Next-generation graphene metamaterial plasmonic solar absorbers with square ring and cross-shaped designs optimised via machine learning for renewable applications

The role of renewable energy has significantly improved in recent years, helping to mitigate the damage caused to natural resources. One of the most prominent forms of renewable energy is electricity produced from wind, air and sunlight. The current study focuses on a solar absorber that primarily uses sunlight as a renewable energy solution. This absorber features a design combining a cross-shaped and square structure, utilising two different materials: silicon (Si) and titanium (Ti), for the resonator design. The graphene composition is placed on a tin (IV) selenide (SnSe2) substrate with an aluminium nitride (AlN) layer. The overall absorption efficiency is 93.02% at 2800 nm, with an absorption rate exceeding 98% at the 1100 nm band. The design's performance is expressed in terms of the electric and magnetic field intensities, and it includes a polarisation-insensitive configuration. The linear regression method employed for machine learning optimisation, achieving a high R² value of 0.98.