A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä

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




TekijätHediyeh Karimi, Rasoul Rahmani, Reza Mashayekhi, Leyla Ranjbari, Amir H. Shirdel, Niloofar Haghighian, Parisa Movahedi, Moein Hadiyan, Razali Ismail

KustantajaBEILSTEIN-INSTITUT

KustannuspaikkaFRANKFURT AM MAIN; TRAKEHNER STRASSE 7-9, FRANKFURT AM MAIN, 60487, GERMANY

Julkaisuvuosi2014

JournalBeilstein Journal of Nanotechnology

Tietokannassa oleva lehden nimiBeilstein Journal of Nanotechnology

Lehden akronyymiBeilstein J.Nanotechnol.

Vuosikerta5

Aloitussivu603

Lopetussivu609

Sivujen määrä7

ISSN2190-4286

DOIhttps://doi.org/10.3762/bjnano.5.71


Tiivistelmä

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.




Last updated on 2024-26-11 at 20:53