2023 Roadmap on molecular modelling of electrochemical energy materials
Review article, 2023

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.

electrochemical interfaces

machine learning

molecular dynamics simulation

density-functional theory

electrochemical energy storage

electrocatalysis

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Published in

JPhys Energy

2515-7655 (eISSN)

Vol. 5 Issue 4 art. no 041501

Research Project(s)

Battery Interface Genome - Materials Acceleration Platform - BIG-MAP

European Commission (EC) (EC/H2020/957189), 2020-09-01 -- 2023-08-31.

Categorizing

Subject Categories (SSIF 2011)

Energy Engineering

Materials Chemistry

Identifiers

DOI

10.1088/2515-7655/acfe9b

More information

Latest update

12/1/2023