Reduced dimensional polynomial chaos approach for efficient uncertainty analysis of multi-walled carbon nanotube interconnects

In this paper, a novel polynomial chaos approach for the fast uncertainty analysis of multi-walled carbon nanotube interconnect networks is proposed. The key feature of this approach is the development of a decoupled sensitivity analysis methodology to intelligently identify and prune the least impactful random dimensions from the original random space. This dimension reduction strategy allows the reliable modeling of the full-dimensional uncertainty in interconnect networks at the cost of evaluating only a fraction of the full-blown PC coefficients. The validity of the proposed methodology is demonstrated using a numerical example.