Design and Simulation of Graphene-Based Biosensor for SARS-CoV-2 Variants Detection

Abstract

In December 2019, a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in Wuhan City, China, and disseminated globally. The fatality rate increased until vaccines were used to control the infectious and morbidity rate worldwide. Key lessons learned from this 3-year pandemic emphasize the imperative to continually enhance diagnostic technologies for the specific detection of emerging viral infections. The COVID-19 pandemic demonstrated the emergence of multiple variants resulting from mutations in SARS-CoV-2, notably the recent and highly transmissible, Omicron variant, posing challenges in detecting asymptomatic cases. National pandemic prevention and control would be significantly hampered without early precautions. Therefore, this study proposed to design and simulate the graphene field effect transistor for the SARS-CoV-2 variants detection biosensor. Using COMSOL Multiphysics 5.6 software, the model incorporates two sets of Graphene Field Effect Transistors, each coated with different antibodies, anti-Delta and anti-Omicron antibodies. Upon the exposure of Omicron variant to the sensing area, the Graphene Field Effect Transistor containing anti-Omicron antibodies (Ab2E8a) will undergo color contour changes that indicates interaction on the graphene layer which is the binding of Omicron antigen with anti-Omicron antibodies. This simulation demonstrated the capability of the Graphene Field Effect Transistor biosensor to detect multiple SARS-CoV-2 variants. Hence, this biosensor offers a promising tool for COVID-19 control through rapid and precise early-stage diagnosis of COVID-19.