Broadband solar absorber and high-temperature thermal emitter based on deep learning optimization and design

Key Points

• The aim is to develop an efficient solar absorber and thermal emitter using deep learning techniques.
• Utilized deep learning algorithms to optimize the design of a solar absorber.
• Developed a metamaterial structure for enhanced performance.
• Performed simulations to assess energy absorption efficiency and thermal emission characteristics.
• Achieved significant improvements in solar energy absorption rates.
• Demonstrated high-temperature thermal emission capabilities of the developed structure.
• Indicated potential applications in energy harvesting and thermal management.