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A Nanofluidic Biosensor Based on Nanoreplica Molding Photonic Crystal

Overview of attention for article published in Nanoscale Research Letters, September 2016
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Title
A Nanofluidic Biosensor Based on Nanoreplica Molding Photonic Crystal
Published in
Nanoscale Research Letters, 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.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 30%
Researcher 2 20%
Student > Ph. D. Student 2 20%
Unknown 3 30%
Readers by discipline Count As %
Engineering 2 20%
Computer Science 1 10%
Medicine and Dentistry 1 10%
Physics and Astronomy 1 10%
Materials Science 1 10%
Other 1 10%
Unknown 3 30%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 September 2016.
All research outputs
#20,342,896
of 22,889,074 outputs
Outputs from Nanoscale Research Letters
#726
of 1,079 outputs
Outputs of similar age
#279,282
of 321,669 outputs
Outputs of similar age from Nanoscale Research Letters
#19
of 26 outputs
Altmetric has tracked 22,889,074 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,079 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 321,669 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.