Performance evaluation of face mask: from textile filtration determination to air leakage minimization
Year: 2026
Type: article
Abstract: The SARS-CoV-2 pandemic emphasized the critical role of face masks in preventing the transmission of respiratory viruses, especially in medical settings. Respiratory viruses, including SARS, influenza, and adenoviruses are primarily transmitted through the respiratory pathways, making face masks the primary barrier for protection. This study aims to evaluate and compare the filtration efficiency and pressure differentials of different face masks to contribute to the development of a comprehensive test bench for medical textiles. Unlike prior fit-testing approaches that assess mask fit only as a wearing condition, this study introduces a test bench that independently quantifies nasal and oral air leakage under controlled sealing configurations, providing a reproducible platform for evaluating custom sealing accessories. The design of a sealing device is also evaluated to assess the effectiveness of a physical external sealer. The study focuses on designing and evaluating accessory seals for face masks to determine air loss percentages in areas where the mask is not in complete contact with the face. The creation of a test bench for textiles in medical use is intended to contribute valuable insights into mask performance, addressing both filtration efficiency and pressure differentials. The study evaluates different face masks including N95, surgical, and newly developed fabrics. Results revealed that N95 masks consistently demonstrate superior filtration efficiency and acceptable pressure differentials across specific flow rates. Thus, understanding face mask efficacies is crucial for optimizing mask designs, contributing to the advancement of protective measures against respiratory diseases.
Source: Scientific Reports
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W7225739577
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