Mechanism of charge transport in lithium thiophosphate

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{
  "id": "2102", 
  "updated": "2024-03-01T16:25:23.011684+00:00", 
  "metadata": {
    "version": 2, 
    "contributors": [
      {
        "givennames": "Lorenzo", 
        "affiliations": [
          "Laboratory of Computational Science and Modeling (COSMO), Institute of Materials, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "email": "cangelsi@hotmail.it", 
        "familyname": "Gigli"
      }, 
      {
        "givennames": "Davide", 
        "affiliations": [
          "Laboratory of Computational Science and Modeling (COSMO), Institute of Materials, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "email": "davide.tisi@epfl.ch", 
        "familyname": "Tisi"
      }, 
      {
        "givennames": "Federico", 
        "affiliations": [
          "Laboratory of Computational Science and Modeling (COSMO), Institute of Materials, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "email": "federico.grasselli@epfl.ch", 
        "familyname": "Grasselli"
      }, 
      {
        "givennames": "Michele", 
        "affiliations": [
          "Laboratory of Computational Science and Modeling (COSMO), Institute of Materials, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "email": "cosmo.epfl@gmail.com", 
        "familyname": "Ceriotti"
      }
    ], 
    "title": "Mechanism of charge transport in lithium thiophosphate", 
    "_oai": {
      "id": "oai:materialscloud.org:2102"
    }, 
    "keywords": [
      "machine learning", 
      "Lithium Thiophosphate", 
      "Lithium Ion Diffusion", 
      "PS4 rotational dynamics", 
      "Electrical conductivity", 
      "Green-Kubo time correlation functions", 
      "molecular dynamics", 
      "post-GGA Density Functional Theory", 
      "Phase transitions", 
      "MARVEL", 
      "SNSF Sinergia"
    ], 
    "publication_date": "Mar 01, 2024, 17:25:22", 
    "_files": [
      {
        "key": "MaterialsCloudArchive-ChemMat2024.zip", 
        "description": "Contains directories with a brief README and the data to reproduce the figures in the main text and the Supplemental Material", 
        "checksum": "md5:e838e8716fb42200c34f06119337e909", 
        "size": 170896274
      }
    ], 
    "references": [
      {
        "doi": "https://doi.org/10.48550/arXiv.2310.15679", 
        "citation": "L. Gigli*, D. Tisi*, F. Grasselli, M. Ceriotti,  arXiv:2310.15679 [cond-mat.mtrl-sci] (2023)", 
        "url": "https://arxiv.org/abs/2310.15679", 
        "type": "Preprint"
      }, 
      {
        "comment": "Paper where the data are used and described", 
        "doi": "10.1021/acs.chemmater.3c02726", 
        "citation": "L. Gigli, D. Tisi, F. Grasselli, and M. Ceriotti, Chem. Mater., 36, 3, 1482\u20131496 (2024)", 
        "url": "https://pubs.acs.org/doi/full/10.1021/acs.chemmater.3c02726", 
        "type": "Journal reference"
      }
    ], 
    "description": "Lithium ortho-thiophosphate (Li\u2083PS\u2084) has emerged as a promising candidate for solid-state-electrolyte batteries, thanks to its highly conductive phases, cheap components, and large electrochemical stability range. Nonetheless, the microscopic mechanisms of Li-ion transport in Li\u2083PS\u2084 are far to be fully understood, the role of PS\u2084 dynamics in charge transport still being controversial. We build machine learning potentials targeting state-of-the-art DFT references (PBEsol, r\u00b2SCAN, and PBE0) to tackle this problem in all known phases of Li\u2083PS\u2084 (\u03b1, \u03b2 and \u03b3), for large system sizes and timescales. We discuss the physical origin of the observed superionic behavior of Li\u2083PS\u2084: the activation of PS\u2084 flipping drives a structural transition to a highly conductive phase, characterized by an increase of Li-site availability and by a drastic reduction in the activation energy of Li-ion diffusion. We also rule out any paddle-wheel effects of PS\u2084 tetrahedra in the superionic phases\u2013previously claimed to enhance Li-ion diffusion\u2013due to the orders-of-magnitude difference between the rate of PS\u2084 flips and Li-ion hops at all temperatures below melting. \nThis archive provides all the relevant data and input files that were used to fit the ML interatomic potentials used in this work, along with the relevant Density-Functional Theory calculations that were used for the training set construction, the validation of the ML models and the calculation of the electronic band structure of the \u03b2 and \u03b3 structure. Furthermore, it provides input files of all the molecular dynamics trajectories needed to investigate Li-ion diffusion properties of Li\u2083PS\u2084 and the rotational dynamics of PS\u2084 tetrahedra. Finally, it provides the raw data to reproduce the figures of the manuscript associated with this archive.", 
    "status": "published", 
    "license": "Creative Commons Attribution 4.0 International", 
    "conceptrecid": "2018", 
    "is_last": true, 
    "mcid": "2024.41", 
    "edited_by": 576, 
    "id": "2102", 
    "owner": 691, 
    "license_addendum": null, 
    "doi": "10.24435/materialscloud:qy-gv"
  }, 
  "revision": 2, 
  "created": "2024-03-01T14:48:48.001940+00:00"
}