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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 (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

twitter
12 tweeters
patent
1 patent

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
46 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 12 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 22%
Student > Bachelor 7 15%
Student > Master 6 13%
Researcher 5 11%
Professor > Associate Professor 3 7%
Other 5 11%
Unknown 10 22%
Readers by discipline Count As %
Engineering 18 39%
Chemistry 5 11%
Chemical Engineering 3 7%
Materials Science 3 7%
Physics and Astronomy 3 7%
Other 3 7%
Unknown 11 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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
#1,778,831
of 15,641,077 outputs
Outputs from Soft Matter
#169
of 6,301 outputs
Outputs of similar age
#45,716
of 267,098 outputs
Outputs of similar age from Soft Matter
#5
of 156 outputs
Altmetric has tracked 15,641,077 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,301 research outputs from this source. They receive a mean Attention Score of 2.4. This one has done particularly well, scoring higher than 97% 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 267,098 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 82% of its contemporaries.
We're also able to compare this research output to 156 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.