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

H Karimi, R Rahmani, R Mashayekhi, L Ranjbari, Amirhossein Shirdel, N Haghighian, P Movahedi, M Hadiyan, R Ismail

    Research output: Contribution to journalArticleScientificpeer-review

    9 Citations (Scopus)

    Abstract

    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.
    Original languageUndefined/Unknown
    Pages (from-to)603–609
    Number of pages7
    JournalBeilstein Journal of Nanotechnology
    Volume5
    DOIs
    Publication statusPublished - 2014
    MoE publication typeA1 Journal article-refereed

    Keywords

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

    Cite this