Payandehpeyman Javad, Parvini Neda, Moradi Kambiz, Hashemian Nima
Department of Mechanical Engineering, Hamedan University of Technology, P.O. Box 65169-13733, Hamedan, Iran.
Cellular and Molecular Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, P.O. Box 66177-13446, Sanandaj, Iran.
ACS Appl Nano Mater. 2021 Jun 1;4(6):6189-6200. doi: 10.1021/acsanm.1c00983. eCollection 2021 Jun 25.
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.
2019冠状病毒病（COVID-19）是一种由严重急性呼吸综合征冠状病毒2（SARS-CoV-2）引起的新出现的人类传染病。早期诊断对于降低COVID-19的传播率和死亡率至关重要。基于聚合酶链反应（PCR）的检测是确诊COVID-19的金标准，但用于检测SARS-CoV-2的免疫检测方法广泛可用，并且在COVID-19的诊断中发挥着越来越重要的作用。纳米机械传感器是一种生物传感器，当添加异物时，它基于系统机械响应的变化来工作。本文介绍了一种用于检测SARS-CoV-2的基于石墨烯的纳米谐振器传感器，并使用有限元方法（FEM）进行了分析。通过用针对SARS-CoV-2刺突S1抗原的特异性抗体包被单层石墨烯片（SLGS）来模拟该传感器。接下来，将SARS-CoV-2病毒随机分布在SLGS上，并评估了纳米谐振器的基本设计参数，包括频移和相对频移。研究了SLGS尺寸、纵横比和边界条件、抗体浓度以及病毒数量变化对频移和相对频移的影响。结果表明，通过适当选择纳米谐振器的设计变量，即使每次测试的病毒数量少于10个，也能获得良好的灵敏度指标来识别SARS-CoV-2病毒。最终，根据模拟结果，通过使用SLGS几何形状确定，给出了一种解析关系，以预测具有所需灵敏度指标的传感器的检测限（LOD）。这些结果可应用于设计和制造用于检测SARS-CoV-2的特定基于石墨烯的纳米谐振器传感器。
