Bayesian data analysis reveals no preference for cardinal Tafel slopes in CO2 reduction electrocatalysis
The Tafel slope is a key parameter often quoted to characterize the efficacy of an electrochemical catalyst. In this paper, we develop a Bayesian data analysis approach to estimate the Tafel slope from experimentally-measured current-voltage data. Our approach obviates the human intervention require...
| Main Authors: | , , , |
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| Format: | Article |
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Springer Science and Business Media LLC
2021
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| Online Access: | https://hdl.handle.net/1721.1/132626 |
| _version_ | 1811074861429161984 |
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| author | Limaye, Aditya M Zeng, Joy Willard, Adam P. Manthiram, Karthish |
| author2 | Massachusetts Institute of Technology. Department of Chemical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Chemical Engineering Limaye, Aditya M Zeng, Joy Willard, Adam P. Manthiram, Karthish |
| author_sort | Limaye, Aditya M |
| collection | MIT |
| description | The Tafel slope is a key parameter often quoted to characterize the efficacy of an electrochemical catalyst. In this paper, we develop a Bayesian data analysis approach to estimate the Tafel slope from experimentally-measured current-voltage data. Our approach obviates the human intervention required by current literature practice for Tafel estimation, and provides robust, distributional uncertainty estimates. Using synthetic data, we illustrate how data insufficiency can unknowingly influence current fitting approaches, and how our approach allays these concerns. We apply our approach to conduct a comprehensive re-analysis of data from the CO₂ reduction literature. This analysis reveals no systematic preference for Tafel slopes to cluster around certain "cardinal values” (e.g. 60 or 120 mV/decade). We hypothesize several plausible physical explanations for this observation, and discuss the implications of our finding for mechanistic analysis in electrochemical kinetic investigations. |
| first_indexed | 2024-09-23T09:56:33Z |
| format | Article |
| id | mit-1721.1/132626 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T09:56:33Z |
| publishDate | 2021 |
| publisher | Springer Science and Business Media LLC |
| record_format | dspace |
| spelling | mit-1721.1/1326262022-09-26T14:45:08Z Bayesian data analysis reveals no preference for cardinal Tafel slopes in CO2 reduction electrocatalysis Limaye, Aditya M Zeng, Joy Willard, Adam P. Manthiram, Karthish Massachusetts Institute of Technology. Department of Chemical Engineering Massachusetts Institute of Technology. Department of Chemistry The Tafel slope is a key parameter often quoted to characterize the efficacy of an electrochemical catalyst. In this paper, we develop a Bayesian data analysis approach to estimate the Tafel slope from experimentally-measured current-voltage data. Our approach obviates the human intervention required by current literature practice for Tafel estimation, and provides robust, distributional uncertainty estimates. Using synthetic data, we illustrate how data insufficiency can unknowingly influence current fitting approaches, and how our approach allays these concerns. We apply our approach to conduct a comprehensive re-analysis of data from the CO₂ reduction literature. This analysis reveals no systematic preference for Tafel slopes to cluster around certain "cardinal values” (e.g. 60 or 120 mV/decade). We hypothesize several plausible physical explanations for this observation, and discuss the implications of our finding for mechanistic analysis in electrochemical kinetic investigations. National Science Foundation (Grants 1745302, 1955628) Air Force Office of Scientific Research (Award FA9550-18-1-0420) 2021-09-22T17:28:27Z 2021-09-22T17:28:27Z 2021-01 2020-11 Article http://purl.org/eprint/type/JournalArticle 2041-1723 https://hdl.handle.net/1721.1/132626 Limaye, Aditya M. "Bayesian data analysis reveals no preference for cardinal Tafel slopes in CO2 reduction electrocatalysis." Nature Communications 12, 1 (January 2021): 703 © 2021 The Author(s) https://doi.org/10.1038/s41467-021-20924-y Nature Communications Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf Springer Science and Business Media LLC Nature |
| spellingShingle | Limaye, Aditya M Zeng, Joy Willard, Adam P. Manthiram, Karthish Bayesian data analysis reveals no preference for cardinal Tafel slopes in CO2 reduction electrocatalysis |
| title | Bayesian data analysis reveals no preference for cardinal Tafel slopes in CO2 reduction electrocatalysis |
| title_full | Bayesian data analysis reveals no preference for cardinal Tafel slopes in CO2 reduction electrocatalysis |
| title_fullStr | Bayesian data analysis reveals no preference for cardinal Tafel slopes in CO2 reduction electrocatalysis |
| title_full_unstemmed | Bayesian data analysis reveals no preference for cardinal Tafel slopes in CO2 reduction electrocatalysis |
| title_short | Bayesian data analysis reveals no preference for cardinal Tafel slopes in CO2 reduction electrocatalysis |
| title_sort | bayesian data analysis reveals no preference for cardinal tafel slopes in co2 reduction electrocatalysis |
| url | https://hdl.handle.net/1721.1/132626 |
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