Preparation of electrospun nanofiber membrane for air filtration and process optimization based on BP neural network

The filtration layer in a medical protective mask can effectively prevent aerosol particles that might carry viruses from air. A nanofiber/microfiber composite membrane (NMCM) was successfully fabricated by electrospinning polyvinylidene fluoride (PVDF) nanofibers collected on the electrified and melt-blown polypropylene (PP) nonwovens, aiming to improve the filtration efficiency and reduce the resistance of respiration of mask. A four-factor and three-level orthogonal experiment was designed to study the effect of electrospinning parameters such as spinning solution concentration, voltage, tip-collect distance (TCD), and flow rate of solution on the filtration efficiency, resistance of respiration as well as quality factor of NMC developed to predict the resistance of respiration. Experimental results demonstrated that the filtration efficiency of NMCM >= 95% in comparison to that of electrified and melt-blown PP nonwovens 79.38%, which increases by 19.68%. Additionally, the average resistance of respiration is 94.78 Pa, which meets the protection requirements. Multivariate analysis of variance indicated that the resistance of respiration of the NMCM has significantly dependent on the concentration, voltage, TCD, and flow rate of the spinning solution and the quality factor of the NMCM has dependent on the resistance of respiration. The air permeability ranges from 166.23 to 314.35 mm s(-1), which is inversely proportional to the filtration resistance. As far as the filtration resistance is concerned, the optimal spinning parameters were obtained as follows. The concentration of spinning solution is 15%, the voltage is 27 kV, the TCD is 22 cm, and the flow rate is 2.5 ml h(-1). The relative error of the BP neural network varies from 0.49505% to 1.49217%, i.e. the error value varies from 0.17 to1.33 Pa. The predicted resistance of respiration corresponding to the optimal process is 68.1374 Pa.