Dataset
CoNbV_CMS2019
Download Dataset XYZ file
| Name | CoNbV_CMS2019 |
|---|---|
| Extended ID | CoNbV_CMS2019_GubaevPodryabinkinHartShapeev__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. |
| Elements |
Co (54.77%) Nb (26.24%) V (18.99%) |
| Number of Data Objects | 383 |
| 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) |
| Data Objects | |
| ColabFit ID | DS_sn623uhg2d1b_0 |
| Files | colabfitspec.json |
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