A data-driven perspective on the colours of metal-organic frameworks


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{
  "id": "530", 
  "metadata": {
    "title": "A data-driven perspective on the colours of metal-organic frameworks", 
    "doi": "10.24435/materialscloud:cc-j6", 
    "license": "Creative Commons Attribution 4.0 International", 
    "keywords": [
      "LSMO", 
      "MARVEL", 
      "EPFL", 
      "ERC", 
      "ML", 
      "Color"
    ], 
    "contributors": [
      {
        "affiliations": [
          "Laboratory of Molecular Simulation, Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1951 Sion, Valais, Switzerland"
        ], 
        "familyname": "Jablonka", 
        "email": "kevin.jablonka@epfl.ch", 
        "givennames": "Kevin Maik"
      }, 
      {
        "affiliations": [
          "Laboratory of Molecular Simulation, Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1951 Sion, Valais, Switzerland"
        ], 
        "familyname": "Moosavi", 
        "givennames": "Seyed Mohamad"
      }, 
      {
        "affiliations": [
          "Institute of Mechanical Engineering (IGM), School of Engineering (STI), \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL),  CH\u20101015 Lausanne, Switzerland", 
          "Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1951 Sion, Valais, Switzerland"
        ], 
        "familyname": "Asgari", 
        "givennames": "Mehrdad"
      }, 
      {
        "affiliations": [
          "Laboratory of Molecular Simulation, Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1951 Sion, Valais, Switzerland"
        ], 
        "familyname": "Ireland", 
        "givennames": "Christopher"
      }, 
      {
        "affiliations": [
          "Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL),  CH\u20101015 Lausanne, Vaud, Switzerland"
        ], 
        "familyname": "Patiny", 
        "givennames": "Luc"
      }, 
      {
        "affiliations": [
          "Laboratory of Molecular Simulation, Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1951 Sion, Valais, Switzerland"
        ], 
        "familyname": "Smit", 
        "email": "berend.smit@epfl.ch", 
        "givennames": "Berend"
      }
    ], 
    "_files": [
      {
        "description": "README with detailed description of the contents of the zip", 
        "checksum": "md5:7d1f961bfefc2e8bc567eadf30a48eec", 
        "size": 2056, 
        "key": "README.txt"
      }, 
      {
        "description": "Archive containing the dataset, the models and the feature importance data", 
        "checksum": "md5:b124f411ed37add72e4881f4fd13724a", 
        "size": 925552902, 
        "key": "Archive.zip"
      }
    ], 
    "references": [
      {
        "type": "Journal reference", 
        "citation": "K. M. Jablonka, S. M. Moosavi, M. Asgari, C. Ireland, L. Patiny, B. Smit, submitted."
      }, 
      {
        "type": "Preprint", 
        "doi": "10.26434/chemrxiv.13033217.v1", 
        "citation": "K. M. Jablonka, S. M. Moosavi, M. Asgari, C. Ireland, L. Patiny, B. Smit, ChemRxiv (2020).", 
        "url": "https://chemrxiv.org/articles/preprint/A_Data-Driven_Perspective_on_the_Colours_of_Metal-Organic_Frameworks/13033217"
      }
    ], 
    "conceptrecid": "529", 
    "version": 1, 
    "edited_by": 100, 
    "id": "530", 
    "owner": 70, 
    "mcid": "2020.163", 
    "is_last": true, 
    "status": "published", 
    "description": "Colour is at the core of chemistry and has been fascinating humans since ancient times. It is also a key descriptor of optoelectronic properties of materials and is used to assess the success of a synthesis. \nHowever, predicting the colour of a material based on its structure is challenging.\nIn this work, we leverage subjective and categorical human assignments of colours to build a model that can predict the colour of compounds on a continuous scale, using chemically meaningful reasoning.\nIn the process of developing the model, we also uncover inadequacies in current reporting mechanisms. \nFor example, we show that the majority of colour assignments are subject to perceptive spread that would not comply with common printing standards. \nTo remedy this, we suggest and implement an alternative way of reporting colour that is more suitable for a data-driven approach to materials science.", 
    "license_addendum": null, 
    "_oai": {
      "id": "oai:materialscloud.org:530"
    }, 
    "publication_date": "Dec 22, 2020, 10:16:27"
  }, 
  "revision": 5, 
  "updated": "2020-12-22T09:16:27.200225+00:00", 
  "created": "2020-09-17T19:33:00.777806+00:00"
}