Graphene‐Enhanced Photonic Crystal Biosensor for Acetone Detection in Wastewater: A Novel Environmental Monitoring Approach

Abstract

Wastewater with high organic content poses serious risks to human health, necessitating precise detection of compounds like acetone. This work presents the design and analysis of a high‐performance biosensor based on a defective 1D ternary photonic crystal (TPC) for detecting acetone concentrations via refractive index (RI) changes. The TPC consists of alternating layers of Si, Nb₂O₅, and SiO₂, with a central defect layer infiltrated by water‐acetone mixtures. The transfer matrix method (TMM) is employed to investigate the transmission spectra. Detection relies on the strong correlation between the defect mode and the RI variations of the infiltrated medium. Key structural parameters—number of periods, defect layer thickness, and incident angle—are optimized to enhance sensitivity (S). Furthermore, the influence of graphene insertion on the sensor's performance is explored. At an incident angle of 55°, with three periods and a defect thickness of 2770 nm, the sensor achieves a maximum S of 3658.25 nm RIU−1. The proposed biosensor exhibits excellent precision in detecting organic contaminants in wastewater, making it a promising candidate for environmental monitoring and water quality assessment.