UV to near-infrared broadband pyramidal absorbers via a genetic algorithm optimization approach

We use a genetic algorithm to optimize broadband absorption by 2-D periodic arrays of pyramidal structures
made of one, two or three stacks of nickel/poly(methyl methacrylate) (Ni/PMMA) layers. The objective was
to achieve perfect absorption of normally incident radiations with wavelengths comprised between 420 and 1600
nm. The absorption spectrum of these pyramidal structures is calculated by a Rigorous Coupled Waves Analysis
method. A genetic algorithm is then used to determine optimal values for the period of the system, the lateral
dimensions of each stack of Ni/PMMA and the width of each layer of PMMA. The idea consists in working
with a population of individuals that represent possible solutions to the problem. The best individuals are
selected. They generate new individuals for the next generation. Random mutations in the coding of parameters
are introduced. A local optimization procedure that works on the data collected by the algorithm is used to
accelerate convergence. This strategy is repeated from generation to generation in order to determine a globally
optimal set of parameters. The optimal three-stacks structure determined by this approach turns out to absorb
99.8% of the incident radiations over the considered 420-1600 nm wavelength range. A value of 99.4% is achieved
with pyramids made of only two stacks of Ni/PMMA layers while a one-stack pyramidal structure absorbs 95.0%
over the same wavelength range. These results are surprisingly competitive considering the small number of layers
involved in the design. They prove the interest of an evolutionary approach to optical engineering problems.