Machine-Learning Approaches for the Discovery of Electrolyte Materials for Solid-State Lithium Batteries
Author:
Affiliation:
1. Department of Materials, Imperial College London, London SW7 2AZ, UK
2. The Faraday Institution, Quad One, Becquerel Ave, Harwell Campus, Didcot OX11 0RA, UK
3. Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot OX11 0FA, UK
Abstract
Funder
EPSRC UKRI Innovation Fellowship
Faraday Institution Industry Fellowship
Faraday Institution Training Grant
Imperial College London UKRI Impact Acceleration Account
Publisher
MDPI AG
Subject
Electrical and Electronic Engineering,Electrochemistry,Energy Engineering and Power Technology
Link
https://www.mdpi.com/2313-0105/9/4/228/pdf
Reference103 articles.
1. Assad, M., and Rosen, M.A.A. (2021). Design and Performance Optimization of Renewable Energy Systems, Elsevier.
2. Sustainable Electric Vehicle Batteries for a Sustainable World: Perspectives on Battery Cathodes, Environment, Supply Chain, Manufacturing, Life Cycle, and Policy;Yang;Adv. Energy Mater.,2022
3. A Review on Lithium-Ion Batteries Safety Issues: Existing Problems and Possible Solutions;Wen;Mater. Express,2012
4. Pigłowska, M., Kurc, B., Galiński, M., Fuć, P., Kamińska, M., Szymlet, N., and Daszkiewicz, P. (2021). Challenges for Safe Electrolytes Applied in Lithium-Ion Cells—A Review. Materials, 14.
5. Reviving the Lithium Metal Anode for High-Energy Batteries;Lin;Nat. Nanotechnol.,2017
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