Plant Nanobionic Sensors for Arsenic Detection

© 2020 Wiley-VCH GmbH.

Bibliographische Detailangaben
Veröffentlicht in:Advanced materials (Deerfield Beach, Fla.). - 1998. - 33(2021), 1 vom: 21. Jan., Seite e2005683
1. Verfasser: Lew, Tedrick Thomas Salim (VerfasserIn)
Weitere Verfasser: Park, Minkyung, Cui, Jianqiao, Strano, Michael S
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2021
Zugriff auf das übergeordnete Werk:Advanced materials (Deerfield Beach, Fla.)
Schlagworte:Journal Article arsenic carbon nanotubes molecular recognition nanoparticles optical sensors plant nanobionics Arsenic N712M78A8G arsenite mehr... N5509X556J Arsenites
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520 |a Arsenic is a highly toxic heavy-metal pollutant which poses a significant health risk to humans and other ecosystems. In this work, the natural ability of wild-type plants to pre-concentrate and extract arsenic from the belowground environment is exploited to engineer plant nanobionic sensors for real-time arsenic detection. Near-infrared fluorescent nanosensors are specifically designed for sensitive and selective detection of arsenite. These optical nanosensors are embedded in plant tissues to non-destructively access and monitor the internal dynamics of arsenic taken up by the plants via the roots. The integration of optical nanosensors with living plants enables the conversion of plants into self-powered autosamplers of arsenic from their environment. Arsenite detection is demonstrated with three different plant species as nanobionic sensors. Based on an experimentally validated kinetic model, the nanobionic sensor could detect 0.6 and 0.2 ppb levels of arsenic after 7 and 14 days respectively by exploiting the natural ability of Pteris cretica ferns to hyperaccumulate and tolerate exceptionally high level of arsenic. The sensor readout could also be interfaced with portable electronics at a standoff distance, potentially enabling applications in environmental monitoring and agronomic research 
650 4 |a Journal Article 
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650 4 |a carbon nanotubes 
650 4 |a molecular recognition 
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700 1 |a Park, Minkyung  |e verfasserin  |4 aut 
700 1 |a Cui, Jianqiao  |e verfasserin  |4 aut 
700 1 |a Strano, Michael S  |e verfasserin  |4 aut 
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