Design of Nanometer-Sized Metasurface Broadband Absorber from UV to MIR Using Genetic Algorithms and Physical Model Constraints

This study proposes a scheme for designing a nanometer-sized metasurface broadband absorber from ultraviolet (UV) to mid-infrared (MIR) using genetic algorithm (GA) optimization based on physical model constraints. A GA was used for the multiparameter optimization of the meta-atom (with a period of 200 nm and nanoscale layer thickness) to improve the broadband spectrum response of the absorber. This study adds several constraint conditions based on the simplified physical model to accelerate the GA optimization process, addressing current challenges in metasurface absorber design optimization, such as computational efficiency and cost, data dependence, and lack of physical models. The results are in line with expectations, and the broadband spectrum response of the nanoscale absorber was significantly improved using low-cost computational resources, indicating the effectiveness and feasibility of the scheme. This work facilitates the design and optimization of metasurface absorbers with enhanced broadband absorption, providing a path for faster development of low-cost nanoscale broadband absorbers.