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Nondestructive, real-time determination and visualization of cellulose, hemicellulose and lignin by luminescent oligothiophenes

Overview of attention for article published in Scientific Reports, October 2016
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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 (92nd percentile)

Mentioned by

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4 news outlets
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26 X users
facebook
1 Facebook page
wikipedia
2 Wikipedia pages
googleplus
1 Google+ user
reddit
1 Redditor
q&a
1 Q&A thread

Citations

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35 Dimensions

Readers on

mendeley
68 Mendeley
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Title
Nondestructive, real-time determination and visualization of cellulose, hemicellulose and lignin by luminescent oligothiophenes
Published in
Scientific Reports, October 2016
DOI 10.1038/srep35578
Pubmed ID
Authors

Ferdinand X. Choong, Marcus Bäck, Svava E. Steiner, Keira Melican, K. Peter R. Nilsson, Ulrica Edlund, Agneta Richter-Dahlfors

Abstract

Enabling technologies for efficient use of the bio-based feedstock are crucial to the replacement of oil-based products. We investigated the feasibility of luminescent conjugated oligothiophenes (LCOs) for non-destructive, rapid detection and quality assessment of lignocellulosic components in complex biomass matrices. A cationic pentameric oligothiophene denoted p-HTEA (pentamer hydrogen thiophene ethyl amine) showed unique binding affinities to cellulose, lignin, hemicelluloses, and cellulose nanofibrils in crystal, liquid and paper form. We exploited this finding using spectrofluorometric methods and fluorescence confocal laser scanning microscopy, for sensitive, simultaneous determination of the structural and compositional complexities of native lignocellulosic biomass. With exceptional photostability, p-HTEA is also demonstrated as a dynamic sensor for real-time monitoring of enzymatic cellulose degradation in cellulolysis. These results demonstrate the use of p-HTEA as a non-destructive tool for the determination of cellulose, hemicellulose and lignin in complex biomass matrices, thereby aiding in the optimization of biomass-converting technologies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 26 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 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 68 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 21%
Student > Master 12 18%
Researcher 9 13%
Student > Bachelor 4 6%
Student > Postgraduate 3 4%
Other 12 18%
Unknown 14 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 18%
Chemistry 9 13%
Biochemistry, Genetics and Molecular Biology 7 10%
Materials Science 6 9%
Immunology and Microbiology 2 3%
Other 12 18%
Unknown 20 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 54. 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 21 January 2019.
All research outputs
#667,642
of 22,893,031 outputs
Outputs from Scientific Reports
#7,379
of 123,706 outputs
Outputs of similar age
#14,267
of 315,872 outputs
Outputs of similar age from Scientific Reports
#255
of 3,571 outputs
Altmetric has tracked 22,893,031 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 123,706 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.2. This one has done particularly well, scoring higher than 94% 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 315,872 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 3,571 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.