PMID- 24991496
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20140703
LR  - 20211021
IS  - 2190-4286 (Print)
IS  - 2190-4286 (Electronic)
IS  - 2190-4286 (Linking)
VI  - 5
DP  - 2014
TI  - Analytical development and optimization of a graphene-solution interface 
      capacitance model.
PG  - 603-9
LID - 10.3762/bjnano.5.71 [doi]
AB  - Graphene, which as a new carbon material shows great potential for a range of 
      applications because of its exceptional electronic and mechanical properties, 
      becomes a matter of attention in these years. The use of graphene in nanoscale 
      devices plays an important role in achieving more accurate and faster devices. 
      Although there are lots of experimental studies in this area, there is a lack of 
      analytical models. Quantum capacitance as one of the important properties of 
      field effect transistors (FETs) is in our focus. The quantum capacitance of 
      electrolyte-gated transistors (EGFETs) along with a relevant equivalent circuit 
      is suggested in terms of Fermi velocity, carrier density, and fundamental 
      physical quantities. The analytical model is compared with the experimental data 
      and the mean absolute percentage error (MAPE) is calculated to be 11.82. In order 
      to decrease the error, a new function of E composed of alpha and beta parameters is 
      suggested. In another attempt, the ant colony optimization (ACO) algorithm is 
      implemented for optimization and development of an analytical model to obtain a 
      more accurate capacitance model. To further confirm this viewpoint, based on the 
      given results, the accuracy of the optimized model is more than 97% which is in 
      an acceptable range of accuracy.
FAU - Karimi, Hediyeh
AU  - Karimi H
AD  - Centre for Artificial Intelligence and Robotics, Universiti Teknologi Malaysia, 
      54100 Kuala Lumpur, Malaysia ; Malaysia Japan International Ins. Of Technology, 
      Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia.
FAU - Rahmani, Rasoul
AU  - Rahmani R
AD  - Centre for Artificial Intelligence and Robotics, Universiti Teknologi Malaysia, 
      54100 Kuala Lumpur, Malaysia.
FAU - Mashayekhi, Reza
AU  - Mashayekhi R
AD  - Faculty of Electrical Engineering, khayyam higher education Institute, 
      9189747178, Mashhad, Iran.
FAU - Ranjbari, Leyla
AU  - Ranjbari L
AD  - Department of Mathematical Science, Faculty of Science, Universiti Teknologi 
      Malaysia, 81310 UTM, Johor Bahru, Malaysia.
FAU - Shirdel, Amir H
AU  - Shirdel AH
AD  - Department of Chemical Engineering, Abo Akademi University, 20500 Abo, Finland.
FAU - Haghighian, Niloofar
AU  - Haghighian N
AD  - Department of physics and CNISM, University of Genova, Via Dodecaneso 33, 16146 
      Genova, Italy.
FAU - Movahedi, Parisa
AU  - Movahedi P
AD  - Department of Information Technology, University of Turku , 20014 Turku, Finland.
FAU - Hadiyan, Moein
AU  - Hadiyan M
AD  - Department of Electrical and computer engineering, K. N. Toosi University of 
      Technology, Tehran, Iran.
FAU - Ismail, Razali
AU  - Ismail R
AD  - Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310, UTM 
      Johor Bahru, Johor, Malaysia.
LA  - eng
PT  - Journal Article
DEP - 20140509
PL  - Germany
TA  - Beilstein J Nanotechnol
JT  - Beilstein journal of nanotechnology
JID - 101551563
PMC - PMC4077292
OTO - NOTNLM
OT  - analytical modeling
OT  - ant colony optimization (ACO)
OT  - electrolyte-gated transistors (EGFET)
OT  - graphene
OT  - quantum capacitance
EDAT- 2014/07/06 06:00
MHDA- 2014/07/06 06:01
PMCR- 2014/05/09
CRDT- 2014/07/04 06:00
PHST- 2014/01/10 00:00 [received]
PHST- 2014/04/08 00:00 [accepted]
PHST- 2014/07/04 06:00 [entrez]
PHST- 2014/07/06 06:00 [pubmed]
PHST- 2014/07/06 06:01 [medline]
PHST- 2014/05/09 00:00 [pmc-release]
AID - 10.3762/bjnano.5.71 [doi]
PST - epublish
SO  - Beilstein J Nanotechnol. 2014 May 9;5:603-9. doi: 10.3762/bjnano.5.71. 
      eCollection 2014.