3 resultados para Single-electron devices
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
Resumo:
A model for computing the generation-recombination noise due to traps within the semiconductor film of fully depleted silicon-on-insulator MOSFET transistors is presented. Dependence of the corner frequency of the Lorentzian spectra on the gate voltage is addressed in this paper, which is different to the constant behavior expected for bulk transistors. The shift in the corner frequency makes the characterization process easier. It helps to identify the energy position, capture cross sections, and densities of the traps. This characterization task is carried out considering noise measurements of two different candidate structures for single-transistor dynamic random access memory devices.
Resumo:
This paper proposes a drain current model for triple-gate n-type junctionless nanowire transistors. The model is based on the solution of the Poisson equation. First, the 2-D Poisson equation is used to obtain the effective surface potential for long-channel devices, which is used to calculate the charge density along the channel and the drain current. The solution of the 3-D Laplace equation is added to the 2-D model in order to account for the short-channel effects. The proposed model is validated using 3-D TCAD simulations where the drain current and its derivatives, the potential, and the charge density have been compared, showing a good agreement for all parameters. Experimental data of short- channel devices down to 30 nm at different temperatures have been also used to validate the model.
Resumo:
One-transistor floating-body random access memory retention time distribution is investigated on silicon-on-insulator UTBOX devices. It is shown that the average retention time can be improved by two to three orders of magnitude by reducing the body-junction electric field. However, the retention time distribution, which is mainly caused by the generation-recombination center density variation, remains similar.