First-principles Prediction of the Absolute Standard Hydrogen Electrode Potential

A study conducted by Ryosuke Jinnouchi et al., in collaboration with Universität Wien and VASP Software GmbH, was published in Chemical Science.

The half-cell potential of the electrode in batteries, fuel cells and electrolytic cells is intrinsic to its structure and composition, determining the cell voltage and reaction rate at the electrode. To understand the state of an electrode, its potential must be measured relative to a defined reference. The most fundamental reference is the absolute standard hydrogen electrode potential (ASHEP)¹⁾. However, determining this reference using first-principles calculations has remained an unresolved challenge and represents a major obstacle in theoretically establishing the absolute reference for the electrode potential.

In this study, we extended our previously developed machine learning-aided first-principles method for calculating redox potentials to precisely compute the ASHEP. This advancement enables the accurate establishment of the reference potential, allowing electrode properties to be investigated with precision through first-principles calculations. This method was applied to the oxygen reduction reaction in polymer electrolyte fuel cells, where it elucidated a mechanism for enhancing catalytic activity. Specifically, it demonstrated that attaching organic molecules to Pt catalysts disrupts the hydrogen-bonding network near the electrode, leading to improved catalytic activity²⁾.

1). The electronic potential relative to the vacuum level at which hydrogen gas and protons in an aqueous solution are in equilibrium under the standard state.
2). Jinnouchi, R., Minami, S. The Journal of Physical Chemistry Letters. 2025, vol.16, pp.265–273.
(https://doi.org/10.1021/acs.jpclett.4c03437).

Title: Absolute Standard Hydrogen Electrode Potential and Redox Potentials of Atoms and Molecules: Machine Learning Aided First Principles Calculations
Authors: Jinnouchi, R., Karsai, F., Kresse, G.
Journal Name: Chemical Science
Published: December 23, 2024 (online)
https://doi.org/10.1039/D4SC03378G