High-throughput dataset of impurity adsorption on common catalysts in biomass upgrading applications


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{
  "id": "2124", 
  "updated": "2024-08-27T10:34:41.712788+00:00", 
  "metadata": {
    "version": 1, 
    "contributors": [
      {
        "givennames": "Michelle A.", 
        "affiliations": [
          "Catalytic Carbon Transformation & Scale-Up Center, National Renewable Energy Laboratory, Golden, CO 80401, United States", 
          "Department of Chemical and Biological Engineering, Colorado School of Mines, Golden, CO 80401, United States"
        ], 
        "familyname": "Nolen"
      }, 
      {
        "givennames": "Sean A.", 
        "affiliations": [
          "Catalytic Carbon Transformation & Scale-Up Center, National Renewable Energy Laboratory, Golden, CO 80401, United States"
        ], 
        "familyname": "Tacey"
      }, 
      {
        "givennames": "Martha A.", 
        "affiliations": [
          "Catalytic Carbon Transformation & Scale-Up Center, National Renewable Energy Laboratory, Golden, CO 80401, United States"
        ], 
        "familyname": "Arellano-Trevi\u00f1o"
      }, 
      {
        "givennames": "Kurt M.", 
        "affiliations": [
          "Catalytic Carbon Transformation & Scale-Up Center, National Renewable Energy Laboratory, Golden, CO 80401, United States"
        ], 
        "familyname": "Van Allsburg"
      }, 
      {
        "givennames": "Carrie A.", 
        "affiliations": [
          "Catalytic Carbon Transformation & Scale-Up Center, National Renewable Energy Laboratory, Golden, CO 80401, United States"
        ], 
        "email": "carrie.farberow@nrel.gov", 
        "familyname": "Farberow"
      }
    ], 
    "title": "High-throughput dataset of impurity adsorption on common catalysts in biomass upgrading applications", 
    "_oai": {
      "id": "oai:materialscloud.org:2124"
    }, 
    "keywords": [
      "density-functional theory", 
      "high-throughput", 
      "VASP"
    ], 
    "publication_date": "Apr 26, 2024, 18:21:58", 
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    "references": [
      {
        "comment": "Paper in which the dataset is discussed.", 
        "citation": "M.A. Nolen, S.A. Tacey, M.A. Arellano-Trevi\u00f1o, K.M. Van Allsburg, C.A. Farberow (2024). In preparation.", 
        "type": "Preprint"
      }
    ], 
    "description": "An extensive dataset consisting of adsorption energies of pernicious impurities present in biomass upgrading processes on common catalysts and support materials has been generated. This work aims to inform catalyst and process development for the conversion of biomass-derived feedstocks to fuels and chemicals. A high-throughput workflow was developed to execute density functional theory calculations for a diverse set of atomic (Al, B, Ca, Cl, Fe, K, Mg, Mn, N, Na, P, S, Si, Zn) and molecular (COS, H\u2082S, HCl, HCN, K\u2082O, KCl, NH\u2083) species on 35 unique surfaces for transition-metal (Ag, Au, Co, Cu, Fe, Ir, Ni, Pd, Pt, Re, Rh, Ru) and metal-oxide (Al\u2082O\u2083, MgO, anatase-TiO\u2082, rutile-TiO\u2082, ZnO, ZrO\u2082) catalysts and supports. Approximately 3,000 unique adsorption geometries were obtained. The data record includes structure and calculation output files for each unique adsorbate geometry on each surface.", 
    "status": "published", 
    "license": "Creative Commons Attribution 4.0 International", 
    "conceptrecid": "2123", 
    "is_last": false, 
    "mcid": "2024.64", 
    "edited_by": 576, 
    "id": "2124", 
    "owner": 1078, 
    "license_addendum": null, 
    "doi": "10.24435/materialscloud:4w-70"
  }, 
  "revision": 23, 
  "created": "2024-03-26T20:22:41.436065+00:00"
}