Effect of graphitization on the wettability and electrical conductivity of CVD-carbon nanotubes and films.

The use of carbon nanomaterials in various applications requires precise control of their surface and bulk properties. In this paper, we present a strategy for modifying the surface chemistry, wettability, and electrical conductivity of carbon tubes and films through annealing in a vacuum. Experiments were conducted with 60-300 nm nanotubes (nanopipes), produced by noncatalytic chemical vapor deposition (CVD) in a porous alumina template, and with thin films deposited by the same technique on a glassy carbon substrate having the same structure and chemistry of the CNTs. The surface of the as-produced CVD-carbon, treated with sodium hydroxide to remove the alumina template, is hydrophilic, and the bulk electrical conductivity is lower by a factor of 20 than that of fully graphitic multiwalled nanotubes (MWNT) or bulk graphite. The bulk electrical conductivity increases to the conductivity of graphite after annealing at 2000 degrees C in a high vacuum. The analysis of CNTs by transmission electron microscopy (TEM) and Raman spectroscopy shows the ordering of carbon accompanied by an exponential increase of the in-plane crystallite size, L(a), with increasing annealing temperature. Environmental scanning electron microscopy (ESEM) was used to study the interaction of CNT with water, and contact angle measurements performed using the sessile drop method on CVD-carbon films demonstrate that the contact angle increases nearly linearly with increasing annealing temperature.

Systems-level questions in Drosophila oogenesis.

This paper describes computational and experimental work on pattern formation in Drosophila egg development (oogenesis), an established experimental model for studying cell fate diversification in developing tissues. Epidermal growth factor receptor (EGFR) is a key regulator of pattern formation and morphogenesis in Drosophila oogenesis. EGFR signalling in oogenesis can be genetically manipulated and monitored at many levels, leading to large sets of heterogeneous data that enable the formulation of increasingly quantitative models of pattern formation in these systems.