Terahertz photonic crystal fiber-based edible oil sensor: Performance evaluation and identification

Abstract

This model introduced an innovative hollow-core optical waveguide with an octagonal core, specifically designed for rapid detection of various food oil contaminations is founded on the principles of Photonic Crystal Fiber (PCF). By analyzing the refractive index (RI) variations between pure and contaminated oil, we evaluate other essential optical parameters. The characteristics inherent to the suggested food oil sensor are examined using COMSOL Multiphysics v6.1, employing the Finite Element Method (FEM). Highly precise mesh components are included to provide optimal simulation accuracy. The outcomes from the suggested sensor model demonstrate exceptionally strong relative sensitivity of 98.52 % for castor oil, 98.46 % for sunflower oil, 98.41 % for mustard oil, 98.32 % for olive oil, and 98.03 % for coconut oil, all measured at 2 THz. Additionally, the simulation shows a very low confinement loss of 2.37 × 10−12 cm-1, a numerical aperture of 0.242, effective area of 1.1459 × 10–7 m², and effective material loss of 0.0038 cm-1 for castor oil under optimal structural circumstances. The straightforward design of the PCF in the sensor indicates that it can be implemented with ease, given these standard performance indicators. Therefore, it is anticipated that this sensor will open improved avenues for detection and identification of several distinct food oil contaminations. It can be produced using standard fabrication processes.

Keywords

• Refractive index (RI)
• Effective area (EA)
• Numerical aperture (NA)
• Spot size
• Air filling fraction (AFF)