Design and Analysis with Monitoring of Photonic Crystal Fiber (PCF) Based Oil Sensing

This study presents a sensor based on hollow-core Photonic Crystal Fiber (PCF), specifically designed for detecting edible oils in the micrometer (μm) range (1.0 μm to 3.0 μm). Various sensing characteristics have been analyzed numerically with performance assessed using COMSOL Multiphysics, a leading software employing the finite element method. This advancement enhances oil detection technology significantly. The computational results reveal impressive relative sensitivity (RS) levels at a wavelength of 1 μm, achieving 99.45%, 98.81%, 99.53%, 99.64%, and 99.68% for oil of coconut, palm, olive, mustard, and sunflower respectively. The proposed model demonstrates impressive lower confinement loss (CL) with values of 9.08× 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-8</sup> dB/m, 9.03×10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-8</sup> dB/m, 9.02×10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-8</sup> dB/m, 8.89×10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-8</sup> dB/m, and 9.07×10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-8</sup> dB/m for coconut oil, palm oil, olive oil, mustard oil, and sunflower oil respectively. Utilizing advanced deposition and 3D printing techniques, this sensor's superior detection capabilities make it a valuable asset for oil-sensing devices in various industries.