Mechanical Engineering Department, A D Patel Institute of Technology, CVM University, Vallabh Vidyanagar, Gujarat, India.
J Mol Model. 2024 Sep 6;30(10):327. doi: 10.1007/s00894-024-06123-8.
Airborne pathogens, defined as microscopic organisms, pose significant health risks and can potentially cause a variety of diseases. Given their ability to spread through diverse transmission routes from infected hosts, there is a critical need for accurate monitoring of these pathogens. This study aims to develop a sensor by investigating the vibrational responses of cantilever and bridged boundary-conditioned single-layer graphene (SLG) sheets with microorganisms, specifically SARS-CoV-2, attached at various positions on the sheet. The dynamic analysis of SLG with different boundary conditions and lengths was conducted using the atomistic finite element method (AFEM). Simulations were performed to evaluate SLG's performance as a sensor for biological entities. Altering the sheet's length and the mass of the attached biological object revealed observable frequency differences. This sensor design shows promise for enhancing the detection capabilities of graphene-based technologies for viruses.
Finite element method (FEM) analysis is employed to model the sensor's performance and optimize its design parameters. The simulation results highlight the sensor's potential for achieving high sensitivity and rapid detection of SARS-CoV-2. Bridged and cantilever boundary conditions are applied at the ends of the SLG structure by using ANSYS software. Simulations have been conducted to observe how SLG behaves when used as sensors. In armchair graphene, under both boundary conditions, an SLG (5, 5) structure with a length of 50 nm displayed the highest frequency when a SARS-CoV-2 molecule with a mass of 2.6594 × 10 g was attached. Conversely, the chiral SLG (17, 1) structure exhibited its lowest frequency at a length of 10 nm. This insight is crucial for grasping detection limits and how factors such as size and boundary conditions influence sensor efficacy. These biosensors hold immense promise in biological sciences and medical applications, revolutionizing patient care by enabling early detection and accurate pathogen identification in clinical settings.
空气中的病原体，定义为微观生物体，对健康构成重大威胁，并可能导致多种疾病。由于它们能够通过各种不同的传播途径从感染宿主传播，因此迫切需要对这些病原体进行准确监测。本研究旨在通过研究悬臂和桥接边界条件下单层石墨烯 (SLG) 片的振动响应来开发一种传感器，这些 SLG 片上附有不同位置的微生物，特别是 SARS-CoV-2。使用原子有限元法 (AFEM) 对具有不同边界条件和长度的 SLG 进行了动态分析。进行了模拟以评估 SLG 作为生物实体传感器的性能。改变片的长度和附着的生物物体的质量会显示出可观察到的频率差异。这种传感器设计有望提高基于石墨烯的技术对病毒的检测能力。
采用有限元法 (FEM) 分析来模拟传感器的性能并优化其设计参数。模拟结果突出了传感器在实现 SARS-CoV-2 的高灵敏度和快速检测方面的潜力。通过使用 ANSYS 软件，在 SLG 结构的两端施加桥接和悬臂边界条件。进行了模拟以观察 SLG 作为传感器的行为。在扶手椅型石墨烯中，在这两种边界条件下，当附着一个质量为 2.6594 × 10-26 g 的 SARS-CoV-2 分子时，长度为 50 nm 的 SLG（5,5）结构显示出最高的频率。相反，长度为 10 nm 的手性 SLG（17,1）结构显示出最低的频率。这一见解对于理解检测极限以及大小和边界条件等因素如何影响传感器的功效至关重要。这些生物传感器在生物科学和医学应用中具有巨大的应用前景，通过在临床环境中实现早期检测和准确的病原体识别，彻底改变了患者的护理方式。
