Investigation of charge-transport models for organic light-emitting devices

Organic light emitting devices (OLEDs) show promise for use in the display industry, particularly as the active display portion of flat panel televisions and monitors. Unfortunately important material fundamentals of these organics are not well understood, like charge transport, charge injection and exciton formation/relaxation. It is therefore useful to attempt to understand the behavior of these materials in the physical state that they will be used in: thin films. There have been two models proposed to explain charge transport in these materials and it is the purpose of this work to examine them using a group of similar materials. These materials are similar enough to use the same theoretical models on, yet different enough to draw conclusions about those models from the observed differences

Extending the Latent Multinomial Model with Complex Error Processes and Dynamic Markov Bases

The latent multinomial model (LMM) model of Link et al. (2010) provided a general framework for modelling mark-recapture data with potential errors in identification. Key to this approach was a Markov chain Monte Carlo (MCMC) scheme for sampling possible configurations of the counts true capture histories that could have generated the observed data. This MCMC algorithm used vectors from a basis for the kernel of the linear map between the true and observed counts to move between the possible configurations of the true data. Schofield and Bonner (2015) showed that a strict basis was sufficient for some models of the errors, including the model presented by Link et al. (2010), but a larger set called a Markov basis may be required for more complex models. We address two further challenges with this approach: 1) that models with more complex error mechanisms do not fit easily within the LMM and 2) that the Markov basis can be difficult or impossible to compute for even moderate sized studies. We address these issues by extending the LMM to separately model the capture/demographic process and the error process and by developing a new MCMC sampling scheme using dynamic Markov bases. Our work is motivated by a study of Queen snakes (Regina septemvittata) in Kentucky, USA, and we use simulation to compare the use of PIT tags, with perfect identification, and brands, which are prone to error, when estimating survival rates

Projecting the impacts of illness on labour force participation: An application of Health&WealthMOD

Health&WealthMOD is the first Australian microsimulation model designed to determine the economic impacts of disease on older workers, aged 45 to 65 years. Chronic health conditions are known to be associated with early retirement. This paper describes an application of Health&WealthMOD to estimate the impact of this association on projected labour force participation to 2020 given the ageing population and long-term trend in chronic conditions. Due to ageing and disease trends, the number of people with chronic conditions in the 45-64 years age group was expected to rise to about 4.8 million by 2020, an increase of 82% from the 2003 population of the same age group. About 904,000 persons in the 45-64 age group were projected to be out of the labour force due to ill health in 2020, when only the ageing and population growth were considered. When trends in illness were captured, the figure was increased to about 1.2 million persons. This demonstrates that health is a major driver of labour force participation and retirement and that economic policies alone, with no consideration of health interventions to treat or prevent chronic illness, will only have a limited impact on labour force participation. Thus, it is important that the government focuses on both health policies and economic policies in order to make sure that there will be an adequate supply of labour force in future.impacts of illness, labour force, participation, Health&WealthMOD

Case Studies - Health&WealthMOD: a microsimulation model of the economic impacts of diseases on older workers

The Australian Government is seeking to encourage older workers to remain in the labour force longer to overcome future labour shortages and ensure adequate taxation revenue to fund the needs of an ageing population. Longer labour force participation also has benefits to individuals in terms of available income and capacity to save for a better standard of living in retirement. While the Government recognises that not all older workers are able to participate in the labour force, there is little information on what health conditions keep people from working, or what the costs are to the government or the individual. This case study outlines how a new micro simulation model, Health&WealthMOD, is being designed to fill this information gap by estimating the economic impacts of illness. The general approach adopted is outlined, following which two early applications of the model are presented. The model is used to explore the determinants of the duration spent in retirement and to generate projections of retirement due to illness to 2020.health; disability; wealth; retirement period

Modelling the cost of ill health in Health&WealthMOD (Version II): lost labour force participation, income and taxation, and the impact of disease prevention

This paper provides a detailed description of the construction of Health&WealthMOD (Version II). It is Australia’s only microsimulation model of health and illness and their impacts on labour force participation, income, wealth and government revenue and expenditure. In this paper, we describe Health&WealthMOD (Version II) and its architecture, the application of the model, and some of the results it has produced.Health&WealthMOD, cost of ill health, lost labour force participation, income, taxation, disease prevention

Failure to predict igneous rocks encountered during exploration of sedimentary basins : a case study of the Bass Basin, Southeastern Australia

This work was carried out during a research visit to the Australian School of Petroleum at the University of Adelaide, and forms part of the lead author's PhD research, which is funded by a University of Aberdeen College of Physical Sciences Scholarship. Seismic interpretation was conducted using IHS Kingdom, and well log interpretation using Schlumberger Techlog software. Synthetic seismic response modelling was performed using Ikon RokDoc software. This paper greatly benefited from the reviews of Sverre Planke, Kamal'deen Omosanya and an anonymous reviewer.Peer reviewedPostprin

Fe K-edge X-ray Absorption Spectroscopy of corrosion phases of archaeological iron: results, limitations, and the need for complementary techniques

Data analysis methods for iron X-ray Absorption Spectroscopy (XAS) can provide extensive information about the oxidation state and co-ordination of an Fe-species. However, the extent to which techniques developed using a single-phase iron sample may be applied to complex, mixed-phase samples formed under real-world conditions is not clear. This work uses a combination of pre-edge fitting and linear combination analysis (LCA) to characterise the near edge region of the X-ray absorption spectrum (XANES) for a set of archaeological iron corrosion samples from a collection of cast iron cannon shot excavated from the Mary Rose shipwreck and compares the data with phase compositions determined by Synchrotron X-ray Powder Diffraction (SXPD). Archaeological powder and cross-section samples were compared to a library of iron standards and diffraction data. The XANES are consistent with previous observations that generation of the chlorinated phase akaganeite, β-FeO(OH,Cl), occurs in those samples which have been removed form passive storage and subjected to active conservation. However, the results show that if any metallic species is present in the sample, the contribution from Fe(0) to the spectral region containing a pre-edge for oxidised iron - Fe(II) and Fe(III) - causes the analysis to be less effective and the conclusions unreliable. Consequently, while the pre-edge fitting methodology may be applied to a mixture of iron oxides or oxyhydroxides, the procedure is inappropriate for a mixed metal-oxide sample without the application of a complimentary technique, such as SXPD

The build up of stars and dust in nearby galaxies

In this thesis I took a combined sample of dust-selected galaxies (from Clark et al. 2015) and HI-selected galaxies (from De Vis et al. 2016). The dust selected sample contains a large fraction of intriguing galaxies dubbed the ‘Blue And Dusty Gas Rich Sources’ (BADGRS), while the HI selected sources revealed another population of blue and gas rich systems which are instead dust-poor. I investigated whether the unique properties of these galaxies could be explained by variations in their recent star formation activity. I showed that the BADGRS are younger, and have typically experienced more recent bursts of star formation compared to the non-BADGRS. Splitting the sample into dust-rich and dust-poor sources showed that both subpopulations are of similar age, although the dust-rich sources have experienced a burst of star formation more recently. I took the chemical evolution model of Morgan & Edmunds (2003), used more recently used in Rowlands et al. (2014), and updated many of the functions and libraries in line with recent literature. I then produced a suite of models to investigate the dust and metal properties of 425 Herschel sources. These models showed (i) a delayed star formation history is required to match the observed star formation rates; (ii) inflows and outflows are required to explain the observed metallicities at low gas fractions; (iii) a significantly reduced contribution of dust from supernovae is necessary to explain the dust poor sources with high gas fractions. We also showed the dust-to-metal ratio is not definitively constant in all galaxies, and that there is evidence for a decrease in the dust-to-metals ratio towards lower metallicity. This thesis proposes a model in which the dust, gas, metals and stars can be modelled in a consistent and coherent manner, and gains insight into the dust-to-gas evolution at early epochs