Low-frequency, high-density, inductively coupled plasma sources : operation and applications

Operation regimes, plasma parameters, and applications of the low-frequency (∼500 kHz) inductively coupled plasma (ICP) sources with a planar external coil are investigated. It is shown that highly uniform, high-density (ne∼9×1012 cm-3) plasmas can be produced in low-pressure argon discharges with moderate rf powers. The low-frequency ICP sources operate in either electrostatic (E) or electromagnetic (H) regimes in a wide pressure range without any Faraday shield or an external multipolar magnetic confinement, and exhibit high power transfer efficiency, and low circuit loss. In the H mode, the ICP features high level of uniformity over large processing areas and volumes, low electron temperatures, and plasma potentials. The low-density, highly uniform over the cross-section, plasmas with high electron temperatures and plasma and sheath potentials are characteristic to the electrostatic regime. Both operation regimes offer great potential for various plasma processing applications. As examples, the efficiency of the low-frequency ICP for steel nitriding and plasma-enhanced chemical vapor deposition of hydrogenated diamond-like carbon (DLC) films, is demonstrated. It appears possible to achieve very high nitriding rates and dramatically increase micro-hardness and wear resistance of the AISI 304 stainless steel. It is also shown that the deposition rates and mechanical properties of the DLC films can be efficiently controlled by selecting the discharge operating regime.

Effect of ion current density on the properties of vacuum arc-deposited TiN coatings

The influence of ion current density on the thickness of coatings deposited in a vacuum arc setup has been investigated to optimize the coating porosity. A planar probe was used to measure the ion current density distribution across plasma flux. A current density from 20 to 50 A/m2 was obtained, depending on the probe position relative to the substrate center. TiN coatings were deposited onto the cutting inserts placed at different locations on the substrate, and SEM was used to characterize the surfaces of the coatings. It was found that lowdensity coatings were formed at the decreased ion current density. A quantitative dependence of the coating thickness on the ion current density in the range of 20-50 A/m2 were obtained for the films deposited at substrate bias of 200 V and nitrogen pressure 0.1 Pa, and the coating porosity was calculated. The coated cutting inserts were tested by lathe machining of the martensitic stainless steel AISI 431. The results may be useful for controlling ion flux distribution over large industrial-scale substrates.

Modelling total duration of traffic incidents including incident detection and recovery time

Traffic incidents are key contributors to non-recurrent congestion, potentially generating significant delay. Factors that influence the duration of incidents are important to understand so that effective mitigation strategies can be implemented. To identify and quantify the effects of influential factors, a methodology for studying total incident duration based on historical data from an ‘integrated database’ is proposed. Incident duration models are developed using a selected freeway segment in the Southeast Queensland, Australia network. The models include incident detection and recovery time as components of incident duration. A hazard-based duration modelling approach is applied to model incident duration as a function of a variety of factors that influence traffic incident duration. Parametric accelerated failure time survival models are developed to capture heterogeneity as a function of explanatory variables, with both fixed and random parameters specifications. The analysis reveals that factors affecting incident duration include incident characteristics (severity, type, injury, medical requirements, etc.), infrastructure characteristics (roadway shoulder availability), time of day, and traffic characteristics. The results indicate that event type durations are uniquely different, thus requiring different responses to effectively clear them. Furthermore, the results highlight the presence of unobserved incident duration heterogeneity as captured by the random parameter models, suggesting that additional factors need to be considered in future modelling efforts.

Charge transport and density of trap states in balanced high mobility ambipolar organic thin-film transistors

We report on charge transport and density of trap states (trap DOS) in ambipolar diketopyrrolopyrrole-benzothiadiazole copolymer thin-film transistors. This semiconductor possesses high electron and hole field-effect mobilities of up to 0.6 cm 2/V-s. Temperature and gate-bias dependent field-effect mobility measurements are employed to extract the activation energies and trap DOS to understand its unique high mobility balanced ambipolar charge transport properties. The symmetry between the electron and hole transport characteristics, parameters and activation energies is remarkable. We believe that our work is the first charge transport study of an ambipolar organic/polymer based field-effect transistor with room temperature mobility higher than 0.1 cm 2/V-s in both electrons and holes.

Exploring the properties of macroscopic fundamental diagram : analysing Brisbane urban network

This thesis explored traffic characteristics at the aggregate level for area-wide traffic monitoring of large urban area. It focused on three aspects: understanding a macroscopic network performance under real-time traffic information provision, measuring traffic performance of a signalised arterial network using available data sets, and discussing network zoning for monitoring purposes in the case of Brisbane, Australia. This work presented the use of probe vehicle data for estimating traffic state variables, and illustrated dynamic features of regional traffic performance of Brisbane. The results confirmed the viability and effectiveness of area-wide traffic monitoring.

Interpreting scratch assays using pair density dynamics and approximate Bayesian computation

Quantifying the impact of biochemical compounds on collective cell spreading is an essential element of drug design, with various applications including developing treatments for chronic wounds and cancer. Scratch assays are a technically simple and inexpensive method used to study collective cell spreading; however, most previous interpretations of scratch assays are qualitative and do not provide estimates of the cell diffusivity, D, or the cell proliferation rate,l. Estimating D and l is important for investigating the efficacy of a potential treatment and provides insight into the mechanism through which the potential treatment acts. While a few methods for estimating D and l have been proposed, these previous methods lead to point estimates of D and l, and provide no insight into the uncertainty in these estimates. Here, we compare various types of information that can be extracted from images of a scratch assay, and quantify D and l using discrete computational simulations and approximate Bayesian computation. We show that it is possible to robustly recover estimates of D and l from synthetic data, as well as a new set of experimental data. For the first time, our approach also provides a method to estimate the uncertainty in our estimates of D and l. We anticipate that our approach can be generalized to deal with more realistic experimental scenarios in which we are interested in estimating D and l, as well as additional relevant parameters such as the strength of cell-to-cell adhesion or the strength of cell-to-substrate adhesion.

Development of a dragline in-bucket bulk density monitor

This paper details the implementation and trialling of a prototype in-bucket bulk density monitor on a production dragline. Bulk density information can provide feedback to mine planning and scheduling to improve blasting and consequently facilitating optimal bucket sizing. The bulk density measurement builds upon outcomes presented in the AMTC2009 paper titled ‘Automatic In-Bucket Volume Estimation for Dragline Operations’ and utilises payload information from a commercial dragline monitor. While the previous paper explains the algorithms and theoretical basis for the system design and scaled model testing this paper will focus on the full scale implementation and the challenges involved.

Mismatch negativity in recent-onset and chronic schizophrenia : a current source density analysis

Mismatch negativity (MMN) is a component of the event-related potential elicited by deviant auditory stimuli. It is presumed to index pre-attentive monitoring of changes in the auditory environment. MMN amplitude is smaller in groups of individuals with schizophrenia compared to healthy controls. We compared duration-deviant MMN in 16 recent-onset and 19 chronic schizophrenia patients versus age- and sex-matched controls. Reduced frontal MMN was found in both patient groups, involved reduced hemispheric asymmetry, and was correlated with Global Assessment of Functioning (GAF) and negative symptom ratings. A cortically-constrained LORETA analysis, incorporating anatomical data from each individual's MRI, was performed to generate a current source density model of the MMN response over time. This model suggested MMN generation within a temporal, parietal and frontal network, which was right hemisphere dominant only in controls. An exploratory analysis revealed reduced CSD in patients in superior and middle temporal cortex, inferior and superior parietal cortex, precuneus, anterior cingulate, and superior and middle frontal cortex. A region of interest (ROI) analysis was performed. For the early phase of the MMN, patients had reduced bilateral temporal and parietal response and no lateralisation in frontal ROIs. For late MMN, patients had reduced bilateral parietal response and no lateralisation in temporal ROIs. In patients, correlations revealed a link between GAF and the MMN response in parietal cortex. In controls, the frontal response onset was 17 ms later than the temporal and parietal response. In patients, onset latency of the MMN response was delayed in secondary, but not primary, auditory cortex. However amplitude reductions were observed in both primary and secondary auditory cortex. These latency delays may indicate relatively intact information processing upstream of the primary auditory cortex, but impaired primary auditory cortex or cortico-cortical or thalamo-cortical communication with higher auditory cortices as a core deficit in schizophrenia.

Interface of graphane with copper : a van der Waals density-functional study

Various forms of hydrogenated graphene have been produced to date by several groups, while the synthesis of pure graphane has not been achieved yet. The study of the interface between graphane, in all its possible hydrogenation configurations, and catalyst metal surfaces can be pivotal to assess the feasibility of direct CVD growth methods for this material. We investigated the adhesion of graphane to a Cu(111) surface by adopting the vdW-DF2-C09 exchange-correlation functional, which is able to describe dispersion forces. The results are further compared with the PBE and the LDA exchange-correlation functionals. We calculated the most stable geometrical configurations of the slab/graphane interface and evaluated how graphane's geometrical parameters are modified. We show that dispersion forces play an important role in the slab/graphane adhesion. Band structure calculations demonstrated that in the presence of the interaction with copper, the band gap of graphane is not only preserved, but also enlarged, and this increase can be attributed to the electronic charge accumulated at the interface. We calculated a substantial energy barrier at the interface, suggesting that CVD graphane films might act as reliable and stable insulating thin coatings, or also be used to form compound layers in conjunction with metals and semiconductors.

Developing a transdisciplinary approach to improve urban traffic congestion based on Product Ecosystem theory

Product Ecosystem theory is an emerging theory that shows that disruptive “game changing” innovation is only possible when the entire ecosystem is considered. When environmental variables change faster than products or services can adapt, disruptive innovation is required to keep pace. This has many parallels with natural ecosystems where species that cannot keep up with changes to the environment will struggle or become extinct. In this case the environment is the city, the environmental pressures are pollution and congestion, the product is the car and the product ecosystem is comprised of roads, bridges, traffic lights, legislation, refuelling facilities etc. Each one of these components is the responsibility of a different organisation and so any change that affects the whole ecosystem requires a transdisciplinary approach. As a simple example, cars that communicate wirelessly with traffic lights are only of value if wireless-enabled traffic lights exist and vice versa. Cars that drive themselves are technically possible but legislation in most places doesn’t allow their use. According to innovation theory, incremental innovation tends to chase ever diminishing returns and becomes increasingly unable to tackle the “big issues.” Eventually “game changing” disruptive innovation comes along and solves the “big issues” and/or provides new opportunities. Seen through this lens, the environmental pressures of urban traffic congestion and pollution are the “big issues.” It can be argued that the design of cars and the other components of the product ecosystem follow an incremental innovation approach. That is why the “big issues” remain unresolved. This paper explores the problems of pollution and congestion in urban environments from a Product Ecosystem perspective. From this a strategy will be proposed for a transdisciplinary approach to develop and implement solutions.

Simulation-based density estimation for time series using covariate data

This paper proposes a simulation-based density estimation technique for time series that exploits information found in covariate data. The method can be paired with a large range of parametric models used in time series estimation. We derive asymptotic properties of the estimator and illustrate attractive finite sample properties for a range of well-known econometric and financial applications.

Profiling high-range speeding offenders : investigating criminal history, personal characteristics, traffic offences, and crash history

This paper reports profiling information for speeding offenders and is part of a larger project that assessed the deterrent effects of increased speeding penalties in Queensland, Australia, using a total of 84,456 speeding offences. The speeding offenders were classified into three groups based on the extent and severity of an index offence: once-only low-rang offenders; repeat high-range offenders; and other offenders. The three groups were then compared in terms of personal characteristics, traffic offences, crash history and criminal history. Results revealed a number of significant differences between repeat high-range offenders and those in the other two offender groups. Repeat high-range speeding offenders were more likely to be male, younger, hold a provisional and a motorcycle licence, to have committed a range of previous traffic offences, to have a significantly greater likelihood of crash involvement, and to have been involved in multiple-vehicle crashes than drivers in the other two offender types. Additionally, when a subset of offenders’ criminal histories were examined, results revealed that repeat high-range speeding offenders were also more likely to have committed a previous criminal offence compared to once only low-range and other offenders and that 55.2% of the repeat high-range offenders had a criminal history. They were also significantly more likely to have committed drug offences and offences against order than the once only low-range speeding offenders, and significantly more likely to have committed regulation offences than those in the other offenders group. Overall, the results indicate that speeding offenders are not an homogeneous group and that, therefore, more tailored and innovative sanctions should be considered and evaluated for high-range recidivist speeders because they are a high-risk road user group.

Association hierarchy mining and its application for network traffic characterisation

This thesis presents an association rule mining approach, association hierarchy mining (AHM). Different to the traditional two-step bottom-up rule mining, AHM adopts one-step top-down rule mining strategy to improve the efficiency and effectiveness of mining association rules from datasets. The thesis also presents a novel approach to evaluate the quality of knowledge discovered by AHM, which focuses on evaluating information difference between the discovered knowledge and the original datasets. Experiments performed on the real application, characterizing network traffic behaviour, have shown that AHM achieves encouraging performance.