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Optimization and predictive modelling for the diameter of nylon-6,6 nanofibers via electrospinning for coronavirus face masks
Currently, the only widely available tool for controlling the SARS-CoV-2 pandemic is nonpharmacological interventions (NPIs). Coronavirus aerosols are around 0.3–2 µm in diameter (0.9 m in mass). The present study used artificial intelligence such as gene expression programming (GEP) and genetic alg...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier B.V. on behalf of King Saud University.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8434686/ http://dx.doi.org/10.1016/j.jscs.2021.101348 |
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author | Zeraati, Malihe Pourmohamad, Rana Baghchi, Bahareh Singh Chauhan, Narendra Pal Sargazi, Ghasem |
author_facet | Zeraati, Malihe Pourmohamad, Rana Baghchi, Bahareh Singh Chauhan, Narendra Pal Sargazi, Ghasem |
author_sort | Zeraati, Malihe |
collection | PubMed |
description | Currently, the only widely available tool for controlling the SARS-CoV-2 pandemic is nonpharmacological interventions (NPIs). Coronavirus aerosols are around 0.3–2 µm in diameter (0.9 m in mass). The present study used artificial intelligence such as gene expression programming (GEP) and genetic algorithms (GA) were used to predict and optimize the diameter of Nylon-6,6 nanofibers via electrospinning for protection against coronavirus. It is suggested that using the controlled experimental conditions such as concentration of nylon-6,6 (16% wt/v), applied voltage (26 kV), working distance (18 cm) and injection rate (0.2 mL/h) have resulted the diameter of nylon-6,6 nanofibers about 55.8 nm. Coronavirus face masks could use the obtained diameter and electrostatic interaction between viral particles and naofibers as active layers. |
format | Online Article Text |
id | pubmed-8434686 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Author(s). Published by Elsevier B.V. on behalf of King Saud University. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84346862021-09-13 Optimization and predictive modelling for the diameter of nylon-6,6 nanofibers via electrospinning for coronavirus face masks Zeraati, Malihe Pourmohamad, Rana Baghchi, Bahareh Singh Chauhan, Narendra Pal Sargazi, Ghasem Journal of Saudi Chemical Society Original Article Currently, the only widely available tool for controlling the SARS-CoV-2 pandemic is nonpharmacological interventions (NPIs). Coronavirus aerosols are around 0.3–2 µm in diameter (0.9 m in mass). The present study used artificial intelligence such as gene expression programming (GEP) and genetic algorithms (GA) were used to predict and optimize the diameter of Nylon-6,6 nanofibers via electrospinning for protection against coronavirus. It is suggested that using the controlled experimental conditions such as concentration of nylon-6,6 (16% wt/v), applied voltage (26 kV), working distance (18 cm) and injection rate (0.2 mL/h) have resulted the diameter of nylon-6,6 nanofibers about 55.8 nm. Coronavirus face masks could use the obtained diameter and electrostatic interaction between viral particles and naofibers as active layers. The Author(s). Published by Elsevier B.V. on behalf of King Saud University. 2021-11 2021-09-11 /pmc/articles/PMC8434686/ http://dx.doi.org/10.1016/j.jscs.2021.101348 Text en © 2021 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Original Article Zeraati, Malihe Pourmohamad, Rana Baghchi, Bahareh Singh Chauhan, Narendra Pal Sargazi, Ghasem Optimization and predictive modelling for the diameter of nylon-6,6 nanofibers via electrospinning for coronavirus face masks |
title | Optimization and predictive modelling for the diameter of nylon-6,6 nanofibers via electrospinning for coronavirus face masks |
title_full | Optimization and predictive modelling for the diameter of nylon-6,6 nanofibers via electrospinning for coronavirus face masks |
title_fullStr | Optimization and predictive modelling for the diameter of nylon-6,6 nanofibers via electrospinning for coronavirus face masks |
title_full_unstemmed | Optimization and predictive modelling for the diameter of nylon-6,6 nanofibers via electrospinning for coronavirus face masks |
title_short | Optimization and predictive modelling for the diameter of nylon-6,6 nanofibers via electrospinning for coronavirus face masks |
title_sort | optimization and predictive modelling for the diameter of nylon-6,6 nanofibers via electrospinning for coronavirus face masks |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8434686/ http://dx.doi.org/10.1016/j.jscs.2021.101348 |
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