Simulation of Graphene Field-Effect Transistors and Resonant Tunneling Diodes Based on Carbon Nanomaterials

The development of field-effect transistors (GFETs), resonant-tunneling diodes (RTDs) and other device structures on the basis of graphene is one of the important tasks for producing a new element base for micro-and nanoelectronics. The report presents the simulation results of the GFET based on monolayer graphene in various operating modes, as well as the RTD based on bilayer graphene and carbon nanotubes. The main model of GFET [1, 2] was developed on the basis of the quantum drift-diffusion model. It is a combination of electrical and physical models. According to the model the electrostatic potential of the channel is calculated selfconsistently. The report describes the modification of the model for the case of GFET transfer characteristics calculation. The optimization method of dichotomy is used for this purpose. A satisfactory agreement with the experimental data not only of the output, but also of the transfer characteristics of a single- and dual-gate GFET was obtained with the use of the modified model. In the report, the influence of various factors on the characteristics of the investigated GFET was analyzed with the use of the model. The wave function formalism was applied in the development of numerical models of resonant-tunneling device structures based on carbon nanomaterials. It was also taken into account that RTD includes not only nanostructures (active regions) but also extended (passive) regions. Combined self-consistent models of RTD based on graphene and carbon nanotubes [3,4] were developed in accordance with quantum-mechanical and semiclassical approaches. The influence of various factors (height and shape of potential barriers, contact areas extension) on the characteristics of the RTD based on bilayer graphene was investigated with the use of the developed models. The programs realizing the models of GFET and graphene-based RTD were included in the nanoelectronic devices simulation system developed at the BSUIR since 1995 [5,6].