Quantifying key factors for optimised manufacturing of Li-ion battery anode and cathode via artificial intelligence-Reference-Cited by-同舟云学术

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Quantifying key factors for optimised manufacturing of Li-ion battery anode and cathode via artificial intelligence

Published:2022-01 Issue: Volume:7 Page:100129
ISSN:2666-5468
Container-title:Energy and AI
language:en
Short-container-title:Energy and AI

Author:

Niri Mona Faraji,Liu Kailong,Apachitei Geanina,Román-Ramírez Luis A.A,Lain Michael,Widanage Dhammika,Marco James

Funder

Faraday Institution

Publisher

Elsevier BV

Subject

Artificial Intelligence,General Energy,Engineering (miscellaneous)

Reference64 articles.

1. Battery materials for low-cost electric transportation;Turcheniuk;Mater Today,2021

2. The future cost of electrical energy storage based on experience rates;Schmidt;Nature Energy,2017

3. K. Edström, “ Battery 2030+ roadmap,” 2020.

4. A bottom-up approach to lithium-ion battery cost modeling with a focus on cathode active materials,”;Wentker;Energies,2019

5. Cost projection of state of the art lithium-ion batteries for electric vehicles up to 2030;Berckmans;Energies,2017

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