This project proposes to develop a rapidly manufacturable novel N95 class respirator design platform that decouples the relationship between comfort and filtering efficiency. The majority of N95 respirator masks are worn improperly even by trained medical personnel, caused by improper donning and fit when optimizing for comfort instead of filtering efficacy. The proposed N95 respirators would enable the monitoring and minimization of face touching and track cleaning cycles and usage patterns. The project will circumvent several fundamental shortcomings in the design of current N95 style respirator masks, as well as their fit and wear protocols. The proposed design maximizes compactness, comfort, and manufacturability, while enabling real-time monitoring of face-touch events. The research team will use the latest advances in knitting technology that controllably place stiff and compliant elements in a seamless and semi-customized manner, sensing algorithms that can run on widely deployed wearable technology, as well as novel kirigami/origami-inspired sensor platforms and mechanical enhancement for filter effectiveness. Despite the advanced nature of these elements, the project will use current hardware and manufacturing capacity and plans to quickly transition to cost-effective implementation.

Broader Impact: Studies have implied that gaps (as caused by an improper fit of the mask) can result in over a 60% decrease in the filtration efficiency, implying the need for future cloth mask design studies to take into account issues of "fit" and leakage, while allowing the exhaled air to vent efficiently. The knitting-enabled approach used in this project allows for N-95 class of masks to be manufactured with a wider variety of size and fit options, using industrial capacity that has not been used to date for medical-grade masks. Successful implementation of these designs will result in greater numbers of PPE produced and made available to healthcare workers. Although the proposed manufacturing process will be more costly initially, the mask construction will meet the necessary standards to allow for reusability and continued fit over time; significantly reducing its per-use cost. Furthermore, this approach to achieving semi- or fully customized fit of something as varied as the human face can be more broadly adapted to a variety of wearable garments and devices.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Emerging Frontiers (EF)
Type
Standard Grant (Standard)
Application #
2034626
Program Officer
Alias Smith
Project Start
Project End
Budget Start
2020-08-01
Budget End
2021-07-31
Support Year
Fiscal Year
2020
Total Cost
$200,000
Indirect Cost
Name
Regents of the University of Michigan - Ann Arbor
Department
Type
DUNS #
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109