<?xml version='1.0' encoding='utf-8'?> <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"> <dc:creator>Rossi, Kevin</dc:creator> <dc:date>2023-02-23</dc:date> <dc:description>We mine from the literature experimental data on the CO2 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 CO2RR 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 CO2RR 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 CO2RR measurements, which result in quantitative disagreement between experiments.</dc:description> <dc:identifier>https://archive.materialscloud.org/record/2023.28</dc:identifier> <dc:identifier>doi:10.24435/materialscloud:nd-50</dc:identifier> <dc:identifier>mcid:2023.28</dc:identifier> <dc:identifier>oai:materialscloud.org:1658</dc:identifier> <dc:language>en</dc:language> <dc:publisher>Materials Cloud</dc:publisher> <dc:rights>info:eu-repo/semantics/openAccess</dc:rights> <dc:rights>Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights> <dc:subject>catalysis</dc:subject> <dc:subject>co2</dc:subject> <dc:subject>cu</dc:subject> <dc:subject>gaussian process</dc:subject> <dc: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</dc:title> <dc:type>Dataset</dc:type> </oai_dc:dc>