AlNiTi_CMS_2019 / README.md
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metadata
configs:
  - config_name: default
    data_files: main/*.parquet
license: cc-by-4.0
tags:
  - molecular dynamics
  - mlip
  - interatomic potential
pretty_name: AlNiTi CMS 2019

Dataset

AlNiTi CMS 2019

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 375,000 binary and ternary structures, enumerating all possible unit cells with different symmetries (BCC, FCC, and HCP) and different number of atoms.

Additional details stored in dataset columns prepended with "dataset_".

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

2684

Number of atoms

25067

Elements included

Al, Ni, Ti

Properties included

energy, atomic forces, cauchy stress

Cite this dataset

Gubaev, K., Podryabinkin, E. V., Hart, G. L., and Shapeev, A. V. AlNiTi CMS 2019. ColabFit, 2023. https://doi.org/10.60732/7b56ca82