An electronically controlled hyperspectral infrared Fabry-Perot filter based on the Fano effect

Zhaomin Chen; Zecheng Gao; Xinyu Zhang

doi:10.1117/12.2689243

31 July 2023 An electronically controlled hyperspectral infrared Fabry-Perot filter based on the Fano effect

Zhaomin Chen, Zecheng Gao, Xinyu Zhang

Proceedings Volume 12747, Third International Conference on Optics and Image Processing (ICOIP 2023); 127470H (2023) https://doi.org/10.1117/12.2689243
Event: Third International Conference on Optics and Image Processing (ICOIP 2023), 2023, Hangzhou, China

Abstract

This paper introduces the design and experiments of a new electrically controlled hyperspectral infrared Fabry-Perot (FP) filter based on Fano resonance. The FP filter reflector material is studied and the DBR layer film system structure is selected for simulation calculations. Ge material is selected for the high refractive index layer and SiO2 material is selected for the low refractive index layer. The dentate structure hyperspectral infrared FP filter is designed by studying the principle of symmetry breaking to produce Fano resonance. The filter transmission spectrum is simulated and calculated using finite element simulation software. Mathematical modeling of the liquid crystal layer is performed to iteratively calculate the variation of the equivalent refractive index of the liquid crystal under different applied voltages. A bilaterally symmetric single-dentete structure filter with liquid crystal filling in the middle was made to test the variation of the transmission spectrum by applying different voltages to verify the correctness of the simulation.The results show that the appearance of a significant Fano resonance peak is observed in the designed device, implying that the design objectives are well achieved

Citation Download Citation

Zhaomin Chen, Zecheng Gao, and Xinyu Zhang "An electronically controlled hyperspectral infrared Fabry-Perot filter based on the Fano effect", Proc. SPIE 12747, Third International Conference on Optics and Image Processing (ICOIP 2023), 127470H (31 July 2023); https://doi.org/10.1117/12.2689243

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