Coronavirus disease 2019 (COVID-19) is a newly emerging human infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Early diagnosis is essential to reducing the transmission rate and mortality of COVID-19. PCR-based tests are the gold standard for the confirmation of COVID-19, but immunological tests for SARS-CoV-2 detection are widely available and play an increasingly important role in the diagnosis of COVID-19. Nanomechanical sensors are biosensors that work based on a change in the mechanical response of the system when a foreign object is added. In this paper, a graphene-based nanoresonator sensor for SARS-CoV-2 detection was introduced and analyzed by using the finite element method (FEM). The sensor was simulated by coating a single-layer graphene sheet (SLGS) with a specific antibody against SARS-CoV-2 Spike S1 antigen. In the following, the SARS-CoV-2 viruses were randomly distributed on the SLGSs, and essential design parameters of the nanoresonator, including frequency shift and relative frequency shift, were evaluated. The effect of the SLGS size, aspect ratio and boundary conditions, antibody concentration, and the number of viruses variation on the frequency shift and relative frequency shift were investigated. The results revealed that, by proper selection of the nanoresonator design variables, a good sensitivity index is achievable for identifying the SARS-CoV-2 virus even when the number of the viruses are less than 10 per test. Eventually, according to the simulation results, by using SLGS geometry determination, an analytical relationship is presented to predict the limit of detection (LOD) of the sensor with the required sensitivity index. The results can be applied in designing and fabricating specific graphene-based nanoresonator sensors for SARS-CoV-2.

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