Quantum capacitance

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

Quantum Capacitance Modifies Interionic Interactions in Semiconducting Nanopores

Abstract: Nanopores made with low dimensional semiconducting materials, such as carbon nanotubes and graphene slit pores, are used in supercapacitors. In theories and simulations of their operation, it is often assumed that such pores screen ion-ion interactions like metallic pores, i.e. that screening leads to an exponential decay of the interaction potential with ion separation. By introducing a quantum capacitance that accounts for the density of states in the material, we show that ion-ion interactions in carbon nanotubes and graphene slit pores actually decay algebraically with ion separation. This result suggests a new avenue of capacitance optimization based on tuning the electronic structure of a pore: a marked enhancement in capacitance might be achieved by developing nanopores made with metallic materials or bulk semimetallic materials.

Model Estimates of the Quantum Capacitance of Graphene Nanostructures

Abstract: Quantum capacitance CQ of an infinite graphene sheet, a graphene nanoribbon, and a chain of carbon atoms (carbyne) have been analytically estimated within the framework of simple models. A nonmonotonic dependence of CQ on the electrostatic potential is demonstrated. The data obtained are compared with the calculation results of other researchers.

Piecewise nonlinearity and capacitance in the joint density functional theory of extended interfaces

Abstract: The ab initio simulation of charged interfaces in the framework of density functional theory (DFT) is heavily employed for the study of electrochemical energy conversion processes. The capacitance is the primary descriptor for the response of the electrochemical interface. It is essentially equal to the inverse of the energy curvature as a function of electron number, and as such there appears a conflict with the fundamental principle of piecewise linearity in DFT that requires the energy curvature to be zero at fractional electron numbers, i.e., almost everywhere. To resolve this conflict, we derive an exact expression between the energy curvature and the Kohn-Sham density of states, the local density of states, and the Fukui potential. We find that the piecewise linearity requirement does not hold for the volume- or area-specific energy of extended systems and surfaces. Applied to the joint density functional theory of an electrode-electrolyte interface, including the ionic and dielectric response of the electrolyte, the same expression represents a rigorous basis for the partitioning of the total interfacial capacitance into contributions of the quantum capacitance, space-charge capacitance, and electrochemical double-layer capacitance. It provides insight into the influence of the electrode material, thickness, and temperature on the charging characteristics, as demonstrated by results for a bulk gold electrode, a single-layer gold electrode, and a single-layer graphene electrode.

Shunt quantum capacitance induced source switching in an electron Y-branch switch

Abstract: Switching between two electron sources can be realized classically by two complementary operating gates. We have studied the switching between two branches serving as electron sources in a Y-branched nanojunction controlled by one gate. By sweeping the voltage at the in-plane gate we observed switching between the electron sources. The source switching deviates from the classical source and drain switching and is related to a shunt quantum capacitance.

Predictive modeling of capacitance and resistance in gate-all-around cylindrical nanowire MOSFETs for parasitic design optimization

Abstract: This paper presents a predictive electrostatic capacitance and resistance compact model of multiple gate MOSFET with cylindrical conducting channels, taking into account parasitic effects, quantum confinement and quasi-ballistic effects. The model incorporates the dependence of channel length, gate height and width, gate-to-contact spacing, nanowire size, multiple channels, as well as 1-D ultra-narrow source/drain extension (SDE) doping profile. The proposed non-iterative electrostatic model is successfully verified, and can be used to predict nanowire-based circuit performance. Based on the analytical model, we can further examine which parasitic components are affecting the delay. Results revealed that C side , C of , R sd , R Q are dominant factors and should be treated as a major design concern. Among all the parameters, L sd , T g and N dop are essentially important in parasitic design optimization. By selectively modifying these parameters, parasitic effect is evidently reduced.