2023 Roadmap on molecular modelling of electrochemical energy materials

Chao Zhang , Jun Cheng , Yiming Chen , Maria Chan , Qiong Cai , Rodrigo Carvalho , Cleber Marchiori , Daniel Brandell , C Moyses Araujo , Ming Chen , Xiangyu Ji , Guang Feng , Kateryna Goloviznina , Alessandra Serva , Mathieu Salanne , Toshihiko Mandai , Tomooki Hosaka , Mirna Alhanash , Patrik Johansson , Yun-Ze Qiu , Hai Xiao , Michael Eikerling , Ryosuke Jinnouchi , Marko Melander , Georg Kastlunger , Assil Bouzid (1, 2) , Alfredo Pasquarello , Seung-Jae Shin , Minho Kim , Hyungjun Kim , Kathleen Schwarz , Ravishankar Sundararaman

1 IRCER-AXE3 - IRCER - Axe 3 : organisation structurale multiéchelle des matériaux
2 IRCER - Institut de Recherche sur les CERamiques

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.

Keywords: electrochemical interfaces; density-functional theory; molecular dynamics simulation; electrochemical energy storage; machine learning; electrocatalysis

Domains: Material chemistry; Catalysis; Theoretical and/or physical chemistry

Chao Zhang, Jun Cheng, Yiming Chen, Maria Chan, Qiong Cai, et al.. 2023 Roadmap on molecular modelling of electrochemical energy materials. JPhys Energy, 2023, 5 (4), pp.041501. ⟨10.1088/2515-7655/acfe9b⟩. ⟨hal-04267648⟩