報告摘要

Proton-coupled electron transfer (PCET) is the key step for energy conversion in electrocatalysis. Atomic-scale simulation performs as an indispensable tool to provide 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 an integrated 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 (HER) at room temperature, and provides a physical picture that 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 on other types of PCET reactions in broader scenarios of energy conversion processes.

報告人簡介

許審鎮，beat365材料科學與工程學院研究員（2020年9月至今），2011年本科畢業于清華大學物理系，2017年博士畢業于美國威斯康星大學麥迪遜分校（導師：Prof. Dane Morgan），2017-2020在美國普林斯頓大學開展博士後研究（導師：Prof. Emily Carter）。主要從事電化學體系表界面過程的計算模拟及方法開發工作。2022年2月至今在北京科學智能研究院（AISI）兼職負責電池材料理論計算團隊。回國後以通訊作者身份在J. Am. Chem. Soc./ J. Phys. Chem. Lett./ J. Chem. Theory Comput./Adv. Funct. Mater./ACS Catal./npj Comput. Mater.等期刊發表論文十餘篇，承擔或參與多項國家、企業科研項目，并于2022年入選國家海外高層次人才引進計劃青年項目。