Dataset
CoNbV_CMS2019
Dataset Downloads Coming Soon
| Name | CoNbV_CMS2019 |
|---|---|
| Extended ID | CoNbV_CMS2019__Gubaev-Podryabinkin-Hart-Shapeev__DS_sn623uhg2d1b_0 |
| Description | This dataset was generated using the following active learning scheme: 1) candidate structures were relaxed by a partially-trained MTP model, 2) structures for which the MTP had to perform extrapolation were passed to DFT to be re-computed, 3) the MTP was retrained, including the structures that were re-computed with DFT, 4) steps 1-3 were repeated until the MTP no longer extrapolated on any of the original candidate structures. The original candidate structures for this dataset included about 27,000 configurations that were bcc-like and close-packed (fcc, hcp, etc.) with 8 or fewer atoms in the unit cell and different concentrations of Co, Nb, and V. |
| Authors |
Konstantin Gubaev Evgeny V. Podryabinkin Gus L.W. Hart Alexander V. Shapeev |
| DOI |
10.60732/f2c623f1
https://commons.datacite.org/doi.org/10.60732/f2c623f1 https://doi.datacite.org/dois/10.60732%2Ff2c623f1 https://doi.org/10.60732/f2c623f1 Cite as: Gubaev, K., Podryabinkin, E. V., Hart, G. L., and Shapeev, A. V. "CoNbV CMS2019." ColabFit, 2023. https://doi.org/10.60732/f2c623f1. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
Co (54.77%) Nb (26.24%) V (18.99%) |
| Number of Configurations | 383 |
| Number of Atoms | 2,812 |
| Links |
https://gitlab.com/kgubaev/accelerating-high-throughput-searches-for-new-alloys-with-active-learning-data https://doi.org/10.1016/j.commatsci.2018.09.031 |
| Configuration Sets by Name | (None) |
| Configuration Sets by ID | (None) |
| Calculated Properties | |
| ColabFit ID | DS_sn623uhg2d1b_0 |
| Files | colabfitspec.json |
No uploaded content is transferred in ownership from the original creators to ColabFit. All content is distributed under the license specified by its contributor who has stated that he or she has the authority to share it under the specified license.