Journal of Materials Chemistry A and Materials Advances Editor's choice web collection: “Machine learning for materials innovation”
Abstract
A graphical abstract is available for this content
Maintenance work is planned from 09:00 BST to 12:00 BST on Saturday 28th September 2024.
During this time the performance of our website may be affected - searches may run slowly, some pages may be temporarily unavailable, and you may be unable to access content. If this happens, please try refreshing your web browser or try waiting two to three minutes before trying again.
We apologise for any inconvenience this might cause and thank you for your patience.
* Corresponding authors
a
School of Materials Science and Engineering, Institute of New Energy Material Chemistry, Nankai University, Tianjin 300350, China
E-mail:
zhouzhen@nankai.edu.cn
b
Engineering Research Center of Advanced Functional Material Manufacturing of Ministry of Education, School of Chemical Engineering, Zhengzhou University, Zhengzhou 450001, China
E-mail:
zhenzhou@zzu.edu.cn
A graphical abstract is available for this content
Z. Zhou, Mater. Adv., 2021, 2, 825 DOI: 10.1039/D0MA90054K
This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.
Read more about how to correctly acknowledge RSC content.
Fetching data from CrossRef.
This may take some time to load.
Loading related content