Structural Characteristics of Carbon Nanofibers for On-chip Interconnect Applications

In this letter, we compare the structures of plasma-enhanced chemical vapor deposition of Ni-catalyzed and Pd-catalyzed carbon nanofibers (CNFs) synthesized for on-chip interconnect applications with scanning transmission electron microscopy (STEM). The Ni-catalyzed CNF has a conventional fiberlike structure and many graphitic layers that are almost parallel to the substrate at the CNF base. In contrast, the Pd-catalyzed CNF has a multiwall nanotubelike structure on the sidewall spanning the entire CNF. The microstructure observed in the Pd-catalyzed fibers at the CNF-metal interface has the potential to lower contact resistance significantly, as our electrical measurements using current-sensing atomic force microscopy indicate. A structural model is presented based on STEM image analysis

Length dependence of current-induced breakdown in carbon nanofiber interconnects

Current-induced breakdown is investigated for carbon nanofibers (CNF) for potential interconnect applications. The measured maximum current density in the suspended CNF is inversely proportional to the nanofiber length and is independent of diameter. This relationship can be described with a heat transport model that takes into account Joule heating and heat diffusion along the CNF, assuming that breakdown occurs when and where the temperature reaches a threshold or critical value

Parameterized Compilation Lower Bounds for Restricted CNF-formulas

We show unconditional parameterized lower bounds in the area of knowledge compilation, more specifically on the size of circuits in decomposable negation normal form (DNNF) that encode CNF-formulas restricted by several graph width measures. In particular, we show that - there are CNF formulas of size $n$ and modular incidence treewidth $k$ whose smallest DNNF-encoding has size $n^{\Omega(k)}$, and - there are CNF formulas of size $n$ and incidence neighborhood diversity $k$ whose smallest DNNF-encoding has size $n^{\Omega(\sqrt{k})}$. These results complement recent upper bounds for compiling CNF into DNNF and strengthen---quantitatively and qualitatively---known conditional low\-er bounds for cliquewidth. Moreover, they show that, unlike for many graph problems, the parameters considered here behave significantly differently from treewidth