Tuning water dissociation at oxide–electrolyte interfaces with electric fields

Research output: Contribution to journalArticlepeer-review

Abstract

Understanding how electric fields influence water dissociation at heterogeneous interfaces is crucial for controlling interfacial chemical reactions and advancing next-generation energy technologies. Herein, ab initio–based machine learning simulations show that even small electric field changes can significantly alter the water dissociation fraction at planar TiO2–electrolyte interfaces. The resulting free energy difference between undissociated and dissociated interfacial water exhibits a linear dependence on the field change with a slope of 1.97 eÅ, which far exceeds the dissociation-induced dipole change of a water molecule. Employing a machine-learned collective variable to investigate the reaction statistics of thousands of water dissociation/recombination events, we find that small electric field changes exert minor effects on individual reaction energy barriers but significantly influence the populations of local configurations associated with initial states that are most favorable for reactions. These findings elucidate the pronounced impact of electric fields on interfacial water dissociation and reveal a mechanism for electric-field-controlled chemical reactions.

Original languageEnglish (US)
Article numbere2505929122
JournalProceedings of the National Academy of Sciences of the United States of America
Volume122
Issue number34
DOIs
StatePublished - Aug 26 2025

All Science Journal Classification (ASJC) codes

  • General

Keywords

  • electrochemistry
  • machine learning
  • molecular dynamics

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