2023 Roadmap on molecular modelling of electrochemical energy materials

2023 Roadmap on molecular modelling of electrochemical energy materials

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 h...

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Bibliographic Details
Main Authors: Chao Zhang, Jun Cheng, Yiming Chen, Maria K Y Chan, Qiong Cai, Rodrigo P Carvalho, Cleber F N 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 M Melander, Georg Kastlunger, Assil Bouzid, Alfredo Pasquarello, Seung-Jae Shin, Minho M Kim, Hyungjun Kim, Kathleen Schwarz, Ravishankar Sundararaman
Format: Article
Language:English
Published: IOP Publishing 2023-01-01
Series:JPhys Energy
Subjects:
electrochemical interfaces
density-functional theory
molecular dynamics simulation
electrochemical energy storage
machine learning
electrocatalysis
Online Access:https://doi.org/10.1088/2515-7655/acfe9b

Internet

https://doi.org/10.1088/2515-7655/acfe9b

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