Low-temperature growth of carbon nanotubes by plasma-enhanced chemical vapor deposition

Vertically aligned carbon nanotubes were grown at temperatures as low as 120degreesC by plasma-enhanced chemical vapor deposition. A systematic study of the temperature dependence of the growth rate and the structure of the as-grown nanotubes is presented using a C2H2/NH3 system and nickel as the catalyst. The activation energy for the growth rate was found to be 0.23 eV, much less than for thermal chemical vapor deposition (1.2-1.5 eV). This suggests growth occurs by surface diffusion of carbon on nickel. The result could allow direct growth of nanotubes onto low-temperature substrates like plastics, and facilitate the integration in sensitive nanoelectronic devices. (C) 2003 American Institute of Physics.

The role of the catalytic particle in the growth of carbon nanotubes by plasma enhanced chemical vapor deposition

Vertically aligned carbon nanotubes were synthesized by plasma enhanced chemical vapor deposition using nickel as a metal catalyst. High resolution transmission electron microscopy analysis of the particle found at the tip of the tubes reveals the presence of a metastable carbide Ni3C. Since the carbide is found to decompose upon annealing at 600 degreesC, we suggest that Ni3C is formed after the growth is stopped due to the rapid cooling of the Ni-C interstitial solid solution. A detailed description of the tip growth mechanism is given, that accounts for the composite structure of the tube walls. The shape and size of the catalytic particle determine the concentration gradient that drives the diffusion of C atoms across and though the metal. (C) 2004 American Institute of Physics.

Elliptical slice sampling

Many probabilistic models introduce strong dependencies between variables using a latent multivariate Gaussian distribution or a Gaussian process. We present a new Markov chain Monte Carlo algorithm for performing inference in models with multivariate Gaussian priors. Its key properties are: 1) it has simple, generic code applicable to many models, 2) it has no free parameters, 3) it works well for a variety of Gaussian process based models. These properties make our method ideal for use while model building, removing the need to spend time deriving and tuning updates for more complex algorithms.

A comparative study of plasma-enhanced chemical vapor gate dielectrics for solution-processed polymer thin-film transistor circuit integration

This paper considers plasma-enhanced chemical vapor deposited (PECVD) silicon nitride (SiNx) and silicon oxide (SiOx) as gate dielectrics for organic thin-film transistors (OTFTs), with solution-processed poly[5, 5′ -bis(3-dodecyl-2-thienyl)-2, 2′ -bithiophene] (PQT-12) as the active semiconductor layer. We examine transistors with SiNx films of varying composition deposited at 300 °C as well as 150 °C for plastic compatibility. The transistors show over 100% (two times) improvement in field-effect mobility as the silicon content in SiNx increases, with mobility (μFE) up to 0.14 cm2 /V s and on/off current ratio (ION / IOFF) of 108. With PECVD SiOx gate dielectric, preliminary devices exhibit a μFE of 0.4 cm2 /V s and ION / IOFF of 108. PQT-12 OTFTs with PECVD SiNx and SiOx gate dielectrics on flexible plastic substrates are also presented. These results demonstrate the viability of using PECVD SiN x and SiOx as gate dielectrics for OTFT circuit integration, where the low temperature and large area deposition capabilities of PECVD films are highly amenable to integration of OTFT circuits targeted for flexible and lightweight applications. © 2008 American Institute of Physics.

Enhanced 10-Gbit/s link performance for directly Modulated complex-coupled DFB lasers via resonance frequency, damping rate, and chirp

This paper demonstrates the respective roles that combined index- and gain-coupling play in the overall link performance of distributed feedback (DFB) lasers. Their impacts on both static and dynamic properties such as slope efficiency, resonance frequency, damping rate, and chirp are investigated. Simulation results are compared with experimental data with good agreement. Transmission-oriented optimization is then demonstrated based on a targeted specification. The design tradeoffs are revealed, and it is shown that a modest combination of index- and gain-coupling enables optimum transmission at 10 Gbit/s.

Enhanced virulence of Salmonella enterica serovar typhimurium after passage through mice.

The interaction between Salmonella enterica and the host immune system is complex. The outcome of an infection is the result of a balance between the in vivo environment where the bacteria survive and grow and the regulation of fitness genes at a level sufficient for the bacteria to retain their characteristic rate of growth in a given host. Using bacteriological counts from tissue homogenates and fluorescence microscopy to determine the spread, localization, and distribution of S. enterica in the tissues, we show that, during a systemic infection, S. enterica adapts to the in vivo environment. The adaptation becomes a measurable phenotype when bacteria that have resided in a donor animal are introduced into a recipient naïve animal. This adaptation does not confer increased resistance to early host killing mechanisms but can be detected as an enhancement in the bacterial net growth rate later in the infection. The enhanced growth rate is lost upon a single passage in vitro, and it is therefore transient and not due to selection of mutants. The adapted bacteria on average reach higher intracellular numbers in individual infected cells and therefore have patterns of organ spread different from those of nonadapted bacteria. These experiments help in developing an understanding of the influence of passage in a host on the fitness and virulence of S. enterica.

Latin hypercube sampling used in the calculation of the fracture probability

The paper proposes Latin hypercube sampling combined with the stratified sampling of variance reduction technique to calculate accurate fracture probability. In the compound sampling, the number of simulations is relatively small and the calculation error is satisfactory.

Fixed-lag blind equalization and sequence estimation in digital communications systems using sequential importance sampling

We present methods for fixed-lag smoothing using Sequential Importance sampling (SIS) on a discrete non-linear, non-Gaussian state space system with unknown parameters. Our particular application is in the field of digital communication systems. Each input data point is taken from a finite set of symbols. We represent transmission media as a fixed filter with a finite impulse response (FIR), hence a discrete state-space system is formed. Conventional Markov chain Monte Carlo (MCMC) techniques such as the Gibbs sampler are unsuitable for this task because they can only perform processing on a batch of data. Data arrives sequentially, so it would seem sensible to process it in this way. In addition, many communication systems are interactive, so there is a maximum level of latency that can be tolerated before a symbol is decoded. We will demonstrate this method by simulation and compare its performance to existing techniques.