Design principles for maximizing photovoltage in metal-oxide-protected water-splitting photoanodes

Metal oxide protection layers for photoanodes may enable the development of large-scale solar fuel and solar chemical synthesis, but the poor photovoltages often reported so far will severely limit their performance. Here we report a novel observation of photovoltage loss associated with a charge extraction barrier imposed by the protection layer, and, by eliminating it, achieve photovoltages as high as 630mV, the maximum reported so far for water-splitting silicon photoanodes. The loss mechanism is systematically probed in metal-insulator-semiconductor Schottky junction cells compared to buried junction p(+) n cells, revealing the need to maintain a characteristic hole density at the semiconductor/insulator interface. A leaky-capacitor model related to the dielectric properties of the protective oxide explains this loss, achieving excellent agreement with the data. From these findings, we formulate design principles for simultaneous optimization of built-in field, interface quality, and hole extraction to maximize the photovoltage of oxide-protected water-splitting anodes.

Accommodating interruptions: a grounded theory of young people with asthma

Background: Accommodating Interruptions is a theory that emerged in the context of young people who have asthma. A background to the prevalence and management of asthma in Ireland is given to situate the theory. Ireland has the fourth highest incidence of asthma in the world, with almost one in five Irish young people having asthma. Although national and international asthma management guidelines exist it is accepted that the symptom control of asthma among the young people population is poor. Aim: The aim of this research is to investigate the lives of young people who have asthma, to allow for a deeper understanding of the issues affecting them. Methods: This research was undertaken using a Classic Grounded Theory approach. It is a systematic approach to allowing conceptual emergence from data in generating a theory that explains behaviour in resolving the participant’s main concern. The data were collected through in-depth interviews with young people aged 11-16 years who had asthma for over one year. Data were also collected from participant diaries. Constant comparative analysis, theoretical coding and memo writing were used to develop the theory. Results: The theory explains how young people resolve their main concern of being restricted, by maximizing their participation and inclusion in activities, events and relationships in spite of their asthma. They achieve this by accommodating interruptions in their lives in minimizing the effects of asthma on their everyday lives. Conclusion: The theory of accommodating interruptions explains young people’s asthma management behaviours in a new way. It allows us to understand how and why young people behave the way they do in order minimise the effect of asthma on their lives. The theory adds to the body of knowledge on young people with asthma and challenges some viewpoints regarding their behaviours.

Reasoning with imprecise trade-offs in decision making under certainty and uncertainty

In many real world situations, we make decisions in the presence of multiple, often conflicting and non-commensurate objectives. The process of optimizing systematically and simultaneously over a set of objective functions is known as multi-objective optimization. In multi-objective optimization, we have a (possibly exponentially large) set of decisions and each decision has a set of alternatives. Each alternative depends on the state of the world, and is evaluated with respect to a number of criteria. In this thesis, we consider the decision making problems in two scenarios. In the first scenario, the current state of the world, under which the decisions are to be made, is known in advance. In the second scenario, the current state of the world is unknown at the time of making decisions. For decision making under certainty, we consider the framework of multiobjective constraint optimization and focus on extending the algorithms to solve these models to the case where there are additional trade-offs. We focus especially on branch-and-bound algorithms that use a mini-buckets algorithm for generating the upper bound at each node of the search tree (in the context of maximizing values of objectives). Since the size of the guiding upper bound sets can become very large during the search, we introduce efficient methods for reducing these sets, yet still maintaining the upper bound property. We define a formalism for imprecise trade-offs, which allows the decision maker during the elicitation stage, to specify a preference for one multi-objective utility vector over another, and use such preferences to infer other preferences. The induced preference relation then is used to eliminate the dominated utility vectors during the computation. For testing the dominance between multi-objective utility vectors, we present three different approaches. The first is based on a linear programming approach, the second is by use of distance-based algorithm (which uses a measure of the distance between a point and a convex cone); the third approach makes use of a matrix multiplication, which results in much faster dominance checks with respect to the preference relation induced by the trade-offs. Furthermore, we show that our trade-offs approach, which is based on a preference inference technique, can also be given an alternative semantics based on the well known Multi-Attribute Utility Theory. Our comprehensive experimental results on common multi-objective constraint optimization benchmarks demonstrate that the proposed enhancements allow the algorithms to scale up to much larger problems than before. For decision making problems under uncertainty, we describe multi-objective influence diagrams, based on a set of p objectives, where utility values are vectors in Rp, and are typically only partially ordered. These can be solved by a variable elimination algorithm, leading to a set of maximal values of expected utility. If the Pareto ordering is used this set can often be prohibitively large. We consider approximate representations of the Pareto set based on ϵ-coverings, allowing much larger problems to be solved. In addition, we define a method for incorporating user trade-offs, which also greatly improves the efficiency.

Hydrodynamics of oscillating water column wave energy converters

This work deals with the numerical studies on hydrodynamics of oscillating water column (OWC) wave energy converters and its damping optimization on maximizing wave energy conversion by the OWC device. As a fundamental step, the hydrodynamic problems have been systematically studied by considering the interactions of the wave-structure and of the wave-internal water surface. Our first attention is on how the hydrodynamic performance can be reliably assessed, especially when it comes to the time-domain analysis, and what the physics behind the considerations is. Further on, a damping optimization for the OWC wave energy converter is also present based on the dynamics of the linear system, and a study on how we can optimize the damping for the given sea states so that the power conversion from irregular waves from irregular waves can be maximized.