colabfit/CuPd_CMS2019
Cite this dataset Gubaev, K., Podryabinkin, E. V., Hart, G. L., and Shapeev, A. V. CuPd CMS2019. ColabFit, 2023. https://doi.org/10.60732/1058e01c This dataset has been curated and formatted for the ColabFit Exchange This dataset is also available on the ColabFit Exchange: https://materials.colabfit.org/id/DS_0ry6z1j8mi8c_0 Visit the ColabFit Exchange to search additional datasets by author, description, element content and more.… See the full description on the dataset page: https://huggingface.co/datasets/colabfit/CuPd_CMS2019.
<details><summary>Cite this dataset </summary>Gubaev, K., Podryabinkin, E. V., Hart, G. L., and Shapeev, A. V. CuPd CMS2019. ColabFit, 2023. https://doi.org/10.60732/1058e01c</details>
This dataset has been curated and formatted for the ColabFit Exchange
This dataset is also available on the ColabFit Exchange:
https://materials.colabfit.org/id/DS0ry6z1j8mi8c0
Visit the ColabFit Exchange to search additional datasets by author, description, element content and more.
https://materials.colabfit.org <br><hr>
Dataset Name
CuPd CMS2019
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 40,000 unrelaxed configurations with BCC, FCC, and HCP lattices.
Dataset authors
Konstantin Gubaev, Evgeny V. Podryabinkin, Gus L.W. Hart, Alexander V. Shapeev
Publication
https://doi.org/10.1016/j.commatsci.2018.09.031
Original data link
https://gitlab.com/kgubaev/accelerating-high-throughput-searches-for-new-alloys-with-active-learning-data
License
CC-BY-4.0
Number of unique molecular configurations
522
Number of atoms
2450
Elements included
Cu, Pd
Properties included
energy, atomic forces, cauchy stress <br> <hr>
Usage
ds.parquet: Aggregated dataset information.co/directory: Configuration rows each include a structure, calculated properties, and metadata.cs/directory : Configuration sets are subsets of configurations grouped by some common characteristic. Ifcs/does not exist, no configurations sets have been defined for this dataset.cs_co_map/directory : The mapping of configurations to configuration sets (if defined). <br>
