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An Open Software Platform for the Automated Design of Paper-Based Microfluidic Devices

Overview of attention for article published in Scientific Reports, November 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

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4 X users
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1 patent

Citations

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Readers on

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51 Mendeley
Title
An Open Software Platform for the Automated Design of Paper-Based Microfluidic Devices
Published in
Scientific Reports, November 2017
DOI 10.1038/s41598-017-16542-8
Pubmed ID
Authors

Nicholas S. DeChiara, Daniel J. Wilson, Charles R. Mace

Abstract

Paper-based microfluidic devices have many applications in biomedical and environmental analysis. However, the process of prototyping device designs can be tedious, error-prone, and time-consuming. Here, we present a cross-platform, open-source software tool-AutoPAD-developed to quickly create and modify device designs and provide a free alternative to commercial design software. The capabilities that we designed to be inherent to AutoPAD (e.g., automatic zone alignment and design refactoring) highlight its potential use in nearly any paper-based microfluidic device application and for creating nearly any desired design, which we demonstrate through the recreation of numerous device designs from the literature.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 22%
Student > Master 7 14%
Student > Bachelor 5 10%
Researcher 4 8%
Professor > Associate Professor 4 8%
Other 12 24%
Unknown 8 16%
Readers by discipline Count As %
Chemistry 11 22%
Engineering 10 20%
Biochemistry, Genetics and Molecular Biology 4 8%
Psychology 2 4%
Nursing and Health Professions 2 4%
Other 8 16%
Unknown 14 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 June 2022.
All research outputs
#5,788,451
of 23,911,072 outputs
Outputs from Scientific Reports
#39,224
of 129,782 outputs
Outputs of similar age
#107,346
of 444,762 outputs
Outputs of similar age from Scientific Reports
#1,150
of 4,076 outputs
Altmetric has tracked 23,911,072 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 129,782 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.5. This one has gotten more attention than average, scoring higher than 69% 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 444,762 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 4,076 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.