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Modal analysis of novel coronavirus (SARS COV-2) using finite element methodology

TitleModal analysis of novel coronavirus (SARS COV-2) using finite element methodology
Publication TypeArticolo su Rivista peer-reviewed
Year of Publication2022
AuthorsWarsame, C., Valerini D., Llavori I., Barber A.H., and Goel S.
JournalJournal of the Mechanical Behavior of Biomedical Materials
Volume135
ISSN17516161
KeywordsAntimicrobial surface, Coronavirus, Coronaviruses, COVID-19, Eigenvalues and eigenfunctions, Eigenvalues and eigenvectors, Engineering methods, Finite element analyse, Finite element method, Finite element methodology, Modal analysis, Mode shapes, Natural frequencies, Spike protein, Vaccine development
Abstract

Many new engineering and scientific innovations have been proposed to date to passivate the novel coronavirus (SARS CoV-2), with the aim of curing the related disease that is now recognised as COVID-19. Currently, vaccine development remains the most reliable solution available. Efforts to provide solutions as alternatives to vaccinations are growing and include established control of behaviours such as self-isolation, social distancing, employing facial masks and use of antimicrobial surfaces. The work here proposes a novel engineering method employing the concept of resonant frequencies to denature SARS CoV-2. Specifically, “modal analysis” is used to computationally analyse the Eigenvalues and Eigenvectors i.e. frequencies and mode shapes to denature COVID-19. An average virion dimension of 63 nm with spike proteins number 6, 7 and 8 were examined, which revealed a natural frequency of a single virus in the range of 88–125 MHz. The information derived about the natural frequency of the virus through this study will open newer ways to exploit medical solutions to combat future pandemics. © 2022 The Authors

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URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85137168087&doi=10.1016%2fj.jmbbm.2022.105406&partnerID=40&md5=6251f93f003c6b3b08b607ad270ab08b
DOI10.1016/j.jmbbm.2022.105406
Citation KeyWarsame2022