Sim_LAMMPS_EDIP_LucasBertolusPizzagalli_2009_SiC__SM_435704953434_000
| Title
A single sentence description.
|
LAMMPS EDIP potential for Si-C developed by Lucas, Bertolus, and Pizzagalli (2009) v000 |
|---|---|
| Description |
An interatomic potential has been developed to describe interactions in silicon, carbon, and silicon carbide. This model generalizes the semi-empirical interatomic potential EDIP, initially designed for silicon (Bazant et al. 1997 Phys. Rev. B 56 8542), for modeling silicon carbide. In addition, the functional form of the original EDIP has been generalized, where all the parameters for Si–Si, C–C, and Si–C interactions are new. This potential has been tested for silicon, carbon (diamond), and silicon carbide for a wide range of properties, including bulk properties stability and structure of high-pressure crystalline phases, formation energy and point structure, extended defects, and amorphous phases structure. The proposed potential enables an accurate description of point and extended defects in silicon, diamond, and silicon carbide, thus preserving the initial focus of the original EDIP potential. An extra feature of this parameter set is the excellent description of the high-pressure phases of the different materials. NOTE: This model was previously named Sim_LAMMPS_EDIP_JiangMorganSzlufarska_2012_SiC__SM_435704953434_000. It was discovered that the header in the parameter file contained in the model was erroneous and that, in fact, the parameters are from G. Lucas, M. Bertolus, and L. Pizzagalli, J. Phys.: Condens. Matter 22, 035802 (2009). |
| Species
The supported atomic species.
| C, Si |
| Disclaimer
A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.
|
None |
| Content Origin | LAMMPS package 30-Jul-2021 |
| Contributor |
Daniel S. Karls |
| Maintainer |
Daniel S. Karls |
| Implementer | Chao Jiang |
| Developer |
G. Lucas M. Bertolus L. Pizzagalli |
| Published on KIM | 2019 |
| How to Cite |
This Simulator Model originally published in [1] is archived in OpenKIM [2-4]. [1] Lucas G, Bertolus M, Pizzagalli L. An environment-dependent interatomic potential for silicon carbide: calculation of bulk properties, high-pressure phases, point and extended defects, and amorphous structures. Journal of Physics: Condensed Matter. 2009Dec;22(3):035802. doi:10.1088/0953-8984/22/3/035802 — (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] Jiang C, Lucas G, Bertolus M, Pizzagalli L. LAMMPS EDIP potential for Si-C developed by Lucas, Bertolus, and Pizzagalli (2009) v000. OpenKIM; 2019. doi:10.25950/b67a8c85 [3] 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 [4] 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. 
Help us to determine which of the papers that cite this potential actually used it to perform calculations. If you know, click the .
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| Funding | Not available |
| Short KIM ID
The unique KIM identifier code.
| SM_435704953434_000 |
| 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.
| Sim_LAMMPS_EDIP_LucasBertolusPizzagalli_2009_SiC__SM_435704953434_000 |
| DOI |
10.25950/b67a8c85 https://doi.org/10.25950/b67a8c85 https://commons.datacite.org/doi.org/10.25950/b67a8c85 |
| KIM Item Type | Simulator Model |
| KIM API Version | 2.1 |
| Simulator Name
The name of the simulator as defined in kimspec.edn.
| LAMMPS |
| Potential Type | edip |
| Simulator Potential | edip |
| Run Compatibility | portable-models |
| 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 |
| F | 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 |
| N/A | 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 |
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: CSpecies: Si
Creators: 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.