eQM7: a dataset for small molecules with Foster-Boys centers


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{
  "revision": 19, 
  "id": "1026", 
  "created": "2021-09-17T09:56:14.333046+00:00", 
  "metadata": {
    "doi": "10.24435/materialscloud:66-9j", 
    "status": "published", 
    "title": "eQM7: a dataset for small molecules with Foster-Boys centers", 
    "mcid": "2021.154", 
    "license_addendum": null, 
    "_files": [
      {
        "description": "The eQM7 dataset. For all 6868 molecules, four extended XYZ files are stored, containing all 500 perturbations per molecule. Read the README file for more information.", 
        "key": "eQM7.tar.gz", 
        "size": 2869408878, 
        "checksum": "md5:5a1ab9299cb1e5914c11874c1b076139"
      }, 
      {
        "description": "An archive containing the hessians and optimized geometries for each of the 6868 molecules in the eQM7 dataset.", 
        "key": "hessians.tar.gz", 
        "size": 95716271, 
        "checksum": "md5:60906e6b4f53e161adea3d1c0cf4f068"
      }, 
      {
        "description": "An archive containing the hessians and optimized geometries of the reference molecules for the eMLP.", 
        "key": "reference_hessians.tar.gz", 
        "size": 5273, 
        "checksum": "md5:9b04a40ed2f9aabf1a8d618aa848b7ce"
      }, 
      {
        "description": "Detailed description of the dataset and all the files.", 
        "key": "README.txt", 
        "size": 3937, 
        "checksum": "md5:076917784fac1bc744d7a379cf1342dd"
      }
    ], 
    "owner": 530, 
    "_oai": {
      "id": "oai:materialscloud.org:1026"
    }, 
    "keywords": [
      "machine learning", 
      "density-functional theory", 
      "Foster-Boys centers"
    ], 
    "conceptrecid": "1025", 
    "is_last": true, 
    "references": [
      {
        "type": "Journal reference", 
        "doi": "https://doi.org/10.1021/acs.jctc.1c00978", 
        "url": "https://pubs.acs.org/doi/10.1021/acs.jctc.1c00978", 
        "comment": "Paper in which the dataset is described", 
        "citation": "M. Cools-Ceuppens, J. Dambre, T. Verstraelen, J. Chem. Theory Comput. 18 (3), 1672\u20131691 (2022)"
      }
    ], 
    "publication_date": "Sep 27, 2021, 11:46:11", 
    "license": "Creative Commons Attribution Share Alike 4.0 International", 
    "id": "1026", 
    "description": "The electron QM7 (eQM7) dataset is created with the purpose of training and validating polarizable (machine learning) force fields on non-equilibrium configurations of small molecules. It contains 6868 molecules with hydrogen, carbon, nitrogen and oxygen. For each molecule, 500 perturbations are constructed using normal mode sampling, torsion sampling, dimer sampling and homogeneous electric fields. Energies, forces and Foster-Boys centers are computed using density functional theory (DFT) with the PBE0 functional, Aug-cc-pVTZ basis set in the ab-initio quantum chemistry code Psi4.", 
    "version": 1, 
    "contributors": [
      {
        "email": "maarten.coolsceuppens@ugent.be", 
        "affiliations": [
          "Ghent University, Center for Molecular Modeling, Technologiepark-Zwijnaarde 46, Gent, B-9052, Belgium"
        ], 
        "familyname": "Cools-Ceuppens", 
        "givennames": "Maarten"
      }, 
      {
        "affiliations": [
          "Ghent University - imec, IDLab, Electronics and Information Systems Department, Technologiepark-Zwijnaarde 126, Gent, B-9052, Belgium"
        ], 
        "familyname": "Dambre", 
        "givennames": "Joni"
      }, 
      {
        "email": "toon.verstraelen@ugent.be", 
        "affiliations": [
          "Ghent University, Center for Molecular Modeling, Technologiepark-Zwijnaarde 46, Gent, B-9052, Belgium"
        ], 
        "familyname": "Verstraelen", 
        "givennames": "Toon"
      }
    ], 
    "edited_by": 530
  }, 
  "updated": "2022-03-08T09:52:14.391594+00:00"
}