Deep learning empowering design for selective solar absorber.

ABSTRACT: The selective broadband absorption of solar radiation plays a crucial role in applying solar energy. However, despite being a decade-old technology, the rapid and precise designs of selective absorbers spanning from the solar spectrum to the infrared region remain a significant challenge. This work develops a high-performance design paradigm that combines deep learning and multi-objective double annealing algorithms to optimize multilayer nanostructures for maximizing solar spectral absorption and minimum infrared radiation. Based on deep learning design, we experimentally fabricate the designed absorber and demonstrate its photothermal effect under sunlight. The absorber exhibits exceptional absorption in the solar spectrum (calculated/measured = 0.98/0.94) and low average emissivity in t

SUBMITTER: Ma W 

PROVIDER: S-EPMC11502052 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature