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A Nanofluidic Biosensor Based on Nanoreplica Molding Photonic Crystal

Overview of attention for article published in Discover Nano, September 2016
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Title
A Nanofluidic Biosensor Based on Nanoreplica Molding Photonic Crystal
Published in
Discover Nano, September 2016
DOI 10.1186/s11671-016-1644-x
Pubmed ID
Authors

Wang Peng, Youping Chen, Wu Ai, Dailin Zhang

Abstract

A nanofluidic biosensor based on nanoreplica molding photonic crystal (PC) was proposed. UV epoxy PC was fabricated by nanoreplica molding on a master PC wafer. The nanochannels were sealed between the gratings on the PC surface and a taped layer. The resonance wavelength of PC-based nanofluidic biosensor was used for testing the sealing effect. According to the peak wavelength value of the sensor, an initial label-free experiment was realized with R6g as the analyte. When the PC-based biosensor was illuminated by a monochromatic light source with a specific angle, the resonance wavelength of the sensor will match with the light source and amplified the electromagnetic field. The amplified electromagnetic field was used to enhance the fluorescence excitation result. The enhancement effect was used for enhancing fluorescence excitation and emission when matched with the resonance condition. Alexa Fluor 635 was used as the target dye excited by 637-nm laser source on a configured photonic crystal enhanced fluorescence (PCEF) setup, and an initial PCEF enhancement factor was obtained.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 27%
Student > Ph. D. Student 2 18%
Researcher 2 18%
Professor > Associate Professor 1 9%
Unknown 3 27%
Readers by discipline Count As %
Engineering 3 27%
Computer Science 1 9%
Medicine and Dentistry 1 9%
Physics and Astronomy 1 9%
Materials Science 1 9%
Other 1 9%
Unknown 3 27%