Optical properties of hollow plasmonic nanopillars for efficient solar photothermal conversion

Solar evaporation of liquid marbles with Fe3O4/CNT hybrid nanostructures

HYPOTHESIS

Through the rational design of nanomaterial composites, broadband light harvesting and good thermal insulation can be achieved simultaneously to improve the efficiency of water evaporation.

EXPERIMENT

Solar evaporation experiments were carried out on liquid marbles (LMs) coated with Fe3O4 nanoparticles, carbon nanotubes (CNTs) and hybrid nanomaterials (Fe3O4/CNTs) with different mass ratios of 2:1, 1:1 and 1:2.

FINDING

The results showed that the mixture of Fe3O4/CNTs enhances the light harvesting ability and solar interfacial evaporation performance. Fe3O4/CNT-LM at the mass ratio of 2:1 case provides the highest evaporation rate of 11.03 μg/s, which is about 1.22 and 1.34 times higher than that of Fe3O4 and CNT, respectively. This high performance is mainly due to the synergistic effect between Fe3O4 nanoparticles and CNTs, as the hybrid nanostructure significantly improves the both photothermal conversion and heat localization capability. Numerical simulation further supports that the composite can concentrate the electromagnetic field and heat at the phase-change interface. This leads to a rapid evaporation of the boundary region. This study provides a novel approach to a three-dimensional interface by assembling nanomaterials on the drop surface to enhance evaporation, which may have far-reaching implications for seawater desalination.

Deep learning empowering design for selective solar absorber

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 the infrared region (calculated/measured = 0.08/0.19). This absorber has the potential to result in annual energy savings of up to 1743 kW h/m2 in areas with abundant solar radiation resources. Our study opens a powerful design method to study solar-thermal energy harvesting and manipulation, which will facilitate for their broad applications in other engineering applications.