Magnetothermal Conductivity of Highly Oriented Pyrolytic Graphite in the Quantum Limit

We report on the magnetic field (0T$\le B \le 9$T) dependence of the longitudinal thermal conductivity $\kappa(T,B)$ of highly oriented pyrolytic graphite in the temperature range 5 K $\le T\le$ 20 K for fields parallel to the $c-$axis. We show that $\kappa(T,B)$ shows large oscillations in the high-field region (B > 2 T) where clear signs of the Quantum-Hall effect are observed in the Hall resistance. With the measured longitudinal electrical resistivity we show that the Wiedemann-Franz law is violated in the high-field regime.Comment: 4 Figures, to be published in Physical Review B (2003

Uptake of gases in bundles of carbon nanotubes

Model calculations are presented which predict whether or not an arbitrary gas experiences significant absorption within carbon nanotubes and/or bundles of nanotubes. The potentials used in these calculations assume a conventional form, based on a sum of two-body interactions with individual carbon atoms; the latter employ energy and distance parameters which are derived from empirical combining rules. The results confirm intuitive expectation that small atoms and molecules are absorbed within both the interstitial channels and the tubes, while large atoms and molecules are absorbed almost exclusively within the tubes.Comment: 9 pages, 12 figures, submitted to PRB Newer version (8MAR2K). There was an error in the old one (23JAN2K). Please download thi

The Electrical Noise of Carbon Fibers

The low-frequency excess electrical noise has been measured on carbon fibers with a wide range of crystalline perfection and corresponding electrical and mechanical properties. Fibers include those prepared from ex-PAN and ex-pitch polymers, and a catalytic-chemical vapor deposited filament. The extensional (Young\u27s) moduli of these fibers varied from about 220 to 890 GPa (35–130 Msi), while the electrical resistivities varied from about 19 to 1 µΩ m. The low-frequency electrical noise of each fiber was found to be proportional to l2 and to vary as 1/fα, where f is the frequency and α is about 1.15. The most striking feature of the results was the strong dependence of the normalized noise power on the degree of crystalline perfection. Journal of Applied Physics is copyrighted by The American Institute of Physics

Stretching Bayesian learning in the relevance feedback of image retrieval

Abstract. This paper is about the work on user relevance feedback in image retrieval. We take this problem as a standard two-class pattern classification problem aiming at refining the retrieval precision by learning through the user relevance feedback data. However, we have investigated the problem by noting two important unique characteristics of the problem: small sample collection and asymmetric sample distributions between positive and negative samples. We have developed a novel approach to stretching Bayesian learning to solve for this problem by explicitly exploiting the two unique characteristics, which is the methodology of BAyesian Learning in Asymmetric and Small sample collections, thus called BALAS. Different learning strategies are used for positive and negative sample collections in BALAS, respectively, based on the two unique characteristics. By defining the relevancy confidence as the relevant posterior probability, we have developed an integrated ranking scheme in BALAS which complementarily combines the subjective relevancy confidence and the objective feature-based distance measure to capture the overall retrieval semantics. The experimental evaluations have confirmed the rationale of the proposed ranking scheme, and have also demonstrated that BALAS is superior to an existing relevance feedback method in the current literature in capturing the overall retrieval semantics.