The COVID-19 pandemic, caused by SARS-CoV-2, highlighted the crucial role of face masks in mitigating transmission. While mask mandates were widely implemented, the efficacy of different mask types remained debated due to a lack of detailed microstructure information. Previous studies primarily focused on overall mask performance, lacking comprehensive 3D microstructural analysis. This paper addresses this gap by applying advanced imaging and modeling techniques to understand the relationship between the microstructure of commonly used face masks and their filtration efficiency and breathability. The research question centers on how the micro- and nanoscale fiber structures of different face masks affect their ability to filter respiratory droplets, and how this relates to their breathability and overall efficacy in preventing COVID-19 transmission. The study's purpose is to provide a quantitative, three-dimensional understanding of the porous structures of these masks, enabling a more rational assessment of their protective capabilities. This information is crucial for informing public health guidelines and guiding the development of improved face mask designs. The importance of the study lies in its potential to contribute significantly to the ongoing efforts to control the spread of respiratory viruses, by providing data-driven insights into the design and performance of face masks.

Existing research on face mask efficacy has primarily focused on macroscopic performance metrics, such as filtration efficiency, using methods like optical measurement of droplet filtering (Fischer et al., 2020) and high-speed camera evaluation of droplet blocking (Aydin et al., 2020). However, these studies provided limited insights into the underlying microstructures. Some investigations utilized 2D imaging techniques (Wang et al., 2020; Mehta et al., 2019), which inherently limit the information obtained about spatial connectivity and percolation behavior. While Lee et al. (2020) characterized N95 filter layers using X-ray tomography, a comprehensive comparison across different widely used mask types was lacking. This study builds upon previous research by combining high-resolution 3D imaging (X-ray CT) with image-based modeling, providing a detailed understanding of the correlation between the micro- and nanoscale fibrous structures and the macroscopic performance of face masks.

Three commercially available face masks—a reusable mask, a surgical mask, and an N95 mask—were selected for analysis. The microstructure of each mask was characterized using a lab-based X-ray micro-scale CT scanner (ZEISS Xradia 620 Versa) at a high resolution (350 nm). Both standard and advanced iterative reconstruction algorithms were employed to obtain high-quality 3D images of the mask structures. Scanning electron microscopy (SEM) provided supplementary 2D surface imaging. The 3D images were analyzed using Avizo software to quantify several microstructural parameters, including volume fraction of fibres and air, specific surface area, pore size distribution, and fibre length and diameter. A pore network model (PNM) was generated to simulate the flow of respiratory droplets through the porous structures. The permeability of each mask was then calculated using Avizo XLab Hydro, an image-based model simulating fluid flow within the porous structures using the Stokes’ equations. In order to assess breathability and comfort, real-time infrared (IR) thermal imaging (FLIR One Pro LT) was used to measure temperature changes on the wearer's face while inhaling and exhaling. The dataset of this research work was made available freely online.

High-resolution X-ray CT revealed distinct microstructures for each mask type. The reusable mask exhibited a single-layer morphology with large pores. The surgical mask displayed a three-layer structure, with the middle layer composed of a denser mixture of micro- and nano-fibers. The N95 mask contained a dense filter layer (~250 µm thick) consisting mainly of nanoscale fibers, covered by a shield-like outer layer. Quantitative analysis showed that the N95 mask had the lowest porosity (65%), the smallest average pore diameter (~30 µm), and the highest specific surface area (0.64 µm²/µm³). Pore Network Modeling (PNM) visually demonstrated the differences in pore size distribution, with the N95 mask having a significantly larger proportion of small pores compared to the reusable and surgical masks. Image-based simulations revealed that the N95 mask had the lowest permeability, indicating superior filtration performance. Infrared thermal imaging confirmed that the N95 mask had the lowest temperature on the wearer's face, further suggesting restricted airflow and high filtration efficiency, while the reusable mask exhibited the highest temperature indicating better breathability. The average fibre lengths were 219 μm, 143 μm and 126 μm for the reusable, surgical and N95 masks respectively. The average fibre diameters were 13.8 μm, 5.6 μm and 2.2 μm for the reusable, surgical and N95 masks respectively. The N95 mask’s superior filtration was attributed to the combination of the shield-like outer layer, dense nanoscale fibers in the filter layer, and high specific surface area, which facilitate impaction, interception, and diffusion of droplets.

The findings directly address the research question by demonstrating a strong correlation between the microstructure of face masks and their filtration performance. The superior filtration efficacy of the N95 mask is explained by its unique microstructural features: a shield layer reducing initial droplet momentum, a high density of nanoscale fibers maximizing surface area for droplet capture, and a combination of micro and nano fibers for capturing various sizes of droplets. The smaller pore size distribution in the N95 mask compared to the other masks is crucial, effectively preventing the passage of droplets containing the virus. These findings have significant implications for public health, providing scientific evidence to support the use of N95 masks in high-risk environments. The results also highlight the potential for optimizing mask design through microstructural engineering to achieve a balance between filtration efficacy and breathability. The detailed 3D analysis offers a significant advancement over previous studies relying on limited 2D observations. This detailed understanding is essential for developing the next generation of face masks with superior performance.

This study provides a comprehensive, quantitative analysis of the microstructure and performance of three common face mask types using advanced imaging and modeling techniques. The results demonstrate the superior filtration efficacy of the N95 mask, attributable to its unique microstructural properties. This research supports the use of N95 masks in high-risk settings and offers valuable insights for future mask design optimization by suggesting specific modifications to improve breathability while maintaining high filtration efficiency. Future research could explore the influence of additional factors like electrostatic charge, humidity, and dynamic airflow conditions on mask performance.

The study focuses on three specific commercially available mask models. The findings may not be generalizable to all masks within each category. The image-based simulation simplified the complex fluid dynamics of droplet flow, potentially introducing some inaccuracies. The IR thermal imaging provided a qualitative assessment of breathability, lacking precise quantitative measures of airflow resistance. Finally, the study did not account for the effects of long-term use, such as fiber degradation or changes in electrostatic charge, which could alter mask performance.