Machine learning for renewable energy materials-Reference-Cited by-同舟云学术

Machine learning for renewable energy materials

Published:2019 Issue:29 Volume:7 Page:17096-17117
ISSN:2050-7488
Container-title:Journal of Materials Chemistry A
language:en
Short-container-title:J. Mater. Chem. A

Author:

Gu Geun Ho¹²³⁴,Noh Juhwan¹²³⁴^ORCID,Kim Inkyung¹²³⁴^ORCID,Jung Yousung¹²³⁴^ORCID

Affiliation:

1. Graduate School of EEWS

2. Korea Advanced Institute of Science and Technology (KAIST)

3. Daejeon

4. South Korea

Abstract

Achieving the 2016 Paris agreement goal of limiting global warming below 2 °C and securing a sustainable energy future require materials innovations in renewable energy technologies. Machine learning has demonstrated many successes to accelerate the discovery renewable energy materials.

Funder

KAIST

National Research Foundation of Korea

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2019/TA/C9TA02356A

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