Edge-Roughness Aware EM-RA Model for Signal Integrity Analysis in MLGNR Interconnects

Abstract

This article presents a fast and accurate edge-roughness aware exponential matrix-rational approximation (EM-RA) model to capture the signal integrity effects, namely, crosstalk noise and the propagation delay, in coupled-multilayer graphene nanoribbon (MLGNR) interconnects. The proposed model provides a speed-up factor of 75 for coupled-two MLGNR line and a speed-up factor of 51 for coupled-three MLGNR line in comparison with the industry-level simulation program with integrated circuit emphasis (SPICE) simulator. The proposed model results always lie within a 1% error band compared with the HSPICE simulations, thereby ensuring the proposed model’s excellent accuracy. The robustness of the proposed edge-roughness aware EM-RA is confirmed by its application to a range of test cases in coupled-three MLGNR interconnects network. It is observed that the edge-roughness variations modeling plays a critical role in narrow (≤ 45 nm) MLGNRs. To ensure the signal integrity further, the eye-diagram analysis for the worst case scenario considering fully rough-edged MLGNR lines is carried out that provides the eye-height of 864.53 mV and the eye-width of 220.17 ps. The results obtained using the proposed closed-form parameterized EM-RA model ensures its immense possibility of incorporation in VLSI design automation tools for efficient capturing of the signal integrity effects in MLGNR interconnect networks.