Ultrafine and bimodal structured polyamide-6 nanofiber/nets membrane for air nanofiltration
Source abstract
Abstract
Particulate matter and spread of viruses, including COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are two of the most serious problems because of their significant threat to human health. Here, we fabricate ultrafine and bimodal structured polyamide-6 nanofiber/nets (PA-6 NFN) membrane via one-step electrospinning/netting. The PA-6 NFN membranes include ultrafine (∼70 nm) nanofibers and two-dimensional (2D) ultrathin (∼20 nm) nanonets. These membranes are optimized by facilely regulating the solution concentration, incomplete phase separation by adding NaCl, and also applying a high voltage of 22 kV. With integrated properties of small pore size, high porosity, high specific surface area of 108.8 m 2 /g, and robust tensile strength of 13.70 MPa, the resultant PA-6 NFN membranes exhibit high filtration efficiency of 99.11%, low pressure drop of 81 Pa, and higher quality factor compared to the two standard commercial masks which consist of three-ply surgical mask and respirator face mask. It can include bacteria, fungi, and also viruses including SARS-CoV-2 (with a diameter of about 100 nm). Additionally, after 24 h of operation of the filtration process in a simulated living environment, the obtained air filter still displayed a high filtration efficiency and a less variation pressure drop that shows the long-term performance of PA-6 NFN membranes. In addition, the R 2 value was 0.99, which indicates that the calculation results are in good agreement with the measured results. The fabrication of PA-6 NFN membrane makes it a promising candidate for PM0.3 governance at applications including face mask, protective clothing, clean room, and engine intake.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Electrospun Nanofibers in Biomedical Applications · Membrane Separation Technologies · Advanced Sensor and Energy Harvesting Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Engineering, Department of Textile Engineering, University of Guilan, Rasht, Iran
Department of Textile Engineering, Amirkabir University of Technology, Tehran, Iran
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