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

Kevin Rossi1*

1 Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), CH-1951 Sion, Valais, Switzerland

* Corresponding authors emails: kevin.rossi@epfl.ch
DOI10.24435/materialscloud:44-pc [version v1]

Publication date: Sep 26, 2022

How to cite this record

Kevin Rossi, What do we talk about, when we talk about single-crystal termination-dependent selectivity of Cu electrocatalysts for CO2 reduction? A data-driven retrospective, Materials Cloud Archive 2022.121 (2022), doi: 10.24435/materialscloud:44-pc.

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.

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README.txt
MD5md5:9badd04bd98c34bf19ff184de8a5dfc4
237 Bytes readme
dd_co2_cu.tar.xz
MD5md5:721f2607cc194c21ff29761ec1b22d44
4.6 MiB data and notebooks

License

Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

External references

Preprint
K. Rossi, submitted (2022)

Keywords

catalysis co2 cu gaussian process

Version history:

2022.121 (version v1) [This version] Sep 26, 2022 DOI10.24435/materialscloud:44-pc