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Mendeley readers
Attention Score in Context
| Title |
Analytical modelling of monolayer graphene-based ion-sensitive FET to pH changes
|
|---|---|
| Published in |
Discover Nano, April 2013
|
| DOI | 10.1186/1556-276x-8-173 |
| Pubmed ID | |
| Authors |
Mohammad Javad Kiani, Mohammad Taghi Ahmadi, Hediyeh Karimi Feiz Abadi, Meisam Rahmani, Amin Hashim, Fauzan Khairi Che harun |
| Abstract |
Graphene has attracted great interest because of unique properties such as high sensitivity, high mobility, and biocompatibility. It is also known as a superior candidate for pH sensing. Graphene-based ion-sensitive field-effect transistor (ISFET) is currently getting much attention as a novel material with organic nature and ionic liquid gate that is intrinsically sensitive to pH changes. pH is an important factor in enzyme stabilities which can affect the enzymatic reaction and broaden the number of enzyme applications. More accurate and consistent results of enzymes must be optimized to realize their full potential as catalysts accordingly. In this paper, a monolayer graphene-based ISFET pH sensor is studied by simulating its electrical measurement of buffer solutions for different pH values. Electrical detection model of each pH value is suggested by conductance modelling of monolayer graphene. Hydrogen ion (H+) concentration as a function of carrier concentration is proposed, and the control parameter (Ƥ) is defined based on the electro-active ions absorbed by the surface of the graphene with different pH values. Finally, the proposed new analytical model is compared with experimental data and shows good overall agreement. |
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 | 18 | 39% |
| Researcher | 10 | 22% |
| Student > Master | 5 | 11% |
| Student > Bachelor | 5 | 11% |
| Other | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 4 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 21 | 46% |
| Materials Science | 7 | 15% |
| Chemistry | 6 | 13% |
| Physics and Astronomy | 3 | 7% |
| Agricultural and Biological Sciences | 2 | 4% |
| Other | 2 | 4% |
| Unknown | 5 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 29 August 2018.
All research outputs
#8,261,756
of 25,371,288 outputs
Outputs from Discover Nano
#209
of 1,146 outputs
Outputs of similar age
#64,100
of 194,546 outputs
Outputs of similar age from Discover Nano
#6
of 67 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 1,146 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done well, scoring higher than 80% 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 194,546 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 67 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.