Utilizing machine learning techniques for predictive modelling of absorptivity in l-shaped metamaterials

Abstract. Metamaterials are artificially engineered materials that have properties not found in naturally occurring materials. They designed to specific electromagnetic or other physical properties, such as negative refraction, superconductivity high absorptivity. often composed of structures on a scale much smaller than the wavelength phenomena they intended manipulate. wide range potential applications, including antennas, cloaking devices, and super resolution imaging. In this paper we simulated validated an L shaped meta material make data set its absorptivity by varying different input parameters then used these predict any metamaterial using machine learning it gave satisfactory results.