Carbon Nanotube Interconnects: Process Variation via Polynomial Chaos

Igor Simone Stievano · Paolo Manfredi · Flavio Canavero

40 citations0/0 files storedIEEE Transactions on Electromagnetic Compatibility

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Probabilistic and Robust Engineering Design Low-power high-performance VLSI design Copper Interconnects and Reliability

Abstract

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.

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References

2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations 2007A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data 2011Parameters Variability Effects on Multiconductor Interconnects via Hermite Polynomial Chaos 2008Stochastic formulation of SPICE-type electronic circuit simulation with polynomial chaos

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