Experimental analysis of novel telecom source materials and devices

Incumbent telecommunication lasers emitting at 1.5 µm are fabricated on InP substrates and consist of multiple strained quantum well layers of the ternary alloy InGaAs, with barriers of InGaAsP or InGaAlAs. These lasers have been seen to exhibit very strong temperature dependence of the threshold current. This strong temperature dependence leads to a situation where external cooling equipment is required to stabilise the optical output power of these lasers. This results in a significant increase in the energy bill associated with telecommunications, as well as a large increase in equipment budgets. If the exponential growth trend of end user bandwidth demand associated with the internet continues, these inefficient lasers could see the telecommunications industry become the dominant consumer of world energy. For this reason there is strong interest in developing new, much more efficient telecommunication lasers. One avenue being investigated is the development of quantum dot lasers on InP. The confinement experienced in these low dimensional structures leads to a strong perturbation of the density of states at the band edge, and has been predicted to result in reduced temperature dependence of the threshold current in these devices. The growth of these structures is difficult due to the large lattice mismatch between InP and InAs; however, recently quantum dots elongated in one dimension, known as quantum dashes, have been demonstrated. Chapter 4 of this thesis provides an experimental analysis of one of these quantum dash lasers emitting at 1.5 µm along with a numerical investigation of threshold dynamics present in this device. Another avenue being explored to increase the efficiency of telecommunications lasers is bandstructure engineering of GaAs-based materials to emit at 1.5 µm. The cause of the strong temperature sensitivity in InP-based quantum well structures has been shown to be CHSH Auger recombination. Calculations have shown and experiments have verified that the addition of bismuth to GaAs strongly reduces the bandgap and increases the spin orbit splitting energy of the alloy GaAs1−xBix. This leads to a bandstructure condition at x = 10 % where not only is 1.5 µm emission achieved on GaAs-based material, but also the bandstructure of the material can naturally suppress the costly CHSH Auger recombination which plagues InP-based quantum-well-based material. It has been predicted that telecommunications lasers based on this material system should operate in the absence of external cooling equipment and offer electrical and optical benefits over the incumbent lasers. Chapters 5, 6, and 7 provide a first analysis of several aspects of this material system relevant to the development of high bismuth content telecommunication lasers.

Comparative genome analysis of human bifidobacteria with commercial potential

This thesis describes two newly sequenced B. longum subsp. longum genomes and subsequent comparative analysis with publicly available B. longum subsp. longum, B. longum subsp. infantis and B. longum subsp. suis genomes (Chapter 2). The acquired data revealed a closed pan-genome for this bifidobacterial species and furthermore facilitated the definition of the B. longum core genome. The comparative analysis also highlights differences in the potential metabolic abilities of all three sub-species. Interestingly, phylogenetic analysis of the B. longum core genome indicated the existence of a novel B. longum subspecies. Characterisation of restriction-modification systems from two B. longum subsp. longum strains is described in Chapter 3. These defence mechanisms limit the uptake of genetic material, which was successfully demonstrated for some of the identified systems. When these systems were by-passed by methylation of DNA prior to the transformation procedure, the resulting transformation efficiency of both B. longum subsp. longum strains was increased to a level that allowed for the generation of mutants via homologous recombination. Arabinoxylan metabolism by B. longum subsp. longum NCIMB 8809 was investigated in Chapter 4 of this thesis. Transcriptome analysis allowed the identification of a number of genes involved in the degradation, uptake and utilisation of arabinoxylan. Biochemical analysis revealed that three of the identified genes encode arabinofuranosidase activity. Phenotypic assessment of a number of insertion mutants in genes identified by the transcriptome analysis revealed the essential role of two of these enzymes in arabinoxylan metabolism, and a third enzyme in the metabolism of debranched arabinan. Furthermore, this investigation revealed that B. longum subsp. longum NCIMB 8809 does not completely degrade arabinoxylan, but utilises the arabinose substitutions only, while leaving the xylan backbone untouched.Finally, Chapter 5 outlines that B. longum subsp. longum NCIMB 8809 is capable of removing ferulic and p-coumaric acid substitutions that originate from arabinoxylan. Analysis of the genome sequence led to the identification of a candidate gene for this activity, which was subsequently cloned and expressed in E. coli. Biochemical analysis revealed that the enzyme, designated here as FaeA, is indeed capable of releasing both ferulic and p-coumaric acid from arabinoxylan. Furthermore, it is shown that a derivative of B. longum subsp. longum NCIMB 8809 carrying an insertion mutation in faeA had lost the ability to release ferulic and p-coumaric acid from arabinoxylan, and that growth of this mutant strain is negatively affected when cultivated on growth-limiting levels of arabinoxylan.

Average-case analysis of power consumption in embedded systems

Power efficiency is one of the most important constraints in the design of embedded systems since such systems are generally driven by batteries with limited energy budget or restricted power supply. In every embedded system, there are one or more processor cores to run the software and interact with the other hardware components of the system. The power consumption of the processor core(s) has an important impact on the total power dissipated in the system. Hence, the processor power optimization is crucial in satisfying the power consumption constraints, and developing low-power embedded systems. A key aspect of research in processor power optimization and management is “power estimation”. Having a fast and accurate method for processor power estimation at design time helps the designer to explore a large space of design possibilities, to make the optimal choices for developing a power efficient processor. Likewise, understanding the processor power dissipation behaviour of a specific software/application is the key for choosing appropriate algorithms in order to write power efficient software. Simulation-based methods for measuring the processor power achieve very high accuracy, but are available only late in the design process, and are often quite slow. Therefore, the need has arisen for faster, higher-level power prediction methods that allow the system designer to explore many alternatives for developing powerefficient hardware and software. The aim of this thesis is to present fast and high-level power models for the prediction of processor power consumption. Power predictability in this work is achieved in two ways: first, using a design method to develop power predictable circuits; second, analysing the power of the functions in the code which repeat during execution, then building the power model based on average number of repetitions. In the first case, a design method called Asynchronous Charge Sharing Logic (ACSL) is used to implement the Arithmetic Logic Unit (ALU) for the 8051 microcontroller. The ACSL circuits are power predictable due to the independency of their power consumption to the input data. Based on this property, a fast prediction method is presented to estimate the power of ALU by analysing the software program, and extracting the number of ALU-related instructions. This method achieves less than 1% error in power estimation and more than 100 times speedup in comparison to conventional simulation-based methods. In the second case, an average-case processor energy model is developed for the Insertion sort algorithm based on the number of comparisons that take place in the execution of the algorithm. The average number of comparisons is calculated using a high level methodology called MOdular Quantitative Analysis (MOQA). The parameters of the energy model are measured for the LEON3 processor core, but the model is general and can be used for any processor. The model has been validated through the power measurement experiments, and offers high accuracy and orders of magnitude speedup over the simulation-based method.