Machine Learning (ML)‐Assisted Design and Fabrication for Solar Cells-Reference-Cited by-同舟云学术

Machine Learning (ML)‐Assisted Design and Fabrication for Solar Cells

Published:2019-09-17 Issue:4 Volume:2 Page:280-291
ISSN:2575-0356
Container-title:ENERGY & ENVIRONMENTAL MATERIALS
language:en
Short-container-title:Energy Environ. Mater.

Author:

Li Fan¹,Peng Xiaoqi¹,Wang Zuo²,Zhou Yi²,Wu Yuxia¹,Jiang Minlin¹^ORCID,Xu Min³

Affiliation:

1. Institute of Advanced Study Nanchang University Nanchang Jiangxi 330031 China

2. School of Information Engineering Nanchang University Nanchang Jiangxi 330031 China

3. Department of Computational Biology Carnegie Mellon University Pittsburgh PA 15213 USA

Funder

Nanchang University

Publisher

Wiley

Subject

Energy (miscellaneous),Waste Management and Disposal,Environmental Science (miscellaneous),Water Science and Technology,General Materials Science,Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/eem2.12049

Reference149 articles.

1. Review of techniques based on artificial neural networks for the electrical characterization of concentrator photovoltaic technology

2. The rapid evolution of highly efficient perovskite solar cells

3. Copper indium gallium selenide based solar cells – a review

4. Toward High-Performance Carbon Nanotube Photovoltaic Devices

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