Author: Zeraati, Malihe; Pourmohamad, Rana; Baghchi, Bahareh; Singh Chauhan, Narendra Pal; Sargazi, Ghasem
Title: Optimization and predictive modelling for the diameter of Nylon-6,6 Nanofibers via electrospinning for coronavirus face masks Cord-id: yvlpaf7l Document date: 2021_9_11
ID: yvlpaf7l
Snippet: Currently, the only widely available tool for controlling the SARS-CoV-2 pandemic is nonpharmacological interventions (NPIs). Coronavirus aerosols are around 0.3–2 microns 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 experimenta
Document: Currently, the only widely available tool for controlling the SARS-CoV-2 pandemic is nonpharmacological interventions (NPIs). Coronavirus aerosols are around 0.3–2 microns 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.
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