Design and finite element modeling of two-dimensional nanomechanical biosensors for SARS-CoV-2 detection

SARS-CoV-2 is the causative agent of COVID-19 disease. The development of different variants has increased the prevalence, pathogenicity, and mortality of the SARS-CoV-2. Prompt diagnosis and timely initiation of therapy can undoubtedly minimize the damage caused by this virus. In this study, a wide range of emerging single layer two-dimensional materials (SL2DMs), including graphene, grapheme oxide (GO), reduced graphene oxide (rGO), hexagonal boron nitride (h-BN), Ti3C2Tx MXene, and MoS2that can be used to fabricate highly sensitive biosensors, are analyzed using the finite element method based on antigen-antibody interaction. Important design parameters including sensor size, sensor aspect ratio, number of viruses, and applying in-plane strain on sensor performance are analyzed using frequency shift technique. In the following, an analytical relationship that can predict the limit of detection (LOD) according to the above parameters is proposed. The results show that all the above materials have a good performance in detecting viruses in the sample range of 10-100 viruses. This range can be reduced significantly by applying strains of less than 0.1. Also, applying strain increases shift frequency index by 2 to 3 times, which is a significant result. The maximum and minimum sensor performance are obtained for GO and Ti3C2Tx, respectively. The results of this paper can be used to build a new generation of two-dimensional biosensors for rapid detection of COVID-19 and other viruses.