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RAPID: Highly Customizable, Breathable N95 Mask Design Utilizing Kirigami-enabled Filters and Sensor Platforms to Maximize Comfort and Monitor usage Patterns

RAPID: Highly Customizable, Breathable N95 Mask Design Utilizing Kirigami-enabled Filters and Sensor Platforms to Maximize Comfort and Monitor usage Patterns
RAPID:高度可定制、透气的 N95 口罩设计,利用 Kirigami 功能的过滤器和传感器平台来最大限度地提高舒适度并监控使用模式
批准号:
2034626
负责人:
Max Shtein
金额:
$20.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-08-01 至 2022-01-31

项目摘要

项目成果

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中文摘要
翻译
智力优势:该项目提出开发一种可快速制造的新型N95级呼吸器设计平台,该平台将舒适性和过滤效率之间的关系进行了简化。大多数N95呼吸器口罩佩戴不当,即使是经过培训的医务人员也是如此,这是由于在优化舒适度而不是过滤功效时佩戴和贴合不当造成的。 拟议的N95净化器将能够监测和最大限度地减少面部接触,并跟踪清洁周期和使用模式。该项目将克服目前N95型呼吸器口罩设计中的几个基本缺陷,以及它们的贴合和佩戴协议。所提出的设计最大限度地提高了紧凑性,舒适性和可制造性,同时能够实时监控面部触摸事件。研究团队将利用针织技术的最新进展,以无缝和半定制的方式可控地放置刚性和顺应性元件,可以在广泛部署的可穿戴技术上运行的传感算法,以及新颖的kirigami/origami启发的传感器平台和过滤器有效性的机械增强。尽管这些元素的先进性,该项目将使用现有的硬件和制造能力,并计划迅速过渡到具有成本效益的实施。更广泛的影响:研究表明,间隙(如口罩的不合适造成的)可能导致过滤效率下降超过60%,这意味着未来的布口罩设计研究需要考虑“适合”和泄漏的问题,同时允许呼出的空气有效地排出。 该项目中使用的支持过滤的方法允许使用迄今为止尚未用于医用级口罩的工业产能,以更广泛的尺寸和适配选项制造N-95级口罩。 这些设计的成功实施将导致生产更多的PPE并提供给医护人员。虽然拟议的制造工艺最初成本较高,但面罩结构将符合必要的标准,以允许可重复使用并随着时间的推移持续贴合;显著降低其每次使用成本。此外,这种实现半定制或完全定制的方法可以更广泛地适用于各种可穿戴服装和设备。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
Intellectual Merit: 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.
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