  Proton-coupled electron transfer (PCET) is the key step for energy conversion
in electrocatalysis. Atomic-scale simulation acts as an indispensable tool to
provide a microscopic understanding of PCET. However, consideration of the
quantum nature of transferring protons under an exact grand canonical (GC)
constant potential condition is a great challenge for theoretical
electrocatalysis. Here, we develop a unified computational framework to
explicitly treat nuclear quantum effects (NQEs) by a sufficient GC sampling,
further assisted by a machine learning force field adapted for electrochemical
conditions. Our work demonstrates a non-negligible impact of NQEs on PCET
simulations for hydrogen evolution reaction at room temperature, and provides a
physical picture that wave-like quantum characteristic of the transferring
protons facilitates the particles to tunnel through classical barriers in PCET
paths, leading to a remarkable activation energy reduction compared to
classical simulations. Moreover, the physical insight of proton tunneling may
reshape our fundamental understanding of other types of PCET reactions in
broader scenarios of energy conversion processes.
