On the sensing performance improvement in SPR biosensor using ZnO and TMDCs architecture for cancer detection.

In this study, we have unveiled an SPR biosensor for highly sensitive and rapid detection of cancerous cells employing 2D materials. The proposed sensor structure introduces a novel approach to cancer cell detection, offering a new perspective in biosensing technology. In other words, specifically, ZnO, SiN and TMDCs based plasmonic sensor structures demonstrate great potential whenever high-accuracy detection of cancerous cells is required. We present four different configuration of SPR based sensor designed for the detection of different types of cancer cells. The designed conventional configuration consists of four functional layers namely Ag, ZnO, SiN and sensing medium along with BK7 prism for coupling light at the interface of metal-dielectric. To illustrate performance improvement, enhancement of light absorption capacity and achieve higher sensitivity of sensor, we incorporated four different 2D materials, MoS, MoSe, WS and WSe. Using the angular interrogation method, the proposed layered structure, BK7/ZnO/Ag/SiN/WS/sensing medium, demonstrated the highest overall sensitivity in terms of detecting three cancerous cells, blood cancer (Jurkat), cervical cancer (HeLa) and skin cancer (Basal) from healthy cells. Notably, the sensitivity which is achieved with the configuration BK7/ZnO/Ag/SiN/WS/sensing medium for blood cancer detection from healthy cells with the value of 342.14 deg/RIU and FOM equal to 124.86 RIU, outperforms all other proposed configurations. Applying finite element method (FEM) simulations, the distribution of electric field across the interfaces of the SPR sensor configurations are analyzed. Overall, SPR biosensors offer a promising technology for the early and accurate cancerous cell detection. The high sensitivity, specificity, and ability to analyze complex biological samples make them valuable tools in the struggle against cancer. However, further research and development are demanded to optimize the performance and translation of these sensors into clinical and real-world applications.