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Royal Society of Chemistry

Article Metrics

Honey, I shrunk the bubbles: microfluidic vacuum shrinkage of lipid-stabilized microbubbles

Overview of attention for article published in Soft Matter, January 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

twitter
10 tweeters
patent
1 patent

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
49 Mendeley
Title
Honey, I shrunk the bubbles: microfluidic vacuum shrinkage of lipid-stabilized microbubbles
Published in
Soft Matter, January 2017
DOI 10.1039/c7sm00128b
Pubmed ID
Authors

Vaskar Gnyawali, Byeong-Ui Moon, Jennifer Kieda, Raffi Karshafian, Michael C. Kolios, Scott S. H. Tsai

Abstract

We present a microfluidic technique that shrinks lipid-stabilized microbubbles from O(100) to O(1) μm in diameter - the size that is desirable in applications as ultrasound contrast agents. We achieve microbubble shrinkage by utilizing vacuum channels that are adjacent to the microfluidic flow channels to extract air from the microbubbles. We tune a single parameter, the vacuum pressure, to accurately control the final microbubble size. Finally, we demonstrate that the resulting O(1) μm diameter microbubbles have similar stability to microfluidically generated microbubbles that are not exposed to vacuum shrinkage. We anticipate that, with additional scale-up, this simple approach to shrink microbubbles generated microfluidically will be desirable in ultrasound imaging and therapeutic applications.

Twitter Demographics

The data shown below were collected from the profiles of 10 tweeters 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 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 22%
Student > Bachelor 6 12%
Student > Master 6 12%
Researcher 5 10%
Professor > Associate Professor 3 6%
Other 6 12%
Unknown 12 24%
Readers by discipline Count As %
Engineering 17 35%
Chemistry 5 10%
Chemical Engineering 3 6%
Materials Science 3 6%
Physics and Astronomy 3 6%
Other 5 10%
Unknown 13 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 13 August 2019.
All research outputs
#3,276,777
of 22,962,258 outputs
Outputs from Soft Matter
#425
of 8,140 outputs
Outputs of similar age
#69,014
of 421,050 outputs
Outputs of similar age from Soft Matter
#30
of 790 outputs
Altmetric has tracked 22,962,258 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,140 research outputs from this source. They receive a mean Attention Score of 3.4. 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 421,050 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 83% of its contemporaries.
We're also able to compare this research output to 790 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 96% of its contemporaries.