报告摘要

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.

报告人简介

许审镇，永利集团材料科学与工程学院研究员（2020年9月至今），2011年本科毕业于清华大学物理系，2017年博士毕业于美国威斯康星大学麦迪逊分校（导师：Prof. Dane Morgan），2017-2020在美国普林斯顿大学开展博士后研究（导师：Prof. Emily Carter）。主要从事电化学体系表界面过程的计算模拟及方法开发工作。2022年2月至今在北京科学智能研究院（AISI）兼职负责电池材料理论计算团队。回国后以通讯作者身份在J. Am. Chem. Soc./ J. Phys. Chem. Lett./ J. Chem. Theory Comput./Adv. Funct. Mater./ACS Catal./npj Comput. Mater.等期刊发表论文十余篇，承担或参与多项国家、企业科研项目，并于2022年入选国家海外高层次人才引进计划青年项目。