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Abstract

Emerging environmental problems, especially air pollution and airborne pathogens, have engendered growing public health concerns due to its adverse effects on humanity. To prevent inhalation of these pollutants, face masks with high filtration efficiency and low-pressure drops are urgently needed. Melt-blown nonwovens are widely employed in air filtration applications due to their fine fibers, large surface area, high porosity, and effective filtration and barrier characteristics. The performance of melt-blown nonwovens in filtration is influenced by various factors, including fiber diameter, mean pore diameter, and electrostatic effects from electrets. Previous research has aimed to enhance air filtration technologies by exploring the interplay between structure, barrier performance, and mechanical properties. This research aims to investigate the impact of two key process variables, namely air pressure and die to collector distance (DCD), on the structural and barrier properties of melt-blown nonwovens. These properties encompass fiber diameter, mean pore diameter, air permeability, pressure drop, and filtration efficiency. Additionally, the study will examine the influence of these variables on mechanical properties such as tensile strength and bursting strength. Moreover, a simple yet effective methodology will be presented for producing high-performance air filters by combining the melt-blown technique with corona charging treatment. The investigation will also focus on the effect of charging distance on filtration performance. Modifying the crystal structure of polypropylene through the addition of magnesium stearate can help prevent charge dissipation and ensure the stability of filtration performance. The study will thoroughly examine the influence of fiber diameter, pore size, air permeability, and charge storage on the filtration performance of the filter. Furthermore, this research will involve characterizing commercially available melt-blown nonwovens commonly used in air filtration. This analysis aims to gain a better understanding of the relationship between

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