Microstructure analysis and image-based modelling of face masks for COVID-19 virus protection

Abstract

SARS-CoV-2 may spread through respiratory droplets released by infected individuals. The viruses are transmitted in moist droplets which cause coronavirus disease. Many countries have mandated the wearing of face masks, to various extents. However, the efficacy of masks is yet to be well rationalised given the limited microstructure information. Here, three common face masks and associated air permeations were revealed by coupling X-ray tomographic imaging and infrared thermal imaging techniques. Quantitative parameters have been extracted from the 3D images. Also, image-based modelling was performed to simulate the permeability to show how droplets pass through the porous structure. Our results show that the N95 mask has the smallest average pore diameter (~30\u2009µm) and the densest nanoscale fibres which provides superior droplet filtration among all cases. Modifications to the N95 masks are proposed to develop the next generation mask with higher efficacy and better breathability. Face masks are key for slowing the spread of COVID-19. Here, the microstructure of three common masks is determined by x-ray tomography, combined with image-based modelling of droplet permeability, revealing that N95 masks are best for droplet filtration.