Vertical leakage mechanism in GaN on Si high electron mobility transistor buffer layers

Control of leakage currents in the buffer layers of GaN based transistors on Si substrates is vital for the demonstration of high performance devices. Here, we show that the growth conditions during the metal organic chemical vapour deposition growth of the graded AlGaN strain relief layers (SRLs) can significantly influence the vertical leakage. Using scanning capacitance microscopy, secondary ion mass spectrometry, and transmission electron microscopy, we investigate the origins of leakage paths and show that they result from the preferential incorporation of oxygen impurities on the side wall facets of the inverted hexagonal pyramidal pits which can occur during the growth of the graded AlGaN SRL. We also show that when 2D growth of the AlGaN SRL is maintained a significant increase in the breakdown voltage can be achieved even in much thinner buffer layer structures. These results demonstrate the importance of controlling the morphology of the high electron mobility transistor buffer layer as even at a very low density the leakage paths identified would provide leakage paths in large area devices.This work was funded by the Engineering and Physical Sciences Research Council under Grant Code Nos. EP/K014471/1 and EP/N01202X/1 and the European Research Council under the European Community's Seventh Framework Programme Grant Agreement No. 279361 (MACONS)

Liquid-infiltrated photonic crystals - enhanced light-matter interactions for lab-on-a-chip applications

Optical techniques are finding widespread use in analytical chemistry for chemical and bio-chemical analysis. During the past decade, there has been an increasing emphasis on miniaturization of chemical analysis systems and naturally this has stimulated a large effort in integrating microfluidics and optics in lab-on-a-chip microsystems. This development is partly defining the emerging field of optofluidics. Scaling analysis and experiments have demonstrated the advantage of micro-scale devices over their macroscopic counterparts for a number of chemical applications. However, from an optical point of view, miniaturized devices suffer dramatically from the reduced optical path compared to macroscale experiments, e.g. in a cuvette. Obviously, the reduced optical path complicates the application of optical techniques in lab-on-a-chip systems. In this paper we theoretically discuss how a strongly dispersive photonic crystal environment may be used to enhance the light-matter interactions, thus potentially compensating for the reduced optical path in lab-on-a-chip systems. Combining electromagnetic perturbation theory with full-wave electromagnetic simulations we address the prospects for achieving slow-light enhancement of Beer-Lambert-Bouguer absorption, photonic band-gap based refractometry, and high-Q cavity sensing.Comment: Invited paper accepted for the "Optofluidics" special issue to appear in Microfluidics and Nanofluidics (ed. Prof. David Erickson). 11 pages including 8 figure

LsrR-Mediated Quorum Sensing Controls Invasiveness of Salmonella typhimurium by Regulating SPI-1 and Flagella Genes

Bacterial cell-to-cell communication, termed quorum sensing (QS), controls bacterial behavior by using various signal molecules. Despite the fact that the LuxS/autoinducer-2 (AI-2) QS system is necessary for normal expression of Salmonella pathogenicity island-1 (SPI-1), the mechanism remains unknown. Here, we report that the LsrR protein, a transcriptional regulator known to be involved in LuxS/AI-2-mediated QS, is also associated with the regulation of SPI-1-mediated Salmonella virulence. We determined that LsrR negatively controls SPI-1 and flagella gene expressions. As phosphorylated AI-2 binds to and inactivates LsrR, LsrR remains active and decreases expression of SPI-1 and flagella genes in the luxS mutant. The reduced expression of those genes resulted in impaired invasion of Salmonella into epithelial cells. Expression of SPI-1 and flagella genes was also reduced by overexpression of the LsrR regulator from a plasmid, but was relieved by exogenous AI-2, which binds to and inactivates LsrR. These results imply that LsrR plays an important role in selecting infectious niche of Salmonella in QS dependent mode

A Taxonomy of Explainable Bayesian Networks

Artificial Intelligence (AI), and in particular, the explainability thereof, has gained phenomenal attention over the last few years. Whilst we usually do not question the decision-making process of these systems in situations where only the outcome is of interest, we do however pay close attention when these systems are applied in areas where the decisions directly influence the lives of humans. It is especially noisy and uncertain observations close to the decision boundary which results in predictions which cannot necessarily be explained that may foster mistrust among end-users. This drew attention to AI methods for which the outcomes can be explained. Bayesian networks are probabilistic graphical models that can be used as a tool to manage uncertainty. The probabilistic framework of a Bayesian network allows for explainability in the model, reasoning and evidence. The use of these methods is mostly ad hoc and not as well organised as explainability methods in the wider AI research field. As such, we introduce a taxonomy of explainability in Bayesian networks. We extend the existing categorisation of explainability in the model, reasoning or evidence to include explanation of decisions. The explanations obtained from the explainability methods are illustrated by means of a simple medical diagnostic scenario. The taxonomy introduced in this paper has the potential not only to encourage end-users to efficiently communicate outcomes obtained, but also support their understanding of how and, more importantly, why certain predictions were made

The Crystal Structure of the Escherichia coli Autoinducer-2 Processing Protein LsrF

Many bacteria produce and respond to the quorum sensing signal autoinducer-2 (AI-2). Escherichia coli and Salmonella typhimurium are among the species with the lsr operon, an operon containing AI-2 transport and processing genes that are up regulated in response to AI-2. One of the Lsr proteins, LsrF, has been implicated in processing the phosphorylated form of AI-2. Here, we present the structure of LsrF, unliganded and in complex with two phospho-AI-2 analogues, ribose-5-phosphate and ribulose-5-phosphate. The crystal structure shows that LsrF is a decamer of (αβ)8-barrels that exhibit a previously unseen N-terminal domain swap and have high structural homology with aldolases that process phosphorylated sugars. Ligand binding sites and key catalytic residues are structurally conserved, strongly implicating LsrF as a class I aldolase

Biomechanical testing of fixed and adjustable femoral cortical suspension devices for ACL reconstruction under high loads and extended cyclic loading

Purpose: To compare loop elongation after 5000 cycles, loop-elongation at failure, and load at failure of the fixed-loop G-Lok device and three adjustable-loop devices (UltraButton, RigidLoop Adjustable and ProCinch RT), during testing over extended cycles under high loading. Methods: Five devices of each type were tested on a custom-built rig fixed to an Instron machine. The testing protocol had four stages: preloading, cyclic preconditioning, incremental cyclic loading and pull-to-failure. Outcome measures were loop elongation after 5000 cycles, loop-elongation at failure, and load at failure. Results: The loop elongation after 5000 cycles for G-Lok was 1.46 ± 0.25 mm, which was comparable to that of RigidLoop (1.51 ± 0.16 mm, p = 1.000) and ProCinch (1.60 ± 0.09 mm, p = 1.000). In comparison, the loop elongation for UltraButton was 2.66 ± 0.28 mm, which was significantly larger than all other devices (p = 0.048). The failure load for all devices ranged between 1455 and 2178 N. G-Lok was significantly stronger than all adjustable-loop devices (p = 0.048). The elongation at failure was largest for UltraButton (4.20 ± 0.33 mm), which was significantly greater than G-Lok (3.17 ± 0.33 mm, p = 0.048), RigidLoop (2.88 ± 0.20 mm, p = 0.048) and ProCinch (2.78 ± 0.08 mm, p = 0.048). There was no significant difference in elongation at failure for the rest of the devices. Conclusions: Our study has shown that the G-Lok fixed-loop device and the three adjustable-loop devices (UltraButton, RigidLoop Adjustable and ProCinch RT) all elongated less than 3 mm during testing over an extended number of cycles at high loads, nonetheless, the fixed loop device performed best in terms of least elongation and highest load at failure.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.published version, accepted versio

Multiphysics simulation of a microfluidic perfusion chamber for brain slice physiology

Understanding and optimizing fluid flows through in vitro microfluidic perfusion systems is essential in mimicking in vivo conditions for biological research. In a previous study a microfluidic brain slice device (μBSD) was developed for microscale electrophysiology investigations. The device consisted of a standard perfusion chamber bonded to a polydimethylsiloxane (PDMS) microchannel substrate. Our objective in this study is to characterize the flows through the μBSD by using multiphysics simulations of injections into a pourous matrix to identify optimal spacing of ports. Three-dimensional computational fluid dynamic (CFD) simulations are performed with CFD-ACE + software to model, simulate, and assess the transport of soluble factors through the perfusion bath, the microchannels, and a material that mimics the porosity, permeability and tortuosity of brain tissue. Additionally, experimental soluble factor transport through a brain slice is predicted by and compared to simulated fluid flow in a volume that represents a porous matrix material. The computational results are validated with fluorescent dye experiments

Large Scale Structure of the Universe

Galaxies are not uniformly distributed in space. On large scales the Universe displays coherent structure, with galaxies residing in groups and clusters on scales of ~1-3 Mpc/h, which lie at the intersections of long filaments of galaxies that are >10 Mpc/h in length. Vast regions of relatively empty space, known as voids, contain very few galaxies and span the volume in between these structures. This observed large scale structure depends both on cosmological parameters and on the formation and evolution of galaxies. Using the two-point correlation function, one can trace the dependence of large scale structure on galaxy properties such as luminosity, color, stellar mass, and track its evolution with redshift. Comparison of the observed galaxy clustering signatures with dark matter simulations allows one to model and understand the clustering of galaxies and their formation and evolution within their parent dark matter halos. Clustering measurements can determine the parent dark matter halo mass of a given galaxy population, connect observed galaxy populations at different epochs, and constrain cosmological parameters and galaxy evolution models. This chapter describes the methods used to measure the two-point correlation function in both redshift and real space, presents the current results of how the clustering amplitude depends on various galaxy properties, and discusses quantitative measurements of the structures of voids and filaments. The interpretation of these results with current theoretical models is also presented.Comment: Invited contribution to be published in Vol. 8 of book "Planets, Stars, and Stellar Systems", Springer, series editor T. D. Oswalt, volume editor W. C. Keel, v2 includes additional references, updated to match published versio