Carbon Nanotube Interconnects: Process Variation via Polynomial Chaos

This paper addresses the generation of an enhanced stochastic model of a carbon nanotube interconnect including the effects of process variation. The proposed approach is based on the expansion of the constitutive relations of state-of-the-art deterministic models of nanointerconnects with uncertain parameters in terms of orthogonal polynomials. The method offers comparable accuracy and improved efficiency with respect to conventional methods like Monte Carlo in predicting the statistical behavior of the electrical performance of next-generation data links. An application example involving both the frequency- and time-domain analysis of a realistic nanointerconnect concludes this paper.