Surface plasmon resonance sensor based on MXene coated PCF for detecting the cancer cells with machine learning approach

Abstract

This article presents a highly sensitive gold/Ti3C2Tx coated photonic crystal fiber (PCF)-based surface plasmon resonance (SPR) sensor for cancer cells detection. The hybrid gold/Ti3C2Tx layer is coated circularly over PCF for occurrence of SPR by coupled mode theory. The simulations and numerical analysis are done by the finite element method. The resonance wavelength shift is measured between normal and cancerous cell samples to estimate the wavelength sensitivity and resolution. In results, the maximum wavelength sensitivity for breast cancer MCF-7 cells is achieved as 10,714 nm/RIU in x-polarization mode and 13,071 nm/RIU in y-polarization mode with very low resolution of 10−6 RIU. The impact of the MXene (Ti3C2Tx) thin film on sensitivity is also observed. In addition, the optimization of parametric variation is analyzed with machine learning technique with low mean squared error of 0.01525. <2% error is obtained in sensitivity analysis with multilayer perceptron regressor. Due to the advanced results and machine learning application, this sensor can be used as a fast, efficient and low-cost cancer disease detection device.