Abstract 

Electrochemical interfaces are central to energy conversion, catalysis, and storage, but also provide a rich arena for fundamental physics. Order–disorder transitions, electrochemical potentials, current–potential relations, and screening connect them to statistical mechanics, semiconductor physics, and condensed matter theory. I will discuss these concepts at reactive, electrified interfaces using first-principles simulations.

A first central question to be adressed is the appropriate ensemble for describing a reactive quantum system in contact with an electron reservoir—the electrode. Since experiments control electrode potential rather than charge, I will present our electronically grand-canonical framework for DFT-based atomistic simulations and contrast it with fixed-electron-number approaches. Applications include potential-dependent adsorption, cyclic voltammetry, interfacial phase transitions, and electron-transfer barriers.

I will then focus on metal–water interfaces, demonstrating how ab initio molecular dynamics reveal previously underestimated effects from quantum-mechanical, electronic charge redistribution at the interface that give rise to specific capacitive response features. 

Finally, I will outline my research programme on machine-learned interatomic potentials for electrified interfaces. Our RAZOR model incorporates external bias by learning response coefficients that are related to Born effective charges. RAZOR enables potential-dependent molecular dynamics and free-energy sampling at ab initio accuracy and its theoretical foundation connects electrochemical interface theory to the language of condensed matter physics. Advancing this connection will be one central goal of my anticipated Habilitation in the Physics Department at FU Berlin.