Piezoelectric MEMS (Micro-Electro-Mechanical Systems) are used in many applications now a day's including the diagnosis of diseases.COVID-19 is a pandemic recently affecting the entire world. Various techniques for detection are being used to date. Paper presents a simulation-based piezoelectric MEMS detection method for the virus, which is fast, portable, cost-effective, require less amount of sample, reliable, and can diagnose the stage for SARS-CoV-2(Severe acute respiratory syndrome corona virus 2) from the first day of virus infection. The design and analysis of cantilever-based MEMS biosensor is done COMSOL Multiphysics. Three cantilevers are used in the design, one each for viral load, IgM, and IgG. The bio-molecular reaction on the cantilever increases the mass at the end, changing the electrical and mechanical properties in the cantilever. Piezoelectric material generates the voltage proportional to the mass applied. From the values of voltage obtained from three cantilevers, the infection stage for symptomatic and asymptomatic can be diagnosed. Results show a linear relationship between the load applied and voltage generated. The proposed biosensor has a mass sensitivity of 20 copies /ml.

Micro-Electro-Mechanical Systems (MEMS) is a process technology that combines mechanical and electrical components to make micro-scale range devices. A considerable cost of the device can be reduced if we simulate the design. There are many available simulation software to choose from, which in turn is one of the major challenge. The paper explores the functional and technical features of some software used in MEMS designing. It further presents the keypoints which we should acknowledge while selecting software. Basic features are available in all MEMS Simulation software. However, if the design involves specific physics, geometry, material or meshing, the search must be done to find the appropriate software. If the user intends to fabricate the device then software with a virtual fabrication tool needs to be selected.

Piezoelectric MEMS (Micro-Electro-Mechanical Systems) Cantilevers have successfully been used in a wide variety of applications in recent years. This paper is a simulation-based study on Micro-cantilever based Piezoelectric MEMS biosensors for Chikungunya Virus (CHIKV) detection. In addition to providing early detection, the proposed method is label-free, faster, and more reliable. The proposed biosensor detects CHIKV E2 protein via MEMS Sensor. The basic principle involves using piezoelectric material on a micro-cantilever for biomaterial detection. A piezoelectric MEMS cantilever is simulated in COMSOL Multiphysics and compared for voltage, stress, and displacement for three materials (silicon, gold, and PDMS). Analytical equations are derived. Post-processing for biosensor design is done in SIMULINK. Simulated voltage, stress, and displacement show a linear relationship with the viral load. PDMS also provided the highest voltage and displacement among the three materials used for MEMS simulation. The graphs show the comparison between simulated and analytical values. Simulation results are also compared to clinical results to prove the biosensor's validity. MEMS Biosensor performance matches with the RT-PCR results, with the added advantage of faster results. Diagnostic tests in the medical field can be performed using the proposed biosensor.