Machine learning for renewable energy materials

Journal: Journal of Materials Chemistry A • • Royal Society of Chemistry • ISSN: 2050-7488

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.

Subjects & Keywords

How to Cite this Article

Geun Ho Gu, Juhwan Noh, I. P. Kim, et al. (2019). "Machine learning for renewable energy materials". Journal of Materials Chemistry A. https://doi.org/10.1039/c9ta02356a