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Glass-based geometry-induced electrostatic trapping devices for improved scattering contrast imaging of nano-objects

Gerspach, Michael Adrian and Mojarad, Nassir and Pfohl, Thomas and Ekinci, Yasin. (2015) Glass-based geometry-induced electrostatic trapping devices for improved scattering contrast imaging of nano-objects. Microelectronic Engineering, 145. pp. 43-48.

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Official URL: http://edoc.unibas.ch/41486/

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Abstract

Trapping of micro- and nano-objects in solution is of great scientific interest in various fields. One method of trapping and detecting objects smaller than 100 nm is the combination of geometry-induced electrostatic (GIE) trapping devices and interferometric scattering detection (iSCAT). In GIE trapping, charged nano-objects are confined in a nanofluidic system that hosts topographically modified surfaces, resulting in electrostatic potential wells. We observe optical limits of detecting gold nanoparticles smaller than 60 nm because of the high reflection of the strong background signal in current silicon-based GIE trapping chips. The high reflection rapidly leads to overexposure of the camera detector and thus limits the incident laser power. In this work, we introduce new functional geometry-induced electrostatic devices fabricated from glass substrates. Due to the reduced reflection at the water–glass interface compared to the silicon-based devices, higher incident laser power can be used to image the nano-objects resulting in higher contrast as well as signal-to-noise ratios (SNR) of the gold nanoparticles. Using glass-based GIE trapping devices, significant SNR increases are achieved in comparison to that of silicon-based devices. These improvements enable the detection of much smaller nanoparticles and thereby studies on their trapping, as well as further investigation in nanofluidic systems.
Faculties and Departments:05 Faculty of Science > Departement Chemie > Chemie > Biophysikalische Chemie (Pfohl)
UniBasel Contributors:Pfohl, Thomas
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Elsevier B.V.
ISSN:0167-9317
Note:Publication type according to Uni Basel Research Database: Journal article
Identification Number:
Last Modified:30 Jun 2016 11:02
Deposited On:18 May 2016 12:00

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