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Reusable, Robust, and Accurate Laser-Generated Photonic Nanosensor

Overview of attention for article published in Nano Letters, May 2014
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

news
2 news outlets
blogs
1 blog
twitter
3 X users
patent
1 patent
facebook
1 Facebook page
wikipedia
6 Wikipedia pages

Citations

dimensions_citation
99 Dimensions

Readers on

mendeley
137 Mendeley
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Title
Reusable, Robust, and Accurate Laser-Generated Photonic Nanosensor
Published in
Nano Letters, May 2014
DOI 10.1021/nl5012504
Pubmed ID
Authors

Ali K. Yetisen, Yunuen Montelongo, Fernando da Cruz Vasconcellos, J.L. Martinez-Hurtado, Sankalpa Neupane, Haider Butt, Malik M. Qasim, Jeffrey Blyth, Keith Burling, J. Bryan Carmody, Mark Evans, Timothy D. Wilkinson, Lauro T. Kubota, Michael J. Monteiro, Christopher R. Lowe

Abstract

Developing noninvasive and accurate diagnostics that are easily manufactured, robust, and reusable will provide monitoring of high-risk individuals in any clinical or point-of-care environment. We have developed a clinically relevant optical glucose nanosensor that can be reused at least 400 times without a compromise in accuracy. The use of a single 6 ns laser (λ = 532 nm, 200 mJ) pulse rapidly produced off-axis Bragg diffraction gratings consisting of ordered silver nanoparticles embedded within a phenylboronic acid-functionalized hydrogel. This sensor exhibited reversible large wavelength shifts and diffracted the spectrum of narrow-band light over the wavelength range λpeak ≈ 510-1100 nm. The experimental sensitivity of the sensor permits diagnosis of glucosuria in the urine samples of diabetic patients with an improved performance compared to commercial high-throughput urinalysis devices. The sensor response was achieved within 5 min, reset to baseline in ∼10 s. It is anticipated that this sensing platform will have implications for the development of reusable, equipment-free colorimetric point-of-care diagnostic devices for diabetes screening.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 137 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Iran, Islamic Republic of 2 1%
United Kingdom 1 <1%
United States 1 <1%
Denmark 1 <1%
Unknown 132 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 27%
Student > Master 19 14%
Researcher 15 11%
Student > Bachelor 12 9%
Other 7 5%
Other 21 15%
Unknown 26 19%
Readers by discipline Count As %
Engineering 23 17%
Chemistry 21 15%
Physics and Astronomy 17 12%
Materials Science 13 9%
Agricultural and Biological Sciences 11 8%
Other 19 14%
Unknown 33 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 34. 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 24 April 2023.
All research outputs
#1,004,653
of 22,957,478 outputs
Outputs from Nano Letters
#789
of 12,433 outputs
Outputs of similar age
#10,663
of 226,887 outputs
Outputs of similar age from Nano Letters
#20
of 182 outputs
Altmetric has tracked 22,957,478 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,433 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has done particularly well, scoring higher than 93% of its peers.
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 226,887 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 182 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.