Large eddy simulations for fan-OGV broadband noise prediction

The work in this paper forms part of a project on the use of large eddy simulation (LES) for broadband rotor-stator interaction noise prediction. Here we focus on LES of the flow field near a fan blade trailing edge. The first part of the paper aims to evaluate LES suitability for predicting the near-field velocity field for a blunt NACA-0012 airfoil at moderate Reynolds numbers (2× 10 5 and 4× 10 5). Preliminary computations of turbulent mean and root-mean-square velocities, as well as energy spectra at the trailing edge, are compared with those from a recent experiment.1 The second part of the paper describes preliminary progress on an LES calculation of the fan wakes on a fan rig. 2 The CFD code uses a mixed element unstructured mesh with a median dual control volume. A wall-adapting local eddy-viscosity sub-grid scale model is employed. A very small amount of numerical dissipation is added in the numerical scheme to keep the compressible solver stable. Further results for the fan turbulentmean and RMS velocity, and especially the aeroacoustics field will be presented at a later stage. Copyright © 2008 by Qinling LI, Nigel Peake & Mark Savill.

Efficient field emission from triode-type 1D arrays of carbon nanotubes.

Carbon nanotube (CNT) emitters were formed on line-patterned cathodes in microtrenches through a thermal CVD process. Single-walled carbon nanotubes (SWCNTs) self-organized along the trench lines with a submicron inter-CNT spacing. Excellent field emission (FE) properties were obtained: current densities at the anode (J(a)) of 1 microA cm(-2), 10 mA cm(-2) and 100 mA cm(-2) were recorded at gate voltages (V(g)) of 16, 25 and 36 V, respectively. The required voltage difference to gain a 1:10 000 contrast of the anode current was as low as 9 V, indicating that a very low operating voltage is possible for these devices. Not only a large number of emission sites but also the optimal combination of trench structure and emitter morphology are crucial to achieve the full FE potential of thin CNTs with a practical lifetime. The FE properties of 1D arrays of CNT emitters and their optimal design are discussed. Self-organization of thin CNTs is an attractive prospect to tailor preferable emitter designs in FE devices.

Energy transfer and enhanced 1.54 μm emission in Erbium-Ytterbium disilicate thin films.

α-(Yb1-xErx)2Si2O7 thin films on Si substrates were synthesized by magnetron co-sputtering. The optical emission from Er3+ ions has been extensively investigated, evidencing the very efficient role of Yb-Er coupling. The energy-transfer coefficient was evaluated for an extended range of Er content (between 0.2 and 16.5 at.%) reaching a maximum value of 2 × 10⁻¹⁶ cm⁻³s⁻¹. The highest photoluminescence emission at 1535 nm is obtained as a result of the best compromise between the number of Yb donors (16.4 at.%) and Er acceptors (1.6 at.%), for which a high population of the first excited state is reached. These results are very promising for the realization of 1.54 μm optical amplifiers on a Si platform.

Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm.

We live in an era of abundant data. This has necessitated the development of new and innovative statistical algorithms to get the most from experimental data. For example, faster algorithms make practical the analysis of larger genomic data sets, allowing us to extend the utility of cutting-edge statistical methods. We present a randomised algorithm that accelerates the clustering of time series data using the Bayesian Hierarchical Clustering (BHC) statistical method. BHC is a general method for clustering any discretely sampled time series data. In this paper we focus on a particular application to microarray gene expression data. We define and analyse the randomised algorithm, before presenting results on both synthetic and real biological data sets. We show that the randomised algorithm leads to substantial gains in speed with minimal loss in clustering quality. The randomised time series BHC algorithm is available as part of the R package BHC, which is available for download from Bioconductor (version 2.10 and above) via http://bioconductor.org/packages/2.10/bioc/html/BHC.html. We have also made available a set of R scripts which can be used to reproduce the analyses carried out in this paper. These are available from the following URL. https://sites.google.com/site/randomisedbhc/.

Localized tail state distribution in amorphous oxide transistors deduced from low temperature measurements

In this paper, we extract density of localized tail states from measurements of low temperature conductance in amorphous oxide transistors. At low temperatures, trap-limited conduction prevails, allowing extraction of the trapped carrier distribution with energy. Using a test device with a-InGaZnO channel layer, the extracted tail state energy and density at the conduction band minima are 20 meV and 2 × 10 19 cm -3 eV -1, respectively, which are consistent with values reported in the literature. Also, the field-effect mobility as a function of temperature from 77 K to 300 K is retrieved for different gate voltages, yielding the activation energy and the percolation threshold. © 2012 American Institute of Physics.

Direct detection of molecular biorecognition by dipole sensing mechanism.

This work investigates the feasibility of transducing molecular-recognition events into a measurable potentiometric signal. It is shown for the first time that biorecognition of acetylcholine (ACh) can be translated to conformational changes in the enzyme, acetylcholine-esterase (AChE), which in turn induces a measurable change in surface potential. Our results show that a highly sensitive detector for ACh can be obtained by the dilute assembly of AChE on a floating gate derived field effect transistor (FG-FET). A wide concentration range response is observed for ACh (10(-2)-10(-9)M) and for the inhibitor carbamylcholine CCh (10(-6)-10(-11)M). These enhanced sensitivities are modeled theoretically and explained by the combined response of the device to local pH changes and molecular dipole variations due to the enzyme-substrate recognition event.