Assessment and design of filters and masks against COVID-19 via modeling and simulations.

Abstract

This study aimed to evaluate and design masks against viruses, especially SARS-CoV-2 associated with COVID-19. A continuum filtration model was developed where the rate of particle deposition and "sticking" on the filter fibers is a critical term in the mass transfer, together with permeation velocity, filter porosity, tortuosity, and Brownian diffusion. CFD simulations of the airflow during respiration lead to the recommendation that the filter permeability should be above 4 × 10^-11 m² to direct the airflow for effectiveness against virus particles; otherwise, low filter permeabilities cause the unfiltered air to flow preferentially through the leak gaps between the mask and the headform. Different mask filters with microstructural and geometry data from the literature are assessed via filtration simulations for breathability and filtration efficiency. The results demonstrate that a surgical mask of 25% porosity, pore size of 150 µm and permeability of 4.4 × 10^-11 m² can achieve 100% minimum efficiency while demonstrating high breathability, complying with the criteria of FFP3, N95, and surgical Class II and IIR masks. Selected cotton and synthetic cloths as well as electrospun fiber layers are predicted to comply with FFP2, N95, and surgical mask Class II and IIR standards.