Evidence map›Paper›PMID 36075162›Full record

ArticleJournal of the mechanical behavior of biomedical materials2022

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

Caaisha Warsame, Daniele Valerini, Iñigo Llavori, Asa H Barber, Saurav Goel

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the mechanical behavior of biomedical materials, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 40% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 4 countries.

Caaisha WarsameSchool of Engineering, London South Bank University, 103 Borough Road, London, SE1 0AA, UK.
Daniele ValeriniSSPT-PROMAS-MATAS, ENEA - Italian National Agency for New Technologies, Energy and Sustainable Economic Development, S.S. 7 Appia, km 706, 72100, Brindisi, Italy.
Iñigo LlavoriFaculty of Engineering, Mondragon Unibertsitatea, 20500, Arrasate, Gipuzkoa, Spain.
Asa H BarberSchool of Engineering, London South Bank University, 103 Borough Road, London, SE1 0AA, UK.
Saurav GoelSchool of Engineering, London South Bank University, 103 Borough Road, London, SE1 0AA, UK; Department of Mechanical Engineering, University of Petroleum and Energy Studies, Dehradun, 248007, India. Electronic address: goels@lsbu.ac.uk.
London South Bank University · GBMondragon Unibertsitatea · ESNational Agency for New Technologies, Energy and Sustainable Economic Development · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

COVID-19SARS-CoV-2Finite Element AnalysisHumansPandemicsSpike Glycoprotein, CoronavirusSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2COVID-19Finite element analysis (FEA)Modal analysisNatural frequenciesSARS-CoV-2

Identifiers

PMID36075162
PMCPMC9391233
OpenAlexW4292805325

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.