Capturing chemical intuition in synthesis of metal-organic frameworks

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{
  "revision": 2, 
  "id": "49", 
  "created": "2020-05-12T13:52:19.024490+00:00", 
  "metadata": {
    "doi": "10.24435/materialscloud:2018.0011/v3", 
    "status": "published", 
    "title": "Capturing chemical intuition in synthesis of metal-organic frameworks", 
    "mcid": "2018.0011/v3", 
    "license_addendum": null, 
    "_files": [
      {
        "description": "Video introducing the SyCoFinder web application which combines scripts used in this study to find optimal synthesis conditions.", 
        "key": "SyCoFinder_movie.mp4", 
        "size": 15230335, 
        "checksum": "md5:8fa477622aeb32893d1c7440ff9ce009"
      }, 
      {
        "description": "Synthesis conditions and their corresponding fitness scores for the synthesis trials of the three generations of the genetic algorithm optimization for Cu-HKUST-1", 
        "key": "CuBTC_synthesis.csv", 
        "size": 4014, 
        "checksum": "md5:ee3a5f860cc84bb1170bad02aa995080"
      }
    ], 
    "owner": 20, 
    "_oai": {
      "id": "oai:materialscloud.org:49"
    }, 
    "keywords": [
      "Machine learning", 
      "Synthesis", 
      "Optimisation", 
      "Genetic algorithms", 
      "Metal-Organic frameworks", 
      "Robotic synthesi", 
      "MARVEL"
    ], 
    "conceptrecid": "46", 
    "is_last": false, 
    "references": [
      {
        "type": "Journal reference", 
        "comment": "Article where the data is discussed", 
        "citation": "Seyed Mohamad Moosavi, Arunraj Chidambaram, Leopold Talirz, Maciej Haranczyk, Kyriakos C. Stylianou, Berend Smit. Submitted."
      }, 
      {
        "type": "Software", 
        "doi": "10.5281/zenodo.2531564", 
        "url": "", 
        "comment": "Web application for finding optimal synthesis conditions", 
        "citation": "Leopold Talirz, & SeyedMohamadMoosavi. (2019, January 4). ltalirz/sycofinder: Release for Materialscloud.org (Version v0.1.0). Zenodo."
      }
    ], 
    "publication_date": "Jan 04, 2019, 00:00:00", 
    "license": "Creative Commons Attribution 4.0 International", 
    "id": "49", 
    "description": "We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal organic framework. We define chemical intuition as the collection of unwritten guidelines used by synthetic chemists to find the right synthesis conditions. As (partially) failed experiments usually remain unreported, we have reconstructed a typical track of failed experiments in a successful search for finding the optimal synthesis conditions that yields HKUST-1 with the highest surface area reported to date. We illustrate the importance of quantifying this chemical intuition for the synthesis of novel materials.", 
    "version": 3, 
    "contributors": [
      {
        "affiliations": [
          "Laboratory of Molecular Simulation, Institut des Sciences et Inge\u0301nierie Chimiques, Valais, Ecole Polytechnique Fe\u0301de\u0301rale de Lausanne (EPFL), Rue de l\u2019Industrie 17, CH-1951 Sion, Switzerland"
        ], 
        "familyname": "Moosavi", 
        "givennames": "Seyed Mohamad"
      }, 
      {
        "affiliations": [
          "Laboratory of Molecular Simulation, Institut des Sciences et Inge\u0301nierie Chimiques, Valais, Ecole Polytechnique Fe\u0301de\u0301rale de Lausanne (EPFL), Rue de l\u2019Industrie 17, CH-1951 Sion, Switzerland"
        ], 
        "familyname": "Chidambaram", 
        "givennames": "Arunraj"
      }, 
      {
        "affiliations": [
          "Laboratory of Molecular Simulation, Institut des Sciences et Inge\u0301nierie Chimiques, Valais, Ecole Polytechnique Fe\u0301de\u0301rale de Lausanne (EPFL), Rue de l\u2019Industrie 17, CH-1951 Sion, Switzerland", 
          "Theory and simulation of materials (THEOS), Facult\u00e9 des Sciences et Techniques de l\u2019Ing\u00e9nieur, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), Station 9, CH-1015 Lausanne, Switzerland"
        ], 
        "familyname": "Talirz", 
        "givennames": "Leopold"
      }, 
      {
        "affiliations": [
          "IMDEA Materials Institute, C/Eric Kandel 2, 28906 Getafe, Madrid, Spain"
        ], 
        "familyname": "Haranczyk", 
        "givennames": "Maciej"
      }, 
      {
        "affiliations": [
          "Laboratory of Molecular Simulation, Institut des Sciences et Inge\u0301nierie Chimiques, Valais, Ecole Polytechnique Fe\u0301de\u0301rale de Lausanne (EPFL), Rue de l\u2019Industrie 17, CH-1951 Sion, Switzerland"
        ], 
        "familyname": "Stylianou", 
        "givennames": "Kyriakos C."
      }, 
      {
        "email": "berend.smit@epfl.ch", 
        "affiliations": [
          "Laboratory of Molecular Simulation, Institut des Sciences et Inge\u0301nierie Chimiques, Valais, Ecole Polytechnique Fe\u0301de\u0301rale de Lausanne (EPFL), Rue de l\u2019Industrie 17, CH-1951 Sion, Switzerland", 
          "Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720, United States"
        ], 
        "familyname": "Smit", 
        "givennames": "Berend"
      }
    ], 
    "edited_by": 98
  }, 
  "updated": "2019-01-04T00:00:00+00:00"
}