Quantum capacitance

About: Quantum capacitance is a research topic. Over the lifetime, 954 publications have been published within this topic receiving 24165 citations.

BSIM Compact Model of Quantum Confinement in Advanced Nanosheet FETs

Abstract: We propose a compact model for nanosheet FETs that take the effects of quantum confinement into account. The model captures the nanosheet width and thickness dependence of the electrostatic dimension, density of states, effective mass, subband energies, and threshold voltages and includes them in the charge calculation, resulting in an accurate terminal charge and current characteristics. The model has been implemented using Verilog-A in the BSIM-CMG framework for all simulations. It has been validated with band-structure calculation-based TCAD simulations as well as measured data. We have also highlighted the significance of quantum mechanical effects on analog and RF performance of the device.

Tailoring graphene-based electrodes from semiconducting to metallic to increase the energy density in supercapacitors.

Abstract: The semiconducting character of graphene and some carbon-based electrodes can lead to noticeably lower total capacitances and stored energy densities in electric double layer (EDL)capacitors. This paper discusses the chemical and electronic structure modifications that enhance the available energy bands, density of states and quantum capacitance of graphene substrates near the Fermi level, therefore restoring the conducting character of these materials. The doping of graphene with p or n dopants, such as boron and nitrogen atoms, or the introduction of vacancy defects that introduce zigzag edges, can significantly increase the quantum capacitance within the potential range of interest for the energy storage applications by either shifting the Dirac point away from the Fermi level or by eliminating the Dirac point. We show that a combination of doping and vacancies at realistic concentrations is sufficient to increase the capacitance of a graphene-based electrode to within 1 μF cm(−2) from that of a metallic surface.Using a combination of ab initio calculations and classical molecular dynamics simulations we estimate how the changes in the quantum capacitance of these electrode materials affect the total capacitance stored by the open structure EDL capacitors containing room temperature ionic liquid electrolytes.

Determination of Quantum Capacitance and Band Filling Potential in Graphene Transistors with Dual Electrochemical and Field-Effect Gates

Abstract: We report here an investigation of graphene field-effect transistors (G-FETs) in which the graphene channel is in contact with an electrolyte phase. The electrolyte and the ultrathin nature of graphene allow direct measurement of the channel electrochemical potential versus a reference electrode also in contact with the electrolyte. In addition, the electrolyte can be used to gate the graphene; i.e., a dual-gate structure is realized. We employ this electrolyte modified G-FET architecture to (1) track the Fermi level of the graphene channel as a function of gate bias, (2) determine the density of states (i.e., the quantum capacitance CQ) of graphene, and (3) separate the gate induced band filling potential δ from the electrochemical double-layer charging potential ΔϕEDL. Additionally, we are able to determine the electric double-layer capacitance CEDL for the graphene/electrolyte interface, which is ∼5 μF/cm2, the same order of magnitude as CQ. Overall, the electrolyte modified G-FETs provide an excellent...

Accurate Intrinsic Gate Capacitance Model for Carbon Nanotube-Array Based FETs Considering Screening Effect

Abstract: In this letter, an accurate semi-analytical model for the intrinsic gate capacitance of carbon nanotube (CN)-array based back-gated field-effect transistors (FETs) is proposed. The model accounts for electrostatic screening effect for any given number of nanotubes, their diameter, pitch, and gate-dielectric thickness. It is shown that screening effect varies significantly not only with the change in density but also with the number of nanotubes and must be considered while modeling the intrinsic gate capacitance of array-based CNFETs for both high-performance and thin-film transistor applications.