Gradient-assisted metasurface absorber with dual-band chiral switching and quasi-linearly tunable circular dichroism

Enhanced Tunability of Dual-Band Chiral Metasurface in the Mid-Infrared Range via Slotted Nanocircuit Design

Multi-band circular dichroism (CD) response and tunability on the chiral metasurface are crucial for this device's applications in sensing and detection. This work proposes a dual-band CD Au-CaF2-Au dimer elliptical metasurface absorber, where chiroptical sensing is realized by breaking the geometric symmetry between two ellipses. The proposed metasurface can achieve high CD values of 0.8 and -0.74 for the dual-band within the 3-5 μm region, and the CD values can be manipulated by independently adjusting the geometric parameters of the metasurface. Furthermore, a slotted nanocircuit is introduced onto the metasurface to enhance its tunability by manipulating the geometry parameter in the design process, and the related mechanism is explained using an equivalent circuit model. The simulation of the sensing model revealed that the slotted nanocircuit enhances the sensor's tunability and significantly improves its bandwidth and sensitivity, achieving peak enhancements at approximately 753 nm and 1311 nm/RIU, respectively. Due to the strong dual-band positive (and negative) responses of the CD values, flexible wavelength tunability, and nonlinear sensitivity enhancement, this design provides a new approach for the development and application of mid-infrared chiroptical devices.

Realizing multi-function absorptions through arbitrary octagonal meta-atoms

Metasurface absorbers (MA) typically exhibit a single type of absorption function due to their regular structures. In this study, we propose an irregular MA structure with octagonal meta-atoms. The presence of eight vertices in each meta-atom allows for tunable coordinates and offers a multitude of degrees of freedom in terms of geometry. As a result, the proposed MA exhibits diverse functionalities, including perfect absorption, multi-peaks absorption, and high absorption with a filtering window. To predict the geometric parameters of the MA structure based on a given target absorption spectrum, as well as the inverse design of the structure using the absorption spectrum as input, we employ a deep neural network combined with the particle swarm optimization algorithm. Remarkably, the mean-square error for spectrum prediction and inverse design of the MA structure is found to be as low as 0.0008 and 0.0031, respectively. This study opens up new possibilities for designing irregular electromagnetic structures and holds great potential for applications in multifunctional metasurfaces and metamaterials.