Design of a Highly Sensitive Self-Reference Tamm-Plasmon-Polariton Sensor Employing Ti3C2Tx MXene

Abstract

This paper presents design and analysis of a self-reference refractive index sensor for precise detection of different concentrations of H5N1 virus in poultry. The sensor is based on the study of Tamm plasmon polariton (TPP) modes excited between Ti <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> Tx MXene and cavity layer integrated 1D photonic crystal (PhC). We demonstrate the self-reference characteristics of the sensor, which significantly decreases the error contributions by the environmental factors like the light intensity fluctuations and local temperature variations. The transfer matrix method (TMM) is employed to investigate the reflectance and absorbance of the sensor. The cornerstone of this work lies on the assay of the shift in the wavelength and intensity of the TPP mode vis-à-vis different concentrations of the H5N1 virus. Numerous structural parameters like selection of materials, thickness of the MXene layer, thickness of the cavity layer, and period of the PhC are judiciously optimized to envisage maximum sensing performance. The colormap plot of field distribution infers a strong electric field localization in the cavity layer, which indicates high absorption of TPP modes. Compared to the traditional TPP sensor designed with Ag thin film, the electric field intensity (EFI) and sensitivity of the proposed MXene-based TPP sensor have been boosted by 40% and 15.93% respectively. It is appraised that the proposed sensor delivers a maximum sensitivity of 60.9375 nm/HAU, quality factor of 5485.71, and detection limit of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${2.6}\times {{10}}^{-{6}}$ </tex-math></inline-formula> RIU. The proposed sensor can find suitable applications in the field of biomedical diagnostics, healthcare, food safety, and environmental monitoring.