Dynamic Pore Modulation of Stretchable Electrospun Nanofiber Filter for Adaptive Machine Learned Respiratory Protection

Jaeho Shin; Seongmin Jeong; Jinmo Kim; Yun Young Choi; Joonhwa Choi; Jae Gun Lee; Seongyoon Kim; Munju Kim; Yoonsoo Rho; Sukjoon Hong; Jung Il Choi; Costas P. Grigoropoulos; Seung Hwan Ko

doi:10.1021/acsnano.1c06204

Dynamic Pore Modulation of Stretchable Electrospun Nanofiber Filter for Adaptive Machine Learned Respiratory Protection

Jaeho Shin, Seongmin Jeong, Jinmo Kim, Yun Young Choi, Joonhwa Choi, Jae Gun Lee, Seongyoon Kim, Munju Kim, Yoonsoo Rho, Sukjoon Hong, Jung Il Choi, Costas P. Grigoropoulos, Seung Hwan Ko

Department of Computational Science and Engineering

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

Abstract

The recent emergence of highly contagious respiratory disease and the underlying issues of worldwide air pollution jointly heighten the importance of the personal respirator. However, the incongruence between the dynamic environment and nonadaptive respirators imposes physiological and psychological adverse effects, which hinder the public dissemination of respirators. To address this issue, we introduce adaptive respiratory protection based on a dynamic air filter (DAF) driven by machine learning (ML) algorithms. The stretchable elastomer fiber membrane of the DAF affords immediate adjustment of filtration characteristics through active rescaling of the micropores by simple pneumatic control, enabling seamless and constructive transition of filtration characteristics. The resultant DAF-respirator (DAF-R), made possible by ML algorithms, successfully demonstrates real-time predictive adapting maneuvers, enabling personalizable and continuously optimized respiratory protection under changing circumstances.

Original language	English
Pages (from-to)	15730-15740
Number of pages	11
Journal	ACS Nano
Volume	15
Issue number	10
DOIs	https://doi.org/10.1021/acsnano.1c06204
Publication status	Published - 2021 Oct 26

Bibliographical note

Funding Information:
This work is supported by the National Research Foundation of Korea (No. 2021R1A2B5B03001691). All experiments in this research associated with the human experiment were consulted and approved by the institutional review board (IRB) of Seoul National University (Approval number, 2008/003-023). Informed consent was obtained from the volunteers of the human experiments prior to participation in this study. The person displayed in and (S.J.) acknowledges and agrees with the use of his image in this article.

Publisher Copyright:
© 2021 American Chemical Society.

All Science Journal Classification (ASJC) codes

Materials Science(all)
Engineering(all)
Physics and Astronomy(all)

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10.1021/acsnano.1c06204

Cite this

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title = "Dynamic Pore Modulation of Stretchable Electrospun Nanofiber Filter for Adaptive Machine Learned Respiratory Protection",

abstract = "The recent emergence of highly contagious respiratory disease and the underlying issues of worldwide air pollution jointly heighten the importance of the personal respirator. However, the incongruence between the dynamic environment and nonadaptive respirators imposes physiological and psychological adverse effects, which hinder the public dissemination of respirators. To address this issue, we introduce adaptive respiratory protection based on a dynamic air filter (DAF) driven by machine learning (ML) algorithms. The stretchable elastomer fiber membrane of the DAF affords immediate adjustment of filtration characteristics through active rescaling of the micropores by simple pneumatic control, enabling seamless and constructive transition of filtration characteristics. The resultant DAF-respirator (DAF-R), made possible by ML algorithms, successfully demonstrates real-time predictive adapting maneuvers, enabling personalizable and continuously optimized respiratory protection under changing circumstances.",

author = "Jaeho Shin and Seongmin Jeong and Jinmo Kim and Choi, {Yun Young} and Joonhwa Choi and Lee, {Jae Gun} and Seongyoon Kim and Munju Kim and Yoonsoo Rho and Sukjoon Hong and Choi, {Jung Il} and Grigoropoulos, {Costas P.} and Ko, {Seung Hwan}",

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AU - Choi, Joonhwa

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AU - Choi, Jung Il

AU - Grigoropoulos, Costas P.

AU - Ko, Seung Hwan

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Dynamic Pore Modulation of Stretchable Electrospun Nanofiber Filter for Adaptive Machine Learned Respiratory Protection

Abstract

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