Machine Learning Screening of Metal-Ion Battery Electrode Materials-Reference-Cited by-同舟云学术

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Machine Learning Screening of Metal-Ion Battery Electrode Materials

Published:2021-06-23 Issue:45 Volume:13 Page:53355-53362
ISSN:1944-8244
Container-title:ACS Applied Materials & Interfaces
language:en
Short-container-title:ACS Appl. Mater. Interfaces

Author:

Moses Isaiah A.¹,Joshi Rajendra P.²,Ozdemir Burak³^ORCID,Kumar Neeraj²^ORCID,Eickholt Jesse⁴,Barone Veronica¹⁵^ORCID

Affiliation:

1. Science of Advanced Materials Program, Central Michigan University, Mount Pleasant, Michigan 48859, United States

2. Pacific Northwest National Laboratory, Richland, Washington 99352, United States

3. Department of Physics, Faculty of Science, University of Ostrava, 30 dubna 22, 70103 Ostrava, Czech Republic

4. Department of Computer Science, Central Michigan University, Mount Pleasant, Michigan 48859, United States

5. Department of Physics, Central Michigan University, Mount Pleasant, Michigan 48859, United States

Funder

U.S. Department of Energy

Publisher

American Chemical Society (ACS)

Subject

General Materials Science

Link

https://pubs.acs.org/doi/pdf/10.1021/acsami.1c04627

Reference59 articles.

1. Alternative energy technologies

2. Electrical Energy Storage for the Grid: A Battery of Choices

3. Functional Materials for Rechargeable Batteries

4. Tarascon, J.M.; Armand, M. Materials for Sustainable Energy: A Collection of Peer-reviewed Research and Review Articles from Nature Publishing Group; World Scientific, 2011; pp 171–179.

5. Li-ion battery materials: present and future

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