Chao Zhang, Jun Cheng, Yiming Chen, Maria 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, Yunze Qiu, Hai Xiao, Michael H Eikerling, Ryosuke Jinnouchi, Marko M Melander, Georg Kastlunger, Assil Bouzid, Alfredo Pasquarello, Seung-Jae Shin, Minho M Kim, Hyungjun Kim, Kathleen Schwarz, Ravishankar Sundararaman
{"title":"2023 roadmap on molecular modelling of electrochemical energy materials","authors":"Chao Zhang, Jun Cheng, Yiming Chen, Maria 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, Yunze Qiu, Hai Xiao, Michael H Eikerling, Ryosuke Jinnouchi, Marko M Melander, Georg Kastlunger, Assil Bouzid, Alfredo Pasquarello, Seung-Jae Shin, Minho M Kim, Hyungjun Kim, Kathleen Schwarz, Ravishankar Sundararaman","doi":"10.1088/2515-7655/acfe9b","DOIUrl":null,"url":null,"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.","PeriodicalId":48500,"journal":{"name":"Journal of Physics-Energy","volume":"80 1","pages":"0"},"PeriodicalIF":7.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Physics-Energy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/2515-7655/acfe9b","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 1
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.
期刊介绍:
The Journal of Physics-Energy is an interdisciplinary and fully open-access publication dedicated to setting the agenda for the identification and dissemination of the most exciting and significant advancements in all realms of energy-related research. Committed to the principles of open science, JPhys Energy is designed to maximize the exchange of knowledge between both established and emerging communities, thereby fostering a collaborative and inclusive environment for the advancement of energy research.