High performance terahertz resonant tunnelling diode sources and broadband antenna for air-side radiation

Resonant tunnelling diode (RTD) is known to be the fastest electronics device that can be fabricated in compact form and operate at room temperature with potential oscillation frequency up to 2.5 THz. The RTD device consists of a narrow band gap quantum well layer sandwiched between two thin wide band gap barriers layers. It exhibits negative differential resistance (NDR) region in its current-voltage (I-V) characteristics which is utilised in making oscillators. Up to date, the main challenge is producing high output power at high frequencies in particular. Although oscillation frequencies of ~ 2 THz have been already reported, the output power is in the range of micro-Watts. This thesis describes the systematic work on the design, fabrication, and characterisation of RTD-based oscillators in microwave/millimetre-wave monolithic integrated circuits (MMIC) form that can produce high output power and high oscillation frequency at the same time. Different MMIC RTD oscillator topologies were designed, fabricated, and characterised in this project which include: single RTD oscillator which employs one RTD device, double RTDs oscillator which employs two RTD devices connected in parallel, and coupled RTD oscillators which combine the powers of two oscillators over a single load, based on mutual coupling and which can employ up to four RTD devices. All oscillators employed relatively large size RTD devices for high power operation. The main challenge was to realise high oscillation frequency (~ 300 GHz) in MMIC form with the employed large sized RTD devices. To achieve this aim, proper designs of passive structures that can provide small values of resonating inductances were essential. These resonating inductance structures included shorted coplanar wave guide (CPW) and shorted microstrip transmission lines of low characteristics impedances Zo. Shorted transmission line of lower Zo has lower inductance per unit length. Thus, the geometrical dimensions would be relatively large and facilitate fabrication by low cost photolithography. A series of oscillators with oscillation frequencies in the J-band (220 – 325 GHz) range and output powers from 0.2 – 1.1 mW have been achieved in this project, and all were fabricated using photolithography. Theoretical estimation showed that higher oscillation frequencies (> 1 THz) can be achieved with the proposed MMIC RTD oscillators design in this project using photolithography with expected high power operation. Besides MMIC RTD oscillators, reported planar antennas for RTD-based oscillators were critically reviewed and the main challenges in designing high performance integrated antennas on large dielectric constant substrates are discussed in this thesis. A novel antenna was designed, simulated, fabricated, and characterised in this project. It was a bow-tie antenna with a tuning stub that has very wide bandwidth across the J-band. The antenna was diced and mounted on a reflector ground plane to alleviate the effect of the large dielectric constant substrate (InP) and radiates upwards to the air-side direction. The antenna was also investigated for integration with the all types of oscillators realised in this project. One port and two port antennas were designed, simulated, fabricated, and characterised and showed the suitability of integration with the single/double oscillator layout and the coupled oscillator layout, respectively.

Quantification of air quality in space and time and its effects on health

The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.