The impact of trench defects in InGaN/GaN light emitting diodes and implications for the "green gap" problem

The impact of trench defects in blue InGaN/GaN light emitting diodes (LEDs) has been investigated. Two mechanisms responsible for the structural degradation of the multiple quantum well (MQW) active region were identified. It was found that during the growth of the p-type GaN capping layer, loss of part of the active region enclosed within a trench defect occurred, affecting the top-most QWs in the MQW stack. Indium platelets and voids were also found to form preferentially at the bottom of the MQW stack. The presence of high densities of trench defects in the LEDs was found to relate to a significant reduction in photoluminescence and electroluminescence emission efficiency, for a range of excitation power densities and drive currents. This reduction in emission efficiency was attributed to an increase in the density of non-radiative recombination centres within the MQW stack, believed to be associated with the stacking mismatch boundaries which form part of the sub-surface structure of the trench defects. Investigation of the surface of green-emitting QW structures found a two decade increase in the density of trench defects, compared to its blue-emitting counterpart, suggesting that the efficiency of green-emitting LEDs may be strongly affected by the presence of these defects. Our results are therefore consistent with a model that the “green gap” problem might relate to localized strain relaxation occurring through defects.This is the accepted manuscript version. The final version is available from AIP at http://scitation.aip.org/content/aip/journal/apl/105/11/10.1063/1.4896279?showFTTab=true&containerItemId=content/aip/journal/apl

Neural Network Parameterizations of Electromagnetic Nucleon Form Factors

The electromagnetic nucleon form-factors data are studied with artificial feed forward neural networks. As a result the unbiased model-independent form-factor parametrizations are evaluated together with uncertainties. The Bayesian approach for the neural networks is adapted for chi2 error-like function and applied to the data analysis. The sequence of the feed forward neural networks with one hidden layer of units is considered. The given neural network represents a particular form-factor parametrization. The so-called evidence (the measure of how much the data favor given statistical model) is computed with the Bayesian framework and it is used to determine the best form factor parametrization.Comment: The revised version is divided into 4 sections. The discussion of the prior assumptions is added. The manuscript contains 4 new figures and 2 new tables (32 pages, 15 figures, 2 tables

Prediction of Cellular Burden with Host--Circuit Models

Heterologous gene expression draws resources from host cells. These resources include vital components to sustain growth and replication, and the resulting cellular burden is a widely recognised bottleneck in the design of robust circuits. In this tutorial we discuss the use of computational models that integrate gene circuits and the physiology of host cells. Through various use cases, we illustrate the power of host-circuit models to predict the impact of design parameters on both burden and circuit functionality. Our approach relies on a new generation of computational models for microbial growth that can flexibly accommodate resource bottlenecks encountered in gene circuit design. Adoption of this modelling paradigm can facilitate fast and robust design cycles in synthetic biology

Supernova remnants: the X-ray perspective

Supernova remnants are beautiful astronomical objects that are also of high scientific interest, because they provide insights into supernova explosion mechanisms, and because they are the likely sources of Galactic cosmic rays. X-ray observations are an important means to study these objects.And in particular the advances made in X-ray imaging spectroscopy over the last two decades has greatly increased our knowledge about supernova remnants. It has made it possible to map the products of fresh nucleosynthesis, and resulted in the identification of regions near shock fronts that emit X-ray synchrotron radiation. In this text all the relevant aspects of X-ray emission from supernova remnants are reviewed and put into the context of supernova explosion properties and the physics and evolution of supernova remnants. The first half of this review has a more tutorial style and discusses the basics of supernova remnant physics and thermal and non-thermal X-ray emission. The second half offers a review of the recent advances.The topics addressed there are core collapse and thermonuclear supernova remnants, SN 1987A, mature supernova remnants, mixed-morphology remnants, including a discussion of the recent finding of overionization in some of them, and finally X-ray synchrotron radiation and its consequences for particle acceleration and magnetic fields.Comment: Published in Astronomy and Astrophysics Reviews. This version has 2 column-layout. 78 pages, 42 figures. This replaced version has some minor language edits and several references have been correcte