2023 Roadmap on molecular modelling of electrochemical energy materials
Chao Zhang, Jun Cheng, Yiming Chen, Maria K. Y. Chan, Qiong Cai, Rodrigo P. Carvalho, Cleber F. N. Marchiori, Daniel Brandell, C. Moysés Araújo, Ming Chen, Xiangyu Ji, Guang Feng, Kateryna Goloviznina, Alessandra Serva, Mathieu Salanne, Toshihiko Mandai, Tomooki Hosaka, Mirna Alhanash, Patrik Johansson, Yunze Qiu, Hai Xiao, Michael Eikerling, Ryosuke Jinnouchi, Marko Melander, Georg Kastlunger, Assil Bouzid, Alfredo Pasquarello, Seung‐Jae Shin, Minho M. Kim, Hyungjun Kim, Kathleen Schwarz, Ravishankar Sundararaman
Abstract
Abstract New materials for electrochemical energy storage and conversion are the key to the electrification and sustainable development of our modern societies. Molecular modelling based on the principles of quantum mechanics and statistical mechanics as well as empowered by machine learning techniques can help us to understand, control and design electrochemical energy materials at atomistic precision. Therefore, this roadmap, which is a collection of authoritative opinions, serves as a gateway for both the experts and the beginners to have a quick overview of the current status and corresponding challenges in molecular modelling of electrochemical energy materials for batteries, supercapacitors, CO 2 reduction reaction, and fuel cell applications.