journal article·2022-10Open access

Predicting catalytic activity in hydrogen evolution reaction

Frederik C. Østergaard, Alexander Bagger, Jan Rossmeisl

Abstract

Hydrogen Evolution Reaction (HER) is a prototype simple catalytical reaction with only a few steps and species involved, nevertheless, several models have been attempted for predicting catalyst activity. This study seeks to use a data-first approach by fitting hydrogen and hydroxide adsorption energies , ΔE H and ΔE OH , as well as work functions obtained using DFT to experimental data and correlating the outcome models with possible mechanisms for HER in acidic and alkaline conditions. Statistical proof is given for the importance of the work function as a descriptor in both acidic and alkaline, explaining the overestimation of Cu activity by ΔE H volcano models and predicting its overpotential required for a 1 mA cm -2 current density correctly within 0.1 eV. An oxophobic HER pathway is identified in alkaline conditions.
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Research context

OpenAlex topics: Electrocatalysts for Energy Conversion · Metalloenzymes and iron-sulfur proteins · Machine Learning in Materials Science

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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