Improving Convergence and Simulation Time of Quantum Hydrodynamic Simulation: Application to Extraction of Best 10-nm FinFET Parameter Values

Abstract

As electronic devices enter the deep nanometer regime, accurate and efficient device simulations become necessary to account for the emerging quantum effects. The traditional drift-diffusion and hydrodynamic (HD) device simulation models are not accurate in this regime. It is important to use the quantum HD (QHD) simulation model. However, this model suffers from poor convergence and high CPU times. To overcome these obstacles, in this paper, we propose a novel method to replace part of the QHD simulation that exhibits poor convergence behavior and high CPU time with HD simulation. In order to implement this, we capture the device states from the classical HD model and then apply the results as the initial guess to the QHD simulation, which is then solved by the Newton-Raphson method. This leads to significant improvements. The nonconvergence rate and the simulation time are reduced by 86.0% and 30.2%, respectively. As an application of the proposed methodology, we extract the best parameter values of both bulk and silicon-on-insulator FinFETs at the 10-nm technology node from their vast device design space.