Alcohol sensing and classification using PCF-based sensor

Abstract

This paper focuses on designing a Photonic Crystal Fiber (PCF) based sensor model. The anticipated sensor is modelled and simulated using COMSOL Multiphysics to carry-out experiments on multiple optical parameters that evaluate the efficiency of this model. This model aims to detect alcohol and classify it. Three variants of alcohol, namely methanol, ethanol, and propanol, have been considered in this study. These analytes are then injected into the core-region separately. The model is then simulated between 1.0 THz and 2.5 THz frequency band to evaluate the optical properties. Simulation results demonstrate higher relative sensitivity of approximately 88%, 91%, and 92% at 2.0 THz for methanol, ethanol, and propanol, respectively. Besides, the confinement loss for this model approaches nearly zero immediately after 1.2 THz. Furthermore, a shallow effective material loss (EML) is found for this sensor model to sense these three types of alcohol. For instance, the EML value is only 0.0056 cm−1 in the case of methanol sensing. Finally, different optical parameters presented in this study demonstrate the effectiveness of the proposed model in sensing various alcohols.