Genetic-algorithm-aided ultra-broadband perfect absorbers using plasmonic metamaterials

Ultra-Broadband Perfect Absorber based on Titanium Nanoarrays for Harvesting Solar Energy

Solar energy is a clean and renewable energy source and solves today's energy and climate emergency. Near-perfect broadband solar absorbers can offer necessary technical assistance to follow this route and develop an effective solar energy-harvesting system. In this work, the metamaterial perfect absorber operating in the ultraviolet to the near-infrared spectral range was designed, consisting of a periodically aligned titanium (Ti) nanoarray coupled to an optical cavity. Through numerical simulations, the average absorption efficiency of the optimal parameter absorber can reach up to 99.84% in the 200-3000 nm broadband range. We show that the Ti pyramid's localized surface plasmon resonances, the intrinsic loss of the Ti material, and the coupling of resonance modes between two neighboring pyramids are highly responsible for this broadband perfect absorption effect. Additionally, we demonstrate that the absorber exhibits some excellent features desirable for the practical absorption and harvesting of solar energy, such as precision tolerance, polarization independence, and large angular acceptance.

Broadband coherent perfect absorption employing an inverse-designed metasurface via genetic algorithm

Coherent perfect absorption (CPA) possesses the unique characteristics of flexibly and actively molding the flow of light. However, restricted by the low design efficiency and limited geometry variety of metamaterial structures, the common CPA metamaterial absorbers based on artificial design show poor performance in bandwidth operation. Here, we proposed a tungsten-based metamaterial absorber to achieve broadband CPA via employing genetic algorithm inverse design. Under the irradiation of two coherent beams, the high coherent absorption (>90%) can be achieved within a wide range from 1.32 to 3.28 µm. By simply adjusting the relative intensity or phase difference of the two coherent beams, the absorption intensity can be continuously modulated to realize the transition between coherent perfect absorption and coherent perfect transparency. Moreover, the coherent absorption maintains greater than 90% over a broad range of incident angles for both TM and TE polarizations. The scattering matrix theorem is applied to explain the physical mechanism of CPA, and the analytical results exhibit good consistency with the numerical calculations. Such a tungsten-based CPA metamaterial absorber with broadband tunability and exceptional angular stability is expected to be utilized in optical signal processing chips, all-optical modulators, and optical switchers.

Optimization of Magnetoplasmonic ε-Near-Zero Nanostructures Using a Genetic Algorithm

Magnetoplasmonic permittivity-near-zero (ε-near-zero) nanostructures hold promise for novel highly integrated (bio)sensing devices. These platforms merge the high-resolution sensing from the magnetoplasmonic approach with the ε-near-zero-based light-to-plasmon coupling (instead of conventional gratings or bulky prism couplers), providing a way for sensing devices with higher miniaturization levels. However, the applications are mostly hindered by tedious and time-consuming numerical analyses, due to the lack of an analytical relation for the phase-matching condition. There is, therefore, a need to develop mechanisms that enable the exploitation of magnetoplasmonic ε-near-zero nanostructures’ capabilities. In this work, we developed a genetic algorithm (GA) for the rapid design (in a few minutes) of magnetoplasmonic nanostructures with optimized TMOKE (transverse magneto-optical Kerr effect) signals and magnetoplasmonic sensing. Importantly, to illustrate the power and simplicity of our approach, we designed a magnetoplasmonic ε-near-zero sensing platform with a sensitivity higher than 56∘/RIU and a figure of merit in the order of 102. These last results, higher than any previous magnetoplasmonic ε-near-zero sensing approach, were obtained by the GA intelligent program in times ranging from 2 to 5 min (using a simple inexpensive dual-core CPU computer).