Analytical development and optimization of a graphene–solution interface capacitance model

Hediyeh Karimi, Rasoul Rahmani, Reza Mashayekhi, Leyla Ranjbari, Amir H. Shirdel, Niloofar Haghighian, Parisai Movahed, Moein Hadiyan, Razali Ismail

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


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 α and β 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.
Original languageEnglish
Pages (from-to)603-609
Number of pages7
JournalBeilstein Journal of Nanotechnology
Publication statusPublished - 9 May 2014


  • analytical modeling
  • ant colony optimization (ACO)
  • electrolyte-gated transistors (EGFET)
  • graphene
  • quantum capacitance


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