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
(National Institute for Materials Science (NIMS))
;
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
Description:
(abstract)Overall, this roadmap originating from 20 groups in 11 countries 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, CO2RR, and fuel cell applications. It is not intended to be a comprehensive review, rather they are opinions of leading experts in their respective domains. Therefore, topics such as solid electrolytes (both ceramic and polymer), descriptor engineering of electrocatalysts and their ML discovery, are not included in this collection and can be found elsewhere.
Rights:
Keyword: electrochemical interfaces, density-functional theory, molecular dynamics simulation, electrochemical energy storage, machine learning, electrocatalysis
Date published: 2023-10-01
Publisher: IOP Publishing
Journal:
Funding:
Manuscript type: Publisher's version (Version of record)
MDR DOI:
First published URL: https://doi.org/10.1088/2515-7655/acfe9b
Related item:
Other identifier(s):
Contact agent:
Updated at: 2024-03-22 00:53:39 +0900
Published on MDR: 2024-03-05 16:30:28 +0900
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74_Roadmap_J Phys Energy 2023_Roadmap on molecular modelling of electrochemical energy materials.pdf
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