What do we talk about, when we talk about single-crystal termination-dependent selectivity of Cu electrocatalysts for CO₂ reduction? A data-driven retrospective

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{
  "created": "2022-09-22T14:18:08.767013+00:00", 
  "metadata": {
    "references": [
      {
        "citation": "K. Rossi, submitted (2022)", 
        "type": "Preprint"
      }
    ], 
    "mcid": "2022.121", 
    "id": "1483", 
    "is_last": false, 
    "title": "What do we talk about, when we talk about single-crystal termination-dependent selectivity of Cu electrocatalysts for CO<sub>2</sub> reduction? A data-driven retrospective", 
    "publication_date": "Sep 26, 2022, 17:16:11", 
    "edited_by": 578, 
    "_oai": {
      "id": "oai:materialscloud.org:1483"
    }, 
    "version": 1, 
    "description": "We mine from the literature experimental data on the CO<sub>2</sub> electrochemical reduction selectivity of Cu single crystal surfaces. We then probe the accuracy of a machine learning model trained to predict Faradaic Efficiencies for 11 CO<sub>2</sub>RR products, as a function of the applied voltage at which the reaction takes place, and the relative amounts of non equivalent surface sites, distinguished according to their nominal coordination. A satisfactory model accuracy is found only when discriminating data according to their provenance. On one hand, this result points at a qualitative agreement across reported experimental CO<sub>2</sub>RR  trends for single-crystal surfaces with well-defined terminations. On the other, this finding hints at the presence of differences in nominally identical catalysts and/or CO<sub>2</sub>RR measurements, which result in quantitative disagreement between experiments.", 
    "status": "published", 
    "license_addendum": null, 
    "keywords": [
      "catalysis", 
      "co2", 
      "cu", 
      "gaussian process"
    ], 
    "license": "Creative Commons Attribution 4.0 International", 
    "owner": 132, 
    "contributors": [
      {
        "affiliations": [
          "Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1951 Sion, Valais, Switzerland"
        ], 
        "familyname": "Rossi", 
        "email": "kevin.rossi@epfl.ch", 
        "givennames": "Kevin"
      }
    ], 
    "conceptrecid": "1482", 
    "doi": "10.24435/materialscloud:44-pc", 
    "_files": [
      {
        "size": 237, 
        "key": "README.txt", 
        "description": "readme", 
        "checksum": "md5:9badd04bd98c34bf19ff184de8a5dfc4"
      }, 
      {
        "size": 4840343, 
        "key": "dd_co2_cu.tar.xz", 
        "description": "data and notebooks", 
        "checksum": "md5:721f2607cc194c21ff29761ec1b22d44"
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    ]
  }, 
  "id": "1483", 
  "updated": "2023-02-23T13:39:40.355208+00:00", 
  "revision": 5
}