Design and Simulation of a Smart Arrow Photonic Crystal Fiber Sensor for Multimodal Optical Detection of Food Adulteration

The challenge of food adulteration has always been a major concern and thus there is a need to formulate quick, sensitive, and un-destructive methods to detect food adulteration. Authors provide the design and performance analysis of a Smart Optical Sensing platform driven by Arrow-type Silica Photonic Crystal Fiber (PCF) that is designed to specifically detect adulterants in food products. The COMSOL Multiphysics numerical simulation environment is used to increase the interaction between light and matter. The intended PCF structure has a pitch size of 1.5 µm, diameter of the air holes to be 0.75 µm and core displacement parameters to be asymmetrical (dx = 0.5 µm, dy = 0.25 µm) that leads to a robust field of evanescent confinements and proves to have high optical sensing qualities. The simulation outcomes also show a large absorbance difference (0.8512 a.u.) between non-adulterated and adulterated ones and the greatest decrease in transmittance amounting to 30% exists in the case of the adulterated specimens. Fluorescence spectral displacement of 40 nm to 75 nm and Raman based at 200 to 800 cm^-1 allowed distinguishing between chemicals at the level of a molecule, and identification of adulterants which include artificial food dyes, heavy metals, and chemical preservatives. A combination of NIR spectroscopy with COMSOL-based modelling will define a sound system of non-destructive, fast, and scalable food safety tests.