Gaussian approximation potentials (GAP) for germanium telluride


JSON Export

{
  "id": "778", 
  "metadata": {
    "title": "Gaussian approximation potentials (GAP) for germanium telluride", 
    "doi": "10.24435/materialscloud:pd-g9", 
    "license": "Creative Commons Attribution 4.0 International", 
    "keywords": [
      "interatomic potential", 
      "gaussian approximation potential", 
      "germanium telluride"
    ], 
    "contributors": [
      {
        "affiliations": [
          "Tyndall National Institute, Cork, Republic of Ireland", 
          "University College Cork, Cork, Republic of Ireland"
        ], 
        "familyname": "Dangi\u0107", 
        "email": "djordje.dangic@tyndall.ie", 
        "givennames": "\u0110or\u0111e"
      }, 
      {
        "affiliations": [
          "University College Cork, Cork, Republic of Ireland", 
          "Tyndall National Institute, Cork, Republic of Ireland"
        ], 
        "familyname": "Fahy", 
        "email": "s.fahy@ucc.ie", 
        "givennames": "Stephen"
      }, 
      {
        "affiliations": [
          "Tyndall National Institute, Cork, Republic of Ireland"
        ], 
        "familyname": "Savi\u0107", 
        "email": "ivana.savic@tyndall.ie", 
        "givennames": "Ivana"
      }
    ], 
    "_files": [
      {
        "description": "train_GeTe.xyz contains density functional theory energies and forces for a number of different atomic configurations of GeTe. GAP.xml* are the potential files used by LAMMPS to perform molecular dynamics simulations. train.sh is the bash script used to train GAP potential.", 
        "checksum": "md5:f49e5b843c970f072e317e7873120e04", 
        "size": 95544368, 
        "key": "complete_data_GAP_GeTe.tar.gz"
      }
    ], 
    "references": [
      {
        "type": "Preprint", 
        "citation": "\u0110. Dangi\u0107, O. Hellman, S. Fahy, I. Savi\u0107, arXiv:2012.08414 [cond-mat.mtrl-sci]", 
        "comment": "Preprint where the data is discussed.", 
        "url": "https://arxiv.org/abs/2012.08414"
      }, 
      {
        "type": "Journal reference", 
        "doi": "https://doi.org/10.1038/s41524-021-00523-7", 
        "citation": "\u0110. Dangi\u0107, O. Hellman, S. Fahy, I. Savi\u0107 npj Computational Materials volume 7, Article number: 57 (2021)", 
        "comment": "Paper where the data is discussed.", 
        "url": "https://www.nature.com/articles/s41524-021-00523-7"
      }
    ], 
    "conceptrecid": "777", 
    "version": 1, 
    "edited_by": 347, 
    "id": "778", 
    "owner": 347, 
    "mcid": "2021.42", 
    "is_last": true, 
    "status": "published", 
    "description": "Quasiharmonic theory of atomic vibrations usually fails to describe materials that undergo structural phase transitions, which is the case with germanium telluride (GeTe) at high temperatures. To correctly model vibrational properties of GeTe at high temperatures, we use the temperature dependent effective potential (TDEP) method (Physical Review B 88, 144301 (2013)). Collecting data needed to fit TDEP models involves running ab-initio molecular dynamics (MD) simulations. These MD simulations can be very CPU time consuming. In order to speed up MD simulations, we fitted an interatomic potential using the Gaussian Approximation Potential (GAP) approach (Physical Review Letters 104, 136403 (2010)) to obtain interatomic forces during MD simulations. This dataset consists of the training set of density functional theory energies and forces of GeTe for GAP, and the training script used to generate the interatomic potential.", 
    "license_addendum": null, 
    "_oai": {
      "id": "oai:materialscloud.org:778"
    }, 
    "publication_date": "Mar 16, 2021, 13:58:19"
  }, 
  "revision": 5, 
  "updated": "2021-05-05T14:03:15.416649+00:00", 
  "created": "2021-03-15T09:47:05.273179+00:00"
}