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Hydraulically amplified self-healing electrostatic actuators with muscle-like performance

Overview of attention for article published in Science, January 2018
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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 (99th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Citations

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277 Dimensions

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571 Mendeley
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Title
Hydraulically amplified self-healing electrostatic actuators with muscle-like performance
Published in
Science, January 2018
DOI 10.1126/science.aao6139
Pubmed ID
Authors

E. Acome, S. K. Mitchell, T. G. Morrissey, M. B. Emmett, C. Benjamin, M. King, M. Radakovitz, C. Keplinger

Abstract

Existing soft actuators have persistent challenges that restrain the potential of soft robotics, highlighting a need for soft transducers that are powerful, high-speed, efficient, and robust. We describe a class of soft actuators, termed hydraulically amplified self-healing electrostatic (HASEL) actuators, which harness a mechanism that couples electrostatic and hydraulic forces to achieve a variety of actuation modes. We introduce prototypical designs of HASEL actuators and demonstrate their robust, muscle-like performance as well as their ability to repeatedly self-heal after dielectric breakdown-all using widely available materials and common fabrication techniques. A soft gripper handling delicate objects and a self-sensing artificial muscle powering a robotic arm illustrate the wide potential of HASEL actuators for next-generation soft robotic devices.

Twitter Demographics

The data shown below were collected from the profiles of 28 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 571 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 571 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 154 27%
Student > Master 80 14%
Researcher 78 14%
Student > Bachelor 47 8%
Student > Doctoral Student 42 7%
Other 70 12%
Unknown 100 18%
Readers by discipline Count As %
Engineering 262 46%
Materials Science 64 11%
Chemistry 37 6%
Physics and Astronomy 14 2%
Chemical Engineering 13 2%
Other 53 9%
Unknown 128 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 375. 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 16 March 2021.
All research outputs
#46,722
of 17,947,665 outputs
Outputs from Science
#2,065
of 71,568 outputs
Outputs of similar age
#1,932
of 417,969 outputs
Outputs of similar age from Science
#93
of 991 outputs
Altmetric has tracked 17,947,665 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 71,568 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 56.2. 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 417,969 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 99% of its contemporaries.
We're also able to compare this research output to 991 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 90% of its contemporaries.