Design of a High-Performance Titanium Nitride Metastructure-Based Solar Absorber Using Quantum Computing-Assisted Optimization

Metastructures of titanium nitride (TiN), a plasmonicrefractorymaterial, can potentially achieve high solar absorptance while operatingat elevated temperatures, but the design has been driven by expertintuition. Here, we design a high-performance solar absorber basedon TiN metastructures using quantum computing-assisted optimization.The optimization scheme includes machine learning, quantum annealing,and optical simulation in an iterative cycle. It designs an optimalstructure with solar absorptance > 95% within 40 h, much fasterthanan exhaustive search. Analysis of electric field distributions demonstratesthat combined effects of Fabry-Perot interferences and surfaceplasmonic resonances contribute to the broadband high absorption efficiencyof the optimally designed metastructure. The designed absorber mayexhibit great potential for solar energy harvesting applications,and the optimization scheme can be applied to the design of othercomplex functional materials.