Literature DB >> 34326352

Discovery of nanoscale sanal flow choking in cardiovascular system: exact prediction of the 3D boundary-layer-blockage factor in nanotubes.

V R Sanal Kumar1,2,3, Vigneshwaran Sankar4,5,6, Nichith Chandrasekaran4,5, Sulthan Ariff Rahman Mohamed Rafic5, Ajith Sukumaran5, Pradeep Kumar Radhakrishnan7, Shiv Kumar Choudhary8.   

Abstract

Evidences are escalating on the diverse neurological-disorders and asymptomatic cardiovascular-diseases associated with COVID-19 pandemic due to the Sanal-flow-choking. Herein, we established the proof of the concept of nanoscale Sanal-flow-choking in real-world fluid-flow systems using a closed-form-analytical-model. This mathematical-model is capable of predicting exactly the 3D-boundary-layer-blockage factor of nanoscale diabatic-fluid-flow systems (flow involves the transfer of heat) at the Sanal-flow-choking condition. As the pressure of the diabatic nanofluid and/or non-continuum-flows rises, average-mean-free-path diminishes and thus, the Knudsen-number lowers heading to a zero-slip wall-boundary condition with the compressible-viscous-flow regime in the nanoscale-tubes leading to Sanal-flow-choking due to the sonic-fluid-throat effect. At the Sanal-flow-choking condition the total-to-static pressure ratio (ie., systolic-to-diastolic pressure ratio) is a unique function of the heat-capacity-ratio of the real-world flows. The innovation of the nanoscale Sanal-flow-choking model is established herein through the entropy relation, as it satisfies all the conservation-laws of nature. The physical insight of the boundary-layer-blockage persuaded nanoscale Sanal-flow-choking in diabatic flows presented in this article sheds light on finding solutions to numerous unresolved scientific problems in physical, chemical and biological sciences carried forward over the centuries because the mathematical-model describing the phenomenon of Sanal-flow-choking is a unique scientific-language of the real-world-fluid flows. The 3D-boundary-layer-blockage factors presented herein for various gases are universal-benchmark-data for performing high-fidelity in silico, in vitro and in vivo experiments in nanotubes.
© 2021. The Author(s).

Entities:  

Year:  2021        PMID: 34326352     DOI: 10.1038/s41598-021-94450-8

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  22 in total

1.  Self-healing materials: Get ready for repair-and-go.

Authors:  Scott R White; Philippe H Geubelle
Journal:  Nat Nanotechnol       Date:  2010-04       Impact factor: 39.213

Review 2.  Fluid flow in carbon nanotubes and nanopipes.

Authors:  M Whitby; N Quirke
Journal:  Nat Nanotechnol       Date:  2007-02       Impact factor: 39.213

3.  The struggle for control.

Authors:  Alberto Moscatelli
Journal:  Nat Nanotechnol       Date:  2013-12       Impact factor: 39.213

4.  The road ahead.

Authors:  Roberto Cingolani
Journal:  Nat Nanotechnol       Date:  2013-11       Impact factor: 39.213

Review 5.  Minimum information reporting in bio-nano experimental literature.

Authors:  Matthew Faria; Mattias Björnmalm; Kristofer J Thurecht; Stephen J Kent; Robert G Parton; Maria Kavallaris; Angus P R Johnston; J Justin Gooding; Simon R Corrie; Ben J Boyd; Pall Thordarson; Andrew K Whittaker; Molly M Stevens; Clive A Prestidge; Christopher J H Porter; Wolfgang J Parak; Thomas P Davis; Edmund J Crampin; Frank Caruso
Journal:  Nat Nanotechnol       Date:  2018-09-06       Impact factor: 39.213

6.  Slip length measurement of gas flow.

Authors:  Abdelhamid Maali; Stéphane Colin; Bharat Bhushan
Journal:  Nanotechnology       Date:  2016-08-09       Impact factor: 3.874

7.  COVID-19 related stroke in young individuals.

Authors:  Johanna T Fifi; J Mocco
Journal:  Lancet Neurol       Date:  2020-09       Impact factor: 44.182

8.  Vascular bursts enhance permeability of tumour blood vessels and improve nanoparticle delivery.

Authors:  Yu Matsumoto; Joseph W Nichols; Kazuko Toh; Takahiro Nomoto; Horacio Cabral; Yutaka Miura; R James Christie; Naoki Yamada; Tadayoshi Ogura; Mitsunobu R Kano; Yasuhiro Matsumura; Nobuhiro Nishiyama; Tatsuya Yamasoba; You Han Bae; Kazunori Kataoka
Journal:  Nat Nanotechnol       Date:  2016-02-15       Impact factor: 39.213

9.  COVID-19 and intracerebral haemorrhage: causative or coincidental?

Authors:  A Sharifi-Razavi; N Karimi; N Rouhani
Journal:  New Microbes New Infect       Date:  2020-03-27

Review 10.  Neurological associations of COVID-19.

Authors:  Mark A Ellul; Laura Benjamin; Bhagteshwar Singh; Suzannah Lant; Benedict Daniel Michael; Ava Easton; Rachel Kneen; Sylviane Defres; Jim Sejvar; Tom Solomon
Journal:  Lancet Neurol       Date:  2020-07-02       Impact factor: 44.182

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