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X Demographics
Mendeley readers
Attention Score in Context
Title |
Carbon nanotube-based multi electrode arrays for neuronal interfacing: progress and prospects
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Published in |
Frontiers in Neural Circuits, January 2013
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DOI | 10.3389/fncir.2012.00122 |
Pubmed ID | |
Authors |
Lilach Bareket-Keren, Yael Hanein |
Abstract |
Carbon nanotube (CNT) coatings have been demonstrated over the past several years as a promising material for neuronal interfacing applications. In particular, in the realm of neuronal implants, CNTs have major advantages owing to their unique mechanical and electrical properties. Here we review recent investigations utilizing CNTs in neuro-interfacing applications. Cell adhesion, neuronal engineering and multi electrode recordings with CNTs are described. We also highlight prospective advances in this field, in particular, progress toward flexible, bio-compatible CNT-based technology. |
X Demographics
The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Mexico | 2 | 18% |
Spain | 1 | 9% |
Portugal | 1 | 9% |
Netherlands | 1 | 9% |
Unknown | 6 | 55% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 11 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 206 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Japan | 2 | <1% |
United States | 2 | <1% |
Netherlands | 1 | <1% |
Italy | 1 | <1% |
Switzerland | 1 | <1% |
United Kingdom | 1 | <1% |
Germany | 1 | <1% |
Czechia | 1 | <1% |
Poland | 1 | <1% |
Other | 0 | 0% |
Unknown | 195 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 56 | 27% |
Researcher | 42 | 20% |
Student > Master | 34 | 17% |
Student > Bachelor | 16 | 8% |
Student > Doctoral Student | 9 | 4% |
Other | 22 | 11% |
Unknown | 27 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 62 | 30% |
Agricultural and Biological Sciences | 25 | 12% |
Physics and Astronomy | 19 | 9% |
Materials Science | 18 | 9% |
Chemistry | 17 | 8% |
Other | 29 | 14% |
Unknown | 36 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 19 January 2023.
All research outputs
#2,231,177
of 25,197,939 outputs
Outputs from Frontiers in Neural Circuits
#95
of 1,297 outputs
Outputs of similar age
#21,258
of 294,042 outputs
Outputs of similar age from Frontiers in Neural Circuits
#10
of 170 outputs
Altmetric has tracked 25,197,939 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,297 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one has done particularly well, scoring higher than 92% 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 294,042 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 92% of its contemporaries.
We're also able to compare this research output to 170 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 94% of its contemporaries.