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Attention Score in Context
| Title |
Study of parasitic resistance effects in nanowire and nanoribbon biosensors
|
|---|---|
| Published in |
Discover Nano, February 2015
|
| DOI | 10.1186/s11671-015-0794-6 |
| Pubmed ID | |
| Authors |
Ioannis Zeimpekis, Kai Sun, Chunxiao Hu, Owain Thomas, Maurits RR de Planque, Harold MH Chong, Hywel Morgan, Peter Ashburn |
| Abstract |
In this work, we investigate sensor design approaches for eliminating the effects of parasitic resistance in nanowire and nanoribbon biosensors. Measurements of pH with polysilicon nanoribbon biosensors are used to demonstrate a reduction in sensitivity as the sensor length is reduced. The sensitivity (normalised conductance change) is reduced from 11% to 5.5% for a pH change from 9 to 3 as the sensing window length is reduced from 51 to 11 μm. These results are interpreted using a simple empirical model, which is also used to demonstrate how the sensitivity degradation can be alleviated by a suitable choice of sensor window length. Furthermore, a differential sensor design is proposed that eliminates the detrimental effects of parasitic resistance. Measurements on the differential sensor give a sensitivity of 15%, which is in good agreement with the predicted maximum sensitivity obtained from modeling. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 7% |
| Unknown | 13 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 29% |
| Professor | 2 | 14% |
| Researcher | 2 | 14% |
| Lecturer | 1 | 7% |
| Professor > Associate Professor | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 4 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 5 | 36% |
| Physics and Astronomy | 1 | 7% |
| Environmental Science | 1 | 7% |
| Materials Science | 1 | 7% |
| Chemistry | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 5 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 09 April 2015.
All research outputs
#22,758,309
of 25,373,627 outputs
Outputs from Discover Nano
#798
of 1,146 outputs
Outputs of similar age
#230,982
of 269,372 outputs
Outputs of similar age from Discover Nano
#17
of 20 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,146 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.