Predicting Electrocatalytic Activation Barriers from Grand Canonical Density Functional Theory

Modeling electrocatalytic activation barriers is challenging due to the complex interplay between the reaction intermediates, solvation, and electrification within the electrochemical double layer. While efforts toward incorporating these complexities within DFT models are available, the sensitivities of reaction paths and activation barriers to modeling choices has received less attention. Here, we review the development of explicit and analytical grand canonical DFT models to incorporate electrochemical double layer (EDL) features when identifying elementary electrochemical reaction transition states. The analytical grand canonical DFT (aGC-DFT) framework is used to isolate modeling considerations for electrocatalytic barriers, specifically the local reaction path and EDL features. Reaction paths with large dipole moment changes have activation barriers that are highly sensitive to EDL properties, resulting in both uncertainties in predicting electrocatalytic rates and opportunities to tune kinetics using EDL design. We emphasize the need for future studies to investigate the structure and dynamic properties of the electrode–electrolyte interface, and discuss best practices for modeling electrocatalytic barriers using grand canonical DFT approaches.

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Publication Details

Journal
The Journal of Physical Chemistry C
Published
2025-11-13
DOI
https://doi.org/10.1021/acs.jpcc.5c05723
Primary Topic
Electrocatalysts for Energy Conversion
Type
article
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article

Predicting Electrocatalytic Activation Barriers from Grand Canonical Density Functional Theory

Soumya Chatterjee, Danny Z. Zhu, Andrew Jark-Wah Wong, Michael John Janik
The Journal of Physical Chemistry C
Electrocatalysts for Energy Conversion
article

Predicting Electrocatalytic Activation Barriers from Grand Canonical Density Functional Theory

Soumya Chatterjee, Danny Z. Zhu, Andrew Jark-Wah Wong, Michael John Janik
article en

Abstract

Modeling electrocatalytic activation barriers is challenging due to the complex interplay between the reaction intermediates, solvation, and electrification within the electrochemical double layer. While efforts toward incorporating these complexities within DFT models are available, the sensitivities of reaction paths and activation barriers to modeling choices has received less attention. Here, we review the development of explicit and analytical grand canonical DFT models to incorporate electrochemical double layer (EDL) features when identifying elementary electrochemical reaction transition states. The analytical grand canonical DFT (aGC-DFT) framework is used to isolate modeling considerations for electrocatalytic barriers, specifically the local reaction path and EDL features. Reaction paths with large dipole moment changes have activation barriers that are highly sensitive to EDL properties, resulting in both uncertainties in predicting electrocatalytic rates and opportunities to tune kinetics using EDL design. We emphasize the need for future studies to investigate the structure and dynamic properties of the electrode–electrolyte interface, and discuss best practices for modeling electrocatalytic barriers using grand canonical DFT approaches.

The Journal of Physical Chemistry CVol. 129(47)
Pennsylvania State University (US)
Openalex Percentile: Top 73%
Electrocatalysts for Energy Conversion
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Predicting Electrocatalytic Activation Barriers from Grand Canonical Density Functional Theory — Soumya Chatterjee, Danny Z. Zhu, et al. · The Journal of Physical Chemistry C (2025) | TGRS Research Map | TGRS