To
date, the understanding of reactions at solid–liquid
interfaces has proven challenging, mainly because of the inaccessible
nature of such systems to current experimental techniques with atomic
resolution. This has meant that many important features, including
free energy barriers and the atomistic structure of intermediates,
remain unknown. To tackle these issues, we construct and utilize a
high-dimensional neural network (HDNN) potential for the simulation
of hydrogen evolution at the HCl(aq)/Pt(111) interface, taking into
consideration the influence of adsorbate–adsorbate, adsorbate–solvent
interactions, and ion solvation explicitly. Long time scale MD simulations
reveal coadsorbed Had/H2Oad on the
surface. The free energy profiles for the Tafel and Heyrovsky type
hydrogen coupling are extracted using umbrella sampling. It is found
that the preferential mechanism can change depending on the surface
coverage, highlighting the dual mechanistic nature for HER on Pt(111).
Our work demonstrates the importance of controlling the solvent–substrate
interactions in developing catalysts beyond Pt.