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Shin, Seung-Jae
THeoretical Energy Materials Modelling for Engineering & Science
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2023 Roadmap on molecular modelling of electrochemical energy materials

Author(s)
Zhang, ChaoCheng, JunChen, YimingChan, Maria K. Y.Cai, QiongCarvalho, Rodrigo P.Marchiori, Cleber F. N.Brandell, DanielAraujo, C. MoysesChen, MingJi, XiangyuFeng, GuangGoloviznina, KaterynaServa, AlessandraSalanne, MathieuMandai, ToshihikoHosaka, TomookiAlhanash, MirnaJohansson, PatrikQiu, Yun-ZeXiao, HaiEikerling, MichaelJinnouchi, RyosukeMelander, Marko M.Kastlunger, GeorgBouzid, AssilPasquarello, AlfredoShin, Seung-JaeKim, Minho M.Kim, HyungjunSchwarz, KathleenSundararaman, Ravishankar
Issued Date
2023-10
DOI
10.1088/2515-7655/acfe9b
URI
https://scholarworks.unist.ac.kr/handle/201301/84007
Citation
JOURNAL OF PHYSICS-ENERGY, v.5, no.4, pp.041501
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, CO2 reduction reaction, and fuel cell applications.
Publisher
IOP Publishing Ltd
ISSN
2515-7655
Keyword (Author)
density-functional theorymolecular dynamics simulationelectrochemical energy storagemachine learningelectrocatalysiselectrochemical interfaces
Keyword
DENSITY-FUNCTIONAL THEORYORGANIC ELECTRODE MATERIALSSINGLE-ATOM CATALYSTSSTRUCTURE-PROPERTY RELATIONSHIPSDOUBLE-LAYERIONIC LIQUIDSCO2 REDUCTION1ST-PRINCIPLES SIMULATIONDYNAMICS SIMULATIONSREACTION-MECHANISMS

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