Journal of hazardous materials · 2024
Ultralow-resistance and self-sterilization biodegradable nanofibrous membranes for efficient PM0.3 removal and machine learning-assisted health management.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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He Xinjian, Li Xinyu, Wang Cunmin, Li Jiaqi, Song Xinyi, Zhu Guiying, Li Xiang, Zhang Yifan, Zhu Xuanjin, Shao Jiang, Zhang Mingming, Xu Huan
Аннотация
The development of multifunctional nanofibrous membranes (NFMs) that enable anti-viral protection during air purification and respiratory disease diagnosis for health management is of increasing importance. Herein, we unraveled a heterostructure-enhanced electro-induced stereocomplexation (HEIS) strategy to fabrication of poly(lactic acid) (PLA) NFMs enabling a combination of efficient PM removal, respiratory monitoring and self-sterilization. The strategy involved an electro-induced stereocomplexation (EIS) approach to trigger the generation of hydrogen bonds between enantiomeric poly(L-lactic acid) (PLLA) and poly(D-lactic acid) (PDLA) chains, promoting CO dipole alignment and molecular polarization during electrospinning. This was further enhanced by incorporation of Ag-doped TiO2 (Ag-TIO) nanodielectrics to promote the electroactivity and surface activity, conferring profound refinement of PLA nanofibers (from 460 nm to an ultralow level of 168 nm) and high porosities of over 91 %. Arising from the sustainable generation of plentiful charges based on triboelectric nanogenerator (TENG) mechanisms, the electroactive PLA NFMs exhibited remarkable triboelectric properties even in high-humidity environments (80 %RH), excellent PM0.3 filtration efficiency with an ultralow pressure drop (93.1 %, 31.8 Pa, 32 L/min), and 100 % antimicrobial efficiency against both E. coli and S. aureus. Moreover, a deep-learning algorithm based on convolutional neural network (CNN) was proposed to recognize various respiratory patterns. The proposed strategy confers the biodegradable NFMs an unusual combination of ultralow-resistance air purification and machine learning-assisted health management, signifying promising prospects in environmental protection and personal healthcare.