Adaptive fabric with emissivity regulation for thermal management of humans
Abstract: The heat generation of the human body dramatically varies between resting and active status, so dynamic heat dissipation is required to ensure optimal thermal comfort. Herein, we propose a spectrally self-adaptive smart fabric (SSSF) by covering polyester fabric with silver nanowires, which autonomously adjusts its emissivity in response to the body’s movement status from dry to wet states. During periods of inactivity, the SSSF maintains radiative heat insulation with a low emissivity state of 0.39. Conversely, during vigorous physical activity, its emissivity is improved to 0.83 when the sweat penetrates the SSSF, facilitating greater heat dissipation. Comparative experiments demonstrate the superior thermal management capabilities of the SSSF, with a 19.5 % reduction in heat dissipation power relative to traditional fabrics when in the low emissivity mode, and an impressive 67.6 % enhancement in heat dissipation power as it changes from low to high emissivity mode. This work provides an adaptive approach to emissivity modulation, offering an effective solution for dynamic heat dissipation of humans across various states of activity, thereby enhancing personal thermal comfort.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Adaptive fabric with emissivity regulation for thermal management of humans ; volume:13 ; number:17 ; year:2024 ; pages:3067-3075 ; extent:9
Nanophotonics ; 13, Heft 17 (2024), 3067-3075 (gesamt 9)
- Urheber
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Li, Xiansheng
Liu, Meiling
Chen, Ken
Li, Lanxin
Pei, Gang
Zhao, Bin
- DOI
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10.1515/nanoph-2023-0930
- URN
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urn:nbn:de:101:1-2407241753036.970280095734
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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14.08.2025, 10:49 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Li, Xiansheng
- Liu, Meiling
- Chen, Ken
- Li, Lanxin
- Pei, Gang
- Zhao, Bin
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