In recent years, implicit solvation approaches have experienced a renaissance in the context of interfacial electrochemistry, not least because in conjunction with ab initio thermodynamics they allow to mimic the polarization of the electrode at potentials beyond the PZC. In this talk, I will survey this context and corresponding fully-grand canonical (FGC) calculations. Specifically, I will discuss the application to compute thermodynamic cyclic voltammograms (CVs) and demonstrate that only FGC calculations are able to capture non-Nernstian peak shifts and other double layer-effects on the CV shape. Relevant for catalysis is in particular the ability to predict potential-induced variations of adsorption energies and concomitant effects on detailed reaction mechanisms. The use of machine-learned potentials finally opens the door toward predictive-quality explicit solvation simulations and global geometry optimization to address a potential operando evolution of the electrode.
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