Kevin Rossi^1*

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), https://doi.org/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.

Materials Cloud sections using this data

Files

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

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External references

Keywords

catalysis co2 cu gaussian process