Machine Learning Assisted Nanomaterials as Super hydrophobic Coatings for Antiviral Functionalities to Fight COVID-19

Saranya J, Suganthi S, Sheena Christabel Pravin, Selvakumar V. S
Anti-viral; Graphene; Health; Nanomaterials; Pandemic; Super Hydrophobic; Machine Learning.
The Coronavirus Disease-19 (COVID-19) pandemic has emerged into a severe problem. The contact spreading of the virus poses more threat to the people. The fast spreading of the virus is due to its endurance for several hours in aerosol and on flat surfaces. This necessitates the need for super hydrophobic coatings on the surfaces of Personal Protection Equipment (PPE), furniture and diagnostic equipment in hospitals. The nanomaterials have been used for inducing anti-viral and anti-bacterial characteristics to the hydrophobic solutions, converting them into super hydrophobic solutions. These nanomaterials on the hydrophobic solutions, encapsulate, suppress and eliminate viruses. For example, graphene has the ability to trap the viruses and transfer electric charges to destroy them. In this review, effective combinations and formulations of nanoparticles for disinfecting surfaces against microbes are presented. Also, the various coating techniques available for converting the fabric surfaces into a super-hydrophobic material is expounded. Further, the incorporation of machine learning models for tuning the nanomaterial parameters is also portrayed.
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Received : 17 September 2021
Accepted : 20 December 2021
Published : 27 December 2021
DOI: 10.30726/esij/v8.i4.2021.84026

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