Recent Advances in Solar Energy Full Spectrum Conversion and Utilization

Chen Chen,1, 2, #

Xixi Xie,1, 2, #

Ming Yang,1, 2, *Email

Hang Zhang,1, 2, *Email

Ilwoo Seok,3

Zhanhu Guo,4

Qinglong Jiang,5

Grant Wangila5 

Qibin Liu1, 2, *Email

1 Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100049, China

2 University of Chinese Academy of Sciences, No. 19(A) Yuquan Road, Beijing 100049, China

3 Arkansas State University, PO Box 1740, State University, AR 72467, USA

4 Department of Chemical & Biomolecular Engineering, University of Tennessee Knoxville, Knoxville, TN 37996, USA

5 Department of Chemistry and Physics, University of Arkansas, Pine Bluff, Arkansas 71601, USA

#Both authors contributed equally to this work


Photovoltaic technology is a direct and effective way to utilize solar energy. The mismatch between the absorption band of solar cells and the solar light band restricts solar energy's efficient use. Full-spectrum conversion of solar energy with spectral modification and coupling solar thermal application are reviewed. Additionally, implementing machine learning (ML) methods to improve solar energy utilization is also examined. With the utilization of up conversion materials for solar cells, the solar-energy-utilization efficiency is enhanced. Combining PV and thermal applications have been validated to be promising for improving efficiency. With the development of computer science and the urgent need to design solar energy materials and forecast PV performances, ML methods in solar energy utilization have been successfully implemented into solar energy utilization.

Recent Advances in Solar Energy Full Spectrum Conversion and Utilization