English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Optimal repeater designs are performed for Cu and carbon nanotube (CNT)-based nanointerconnects to reduce the delay and power dissipation. The effects of inductance and metal-CNT contact resistance are treated appropriately. In this paper, the circuit parameters are calculated analytically, while they can be extracted experimentally for a specific foundry at a specific technology node. The particle swarm optimization (PSO) technique is employed to numerically calculate the optimal repeater size and the optimal number of repeaters in the Cu and CNT-based nanointerconnects. The results are verified against the analytical and genetic algorithm results. To facilitate CAD design, the machine-learning neural network (NN) is adopted. The data obtained using the PSO algorithm are used to train the NN and the feasibility of the NN is investigated and validated.

Repeater Insertion to Reduce Delay and Power in Copper and Carbon Nanotube-Based Nanointerconnects