Mathematical modelling and gas sensing abilities of graphene based optical sensor

Abstract

In this work, graphene based Langmuir-Blodgett (LB) thin films prepared onto gold-coated glass substrates to evaluate its sensing ability by using Surface Plasmon Resonance (SPR) system. In order to illuminate the swelling characteristics of the graphene optical sensor, the diffusion coefficients of these vapors were calculated by applying the early-time Fick’s diffusion equation. The diffusion coefficients are found to be 0.1954 x 10−15, 0.0696 x 10−15 and 0.0197 x 10−15 cm2 s−1 for benzene, toluene, and xylene, respectively. The nonlinear autoregressive with exogenous input neural network was designed by utilizing experimental data from SPR kinetic results to model the change in photodetector response. The calculated diffusion coefficients using artificial neural network model are approximately equal to real-data diffusion coefficients as verified by very high correlation coefficients (0.1948 x 10−15, 0.0760 x 10−15 and 0.0198 x 10−15 cm2 s−1 for benzene, toluene, and xylene, respectively). Consequently, graphene-based optical sensors displays high response and sensitivity for saturated benzene vapor than other vapors. These optical thin film sensors were potential candidates for organic vapor sensing applications with simple and low cost preparation at room temperature..