Statistical estimation of electrostatic and transport contributions to device parameter variation

An efficient method to model accurately the statistical drain current variability in nano-scale MOSFETs is presented. Two linear regression models are proposed for the estimation of the percentage drain current variation obtained by Monte Carlo (MC) from analogous Drift Diffusion (DD) simulation. The total variation observed in MC may be attributed to in part electrostatic variation and in part transport variation. The combined effects of the electrostatic and transport variations are estimated by an absolute and conditional model, assuming that DD simulation accounts for the entire electrostatic variation and that this is identically recovered within MC. The analysis is applied to atomistic substrate dopant induced current variation over a range of scaled nMOS devices.