
This Model requires a Model Driver. Archives for the Model Driver SW__MD_335816936951_005 appear below.
| SW__MD_335816936951_005.txz | Tar+XZ | Linux and OS X archive |
| SW__MD_335816936951_005.zip | Zip | Windows archive |