Study the Temperature Effects on Crosstalk in Graphene Nanoribbon Interconnects

Abstract

Scaling plays an important role in the performance of a chip. But the effect of the parameter scaling in VLSI field has not been investigated in detail. Many researchers showed that multilayer graphene nanoribbons (MLGNR) are the best promising candidates for next generation of VLSI interconnect. Multilayer graphene nanoribbons (MLGNR) are preferred over copper interconnects and carbon nanotubes due to easy patterning by high resolution lithography and lower interconnect line resistance due to multiple conduction paths. So, it’s the need of the hour to study the impact of parameter scaling in the MLGNR interconnects. In this dissertation, the complete analysis of the functional and dynamic crosstalk and the impact of parameter scaling on the crosstalk in temperature-dependent capacitive coupled MLGNR interconnects is presented at 14 nm technology node. A capacitively coupled MLGNR model is used to find temperature-dependent impedance parameters for the three scaling conditions and results are compared with existing temperature-independent MLGNR interconnect impedance parameters at same technology node. Further, the dynamic and functional crosstalk occurring in the temperature-dependent MLGNR interconnect under the three scaling conditions is studied and compared with copper. The effect of various parameters such as interconnect length on crosstalk noise in temperature dependent and temperature-independent MLGNR interconnects propagation has been analysed.