Inverse Design and Experimental Verification of Metamaterials for Thermal Illusion Using Genetic Algorithms

Abstract

Thermal metamaterials offer a promising avenue for creating artificial materials with unconventional physical properties, such as thermal cloak, concentrator, rotator, and illusion. However, designs and fabrication of thermal metamaterials are of challenge due to the limitations of existing methods on anisotropic material properties. We propose an evolutionary framework for designing thermal metamaterials using genetic algorithm optimization. Our approach encodes unit cells with different thermal conductivities and performs global optimization using the evolution-inspired operators. We further fabricate the thermal functional cells using 3D printing and verify their thermal illusion functionality experimentally. Our study introduces a new design paradigm for advanced thermal metamaterials that can manipulate heat flows robustly and realize functional thermal metadevices without anisotropic thermal conductivity. Our approach can be easily applied to fabrications in various fields such as thermal management and thermal sensing.