Using machine learning and the calculation of thermal emission properties, a research team from RIKEN and the National Institute for Materials Science (NIMS) created metamaterial structures with optimum thermal radiation performance. The project focused on easy-to-fabricate multilayered metamaterial structures composed of three types of materials in 18 layers of varying thickness. Application of this method to about eight billion candidate structures led to the prediction that a nanostructure composed of non-periodically arranged semiconductor and dielectric materials would have superior thermal radiation performance.
The team fabricated the metamaterial structure and measured its thermal emission spectrum, and consequently demonstrated an extremely narrow thermal emission band. Measured in terms of the Q-factor (a parameter used to measure the width of thermal emission spectral bands), the newly designed nanostructure produced a Q-factor close to 200, when 100 had been considered the upper limit for conventional materials—an exceptionally narrow thermal emission spectral band.
Because the nanostructure design method developed is applicable to all types of materials, it may serve as an effective tool for the design of high-performance materials in the future.