Vapor detection through dynamic process of molecule desorption from butterfly wings
Abstract: This work explores an alternative vapor sensing mechanism through analyzing dynamic desorption process from butterfly wings for the differentiation of both individual and mixed vapors quantitatively. Morpho butterfly wings have been used in differentiating individual vapors, but it is challenging to use them for the differentiation of mixed vapor quantitatively. This paper demonstrates the use of Morpho butterfly wings for the sensitive and selective detection of closely related vapors in mixtures. Principal components analysis (PCA) is used to process the reflectance spectra of the wing scales during dynamic desorption of different vapors. With the desorption-based detection mechanism, individual vapors with different concentrations and mixed vapors with different mixing ratios can be differentiated using the butterfly wing based sensors. Both the original butterfly wings and butterfly wings with surface modification show the capability in distinguishing vapors in mixtures, which may offer a guideline for further improving selectivity and sensitivity of bioinspired sensors.
- 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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Vapor detection through dynamic process of molecule desorption from butterfly wings ; volume:92 ; number:2 ; year:2020 ; pages:223-232 ; extent:10
Pure and applied chemistry ; 92, Heft 2 (2020), 223-232 (gesamt 10)
- Urheber
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Luo, Zhen
Weng, Zhaoyue
Shen, Qingchen
An, Shun
He, Jiaqing
Fu, Benwei
Zhang, Ruoxi
Tao, Peng
Song, Chengyi
Wu, Jianbo
Deng, Tao
Shang, Wen
- DOI
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10.1515/pac-2019-0118
- URN
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urn:nbn:de:101:1-2024030513071113428279
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
- 14.08.2025, 10:55 MESZ
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Beteiligte
- Luo, Zhen
- Weng, Zhaoyue
- Shen, Qingchen
- An, Shun
- He, Jiaqing
- Fu, Benwei
- Zhang, Ruoxi
- Tao, Peng
- Song, Chengyi
- Wu, Jianbo
- Deng, Tao
- Shang, Wen