Novel coatings for hard tissue implants

A novel deposition process named CoBlastTM, based on grit blasting technology, has been used to deposit hydroxyapatite (HA) onto titanium (Ti) metal using a dopant/abrasive regime. The various powders (HA powder, apatitic abrasives) and the treated substrates were characterised for chemical composition, coating coverage, crystallinity and topography including surface roughness. The surface roughness of the HA surfaces could be altered using apatitic abrasives of different particle sizes. Compared to the standard plasma spraying process, the CoBlast surface produced excellent coating adhesion, lower dissolution, higher levels of mechanical and chemical stability in stimulated body fluid (SBF). Enhanced viability of osteoblastic cells was also observed on the CoBlast HA surfaces compared to the microblast and untreated Ti as well as the plasma HA coating. CoBlast offers an alternative to the traditional methods of coating HA implants with added versatility. Apatites substituted with antimicrobial metals can also be deposited to add functionality to HA coatings without cytotoxicty. The potential use of these coatings as an infection preventing strategy for application on hard tissue implants was assessed in vitro and also in vivo. Surface physicochemical properties and morphology were determined in addition to surface cytocompatibility assessments using a MG-63 osteoblast cell line. The antibacterial potential of the immobilised metal ion on the surface and the eluted ion to a lesser extent, contributed to the anticolonising behaviour of the surfaces against a standard bacteria strain (S. aureus) as well as a number of clinically relevant strains (MRSA, MSSA and S. epidermis). The results revealed that the surfaces coated with silver substituted apatites (AgA) outperformed the other apatites examined (apatites loaded with Zn, Sr and both Ag and Sr ions). Assessment of bacterial adherence on coated K-wires following subcutaneous implantation in a nude mouse infection model (S. aureus) for two days demonstrated that the 12% wt surface outperformed the 5% wt AgA coating. Lower inflammatory responses were activated with the insertion of the Ag loaded K-wires with a localised infection at the implantation site noted over the two day study period. These results indicated that the AgA coating on the surface of orthopaedic implants demonstrate good biocompatibility whilst inhibiting bacterial adhesion and colonising of the implant surface.

First principles modelling of nucleation and growth during atomic layer deposition onto III-V substrates

Atomic layer deposition (ALD) is now used in semiconductor fabrication lines to deposit nanometre-thin oxide films, and has thus enabled the introduction of high-permittivity dielectrics into the CMOS gate stack. With interest increasing in transistors based on high mobility substrates, such as GaAs, we are investigating the surface treatments that may improve the interface characteristics. We focus on incubation periods of ALD processes on III-V substrates. We have applied first principles Density Functional Theory (DFT) to investigate detailed chemistry of these early stages of growth, specifically substrate and ALD precursor interaction. We have modelled the ‘clean-up’ effect by which organometallic precursors: trimethylaluminium (TMA) or hafnium and titanium amides clean arsenic oxides off the GaAs surface before ALD growth of dielectric commences and similar effect on Si3N4 substrate. Our simulations show that ‘clean-up’ of an oxide film strongly depends on precursor ligand, its affinity to the oxide and the redox character of the oxide. The predominant pathway for a metalloid oxide such as arsenic oxide is reduction, producing volatile molecules or gettering oxygen from less reducible oxides. An alternative pathway is non-redox ligand exchange, which allows non-reducible oxides (e.g. SiO2) to be cleaned-up. First principles study shows also that alkylamides are more susceptible to decomposition rather than migration on the oxide surface. This improved understanding of the chemical principles underlying ‘clean-up’ allows us to rationalize and predict which precursors will perform the reaction. The comparison is made between selection of metal chlorides, methyls and alkylamides precursors.

Multi-scale modelling of atomic layer deposition

High-permittivity ("high-k") dielectric materials are used in the transistor gate stack in integrated circuits. As the thickness of silicon oxide dielectric reduces below 2 nm with continued downscaling, the leakage current because of tunnelling increases, leading to high power consumption and reduced device reliability. Hence, research concentrates on finding materials with high dielectric constant that can be easily integrated into a manufacturing process and show the desired properties as a thin film. Atomic layer deposition (ALD) is used practically to deposit high-k materials like HfO2, ZrO2, and Al2O3 as gate oxides. ALD is a technique for producing conformal layers of material with nanometer-scale thickness, used commercially in non-planar electronics and increasingly in other areas of science and technology. ALD is a type of chemical vapor deposition that depends on self-limiting surface chemistry. In ALD, gaseous precursors are allowed individually into the reactor chamber in alternating pulses. Between each pulse, inert gas is admitted to prevent gas phase reactions. This thesis provides a profound understanding of the ALD of oxides such as HfO2, showing how the chemistry affects the properties of the deposited film. Using multi-scale modelling of ALD, the kinetics of reactions at the growing surface is connected to experimental data. In this thesis, we use density functional theory (DFT) method to simulate more realistic models for the growth of HfO2 from Hf(N(CH3)2)4/H2O and HfCl4/H2O and for Al2O3 from Al(CH3)3/H2O.Three major breakthroughs are discovered. First, a new reaction pathway, ’multiple proton diffusion’, is proposed for the growth of HfO2 from Hf(N(CH3)2)4/H2O.1 As a second major breakthrough, a ’cooperative’ action between adsorbed precursors is shown to play an important role in ALD. By this we mean that previously-inert fragments can become reactive once sufficient molecules adsorb in their neighbourhood during either precursor pulse. As a third breakthrough, the ALD of HfO2 from Hf(N(CH3)2)4 and H2O is implemented for the first time into 3D on-lattice kinetic Monte-Carlo (KMC).2 In this integrated approach (DFT+KMC), retaining the accuracy of the atomistic model in the higher-scale model leads to remarkable breakthroughs in our understanding. The resulting atomistic model allows direct comparison with experimental techniques such as X-ray photoelectron spectroscopy and quartz crystal microbalance.

Optimizing perioperative analgesia for patients undergoing operative fixation of hip fractures

This PhD thesis describes work carried out on investigation of various interventions with the aim to optimise the anaesthetic management of patients scheduled to undergo operative fixation of hip fractures. We analysed the perioperative effects of continuous femoral nerve block, single preoperative dose of i.v. dexamethasone, the intention to deposit local anaesthetic in different locations around the femoral nerve during ultrasound guided femoral nerve block, continuous spinal anaesthesia and peri-surgical site infiltration with local anaesthetic after surgical fixation of hip fractures. Continuous femoral nerve block provided more effective preoperative analgesia six hours after the insertion of the perineural catheter compared to a standard opiate-based regimen in patients undergoing operative fixation of fractured hip. A single low dose of preoperative dexamethasone in the intervention group decreased pain scores by 75% six hours after the surgery. Both interventions had no major effect on the functional recovery in the first year after the surgical fixation of fractured hip. The results of the ultrasound guided femoral nerve block trial showed no clinical advantage of intending to deposit local anaesthetic circumferentially during performing femoral nerve block. Using the Dixon and Massey’s “up- and-down” method, we demonstrated that intrathecal 0.26 ml of 0.5% bupivacaine provided adequate surgical anaesthesia within 15 minutes in 50% of patients undergoing operative fixation of hip fracture. Finally, we demonstrated that local anaesthetic infiltration had no effect on pain scores 12 hours after the surgical fixation of fractured neck of femur. In addition to this original body of work, a review article was published on femoral nerve block highlighting the use of ultrasound guidance. In conclusion, the results of this thesis offer an insight into interventions aimed at optimising perioperative analgesia in patients scheduled to undergo operative fixation of hip fractures.

Quantum chemical study of the effect of precursor stereochemistry on dissociative chemisorption and surface redox reactions during the atomic layer deposition of the transition metal copper

Using quantum chemical calculations, we investigate surface reactions of copper precursors and diethylzinc as the reducing agent for effective Atomic Layer Deposition (ALD) of Cu. The adsorption of various commonly used Cu(II) precursors is explored. The precursors vary in the electronegativity and conjugation of the ligands and flexibility of the whole molecule. Our study shows that the overall stereochemistry of the precursor governs the adsorption onto its surface. Formation of different Cu(II)/Cu(I)/Cu(0) intermediate complexes from the respective Cu(II) compounds on the surface is also explored. The surface model is a (111) facet of a Cu55 cluster. Cu(I) compounds are found to cover the surface after the precursor pulse, irrespective of the precursor chosen. We provide new information about the surface chemistry of Cu(II) versus Cu(I) compounds. A pair of CuEt intermediates or the dimer Cu2Et2 reacts in order to deposit a new Cu atom and release gaseous butane. In this reaction, two electrons from the Et anions are donated to copper for reduction to metallic form. This indicates that a ligand exchange between the Cu and Zn is important for the success of this transmetalation reaction. The effect of the ligands in the precursor on the electron density before and after adsorption onto the surface has also been computed through population analysis. In the Cu(I) intermediate, charge is delocalized between the Cu precursor and the bare copper surface, indicating metallic bonding as the precursor densifies to the surface.

Chamber investigations of atmospheric mercury oxidation chemistry

Mercury is a potent neurotoxin even at low concentrations. The unoxidised metal has a high vapour pressure and can circulate through the atmosphere, but when oxidised can deposit and be accumulated through the food chain. This work aims to investigate the oxidation processes of atmospheric Hg0(g). The first part describes efforts to make a portable Hg sensor based on Cavity Enhanced Absorption Spectroscopy (CEAS). The detection limit achieved was 66 ngm−3 for a 10 second averaging time. The second part of this work describes experiments carried out in a temperature controlled atmospheric simulation chamber in the Desert Research Institute, Reno, Nevada, USA. The chamber was built around an existing Hg CRDS system that could measure Hg concentrations in the chamber of<100 ngm−3 at 1 Hz enabling reactions to be followed. The main oxidant studied was bromine, which was quantified with a LED based CEAS system across the chamber. Hg oxidation in the chamber was found to be mostly too slow for current models to explain. A seven reaction model was developed and tested to find which parameters were capable of explaining the deviation. The model was overdetermined and no unique solution could be found. The most likely possibility was that the first oxidation step Hg + Br →HgBr was slower than the preferred literature value by a factor of two. However, if the more uncertain data at low [Br2] was included then the only parameter that could explain the experiments was a fast, temperature independent dissociation of HgBr some hundreds of times faster than predicted thermolysis or photolysis rates. Overall this work concluded that to quantitatively understand the reaction of Hg with Br2, the intermediates HgBr and Br must be measured. This conclusion will help to guide the planning of future studies of atmospheric Hg chemistry.

Neonatal EEG classification using atomic decomposition

The electroencephalogram (EEG) is an important noninvasive tool used in the neonatal intensive care unit (NICU) for the neurologic evaluation of the sick newborn infant. It provides an excellent assessment of at-risk newborns and formulates a prognosis for long-term neurologic outcome.The automated analysis of neonatal EEG data in the NICU can provide valuable information to the clinician facilitating medical intervention. The aim of this thesis is to develop a system for automatic classification of neonatal EEG which can be mainly divided into two parts: (1) classification of neonatal EEG seizure from nonseizure, and (2) classifying neonatal background EEG into several grades based on the severity of the injury using atomic decomposition. Atomic decomposition techniques use redundant time-frequency dictionaries for sparse signal representations or approximations. The first novel contribution of this thesis is the development of a novel time-frequency dictionary coherent with the neonatal EEG seizure states. This dictionary was able to track the time-varying nature of the EEG signal. It was shown that by using atomic decomposition and the proposed novel dictionary, the neonatal EEG transition from nonseizure to seizure states could be detected efficiently. The second novel contribution of this thesis is the development of a neonatal seizure detection algorithm using several time-frequency features from the proposed novel dictionary. It was shown that the time-frequency features obtained from the atoms in the novel dictionary improved the seizure detection accuracy when compared to that obtained from the raw EEG signal. With the assistance of a supervised multiclass SVM classifier and several timefrequency features, several methods to automatically grade EEG were explored. In summary, the novel techniques proposed in this thesis contribute to the application of advanced signal processing techniques for automatic assessment of neonatal EEG recordings.

Computational study of the growth of copper thin films by atomic layer deposition

Copper is the main interconnect material in microelectronic devices, and a 2 nm-thick continuous Cu film seed layer needs to be deposited to produce microelectronic devices with the smallest features and more functionality. Atomic layer deposition (ALD) is the most suitable method to deposit such thin films. However, the reaction mechanism and the surface chemistry of copper ALD remain unclear, which is deterring the development of better precursors and design of new ALD processes. In this thesis, we study the surface chemistries during ALD of copper by means of density functional theory (DFT). To understand the effect of temperature and pressure on the composition of copper with substrates, we used ab initio atomistic thermodynamics to obtain phase diagram of the Cu(111)/SiO2(0001) interface. We found that the interfacial oxide Cu2O phases prefer high oxygen pressure and low temperature while the silicide phases are stable at low oxygen pressure and high temperature for Cu/SiO2 interface, which is in good agreement with experimental observations. Understanding the precursor adsorption on surfaces is important for understanding the surface chemistry and reaction mechanism of the Cu ALD process. Focusing on two common Cu ALD precursors, Cu(dmap)2 and Cu(acac)2, we studied the precursor adsorption on Cu surfaces by means of van der Waals (vdW) inclusive DFT methods. We found that the adsorption energies and adsorption geometries are dependent on the adsorption sites and on the method used to include vdW in the DFT calculation. Both precursor molecules are partially decomposed and the Cu cations are partially reduced in their chemisorbed structure. It is found that clean cleavage of the ligand−metal bond is one of the requirements for selecting precursors for ALD of metals. 2 Bonding between surface and an atom in the ligand which is not coordinated with the Cu may result in impurities in the thin film. To have insight into the reaction mechanism of a full ALD cycle of Cu ALD, we proposed reaction pathways based on activation energies and reaction energies for a range of surface reactions between Cu(dmap)2 and Et2Zn. The butane formation and desorption steps are found to be extremely exothermic, explaining the ALD reaction scheme of original experimental work. Endothermic ligand diffusion and re-ordering steps may result in residual dmap ligands blocking surface sites at the end of the Et2Zn pulse, and in residual Zn being reduced and incorporated as an impurity. This may lead to very slow growth rate, as was the case in the experimental work. By investigating the reduction of CuO to metallic Cu, we elucidated the role of the reducing agent in indirect ALD of Cu. We found that CuO bulk is protected from reduction during vacuum annealing by the CuO surface and that H2 is required in order to reduce that surface, which shows that the strength of reducing agent is important to obtain fully reduced metal thin films during indirect ALD processes. Overall, in this thesis, we studied the surface chemistries and reaction mechanisms of Cu ALD processes and the nucleation of Cu to form a thin film.

A distributed architecture for the monitoring and analysis of time series data

It is estimated that the quantity of digital data being transferred, processed or stored at any one time currently stands at 4.4 zettabytes (4.4 × 2 70 bytes) and this figure is expected to have grown by a factor of 10 to 44 zettabytes by 2020. Exploiting this data is, and will remain, a significant challenge. At present there is the capacity to store 33% of digital data in existence at any one time; by 2020 this capacity is expected to fall to 15%. These statistics suggest that, in the era of Big Data, the identification of important, exploitable data will need to be done in a timely manner. Systems for the monitoring and analysis of data, e.g. stock markets, smart grids and sensor networks, can be made up of massive numbers of individual components. These components can be geographically distributed yet may interact with one another via continuous data streams, which in turn may affect the state of the sender or receiver. This introduces a dynamic causality, which further complicates the overall system by introducing a temporal constraint that is difficult to accommodate. Practical approaches to realising the system described above have led to a multiplicity of analysis techniques, each of which concentrates on specific characteristics of the system being analysed and treats these characteristics as the dominant component affecting the results being sought. The multiplicity of analysis techniques introduces another layer of heterogeneity, that is heterogeneity of approach, partitioning the field to the extent that results from one domain are difficult to exploit in another. The question is asked can a generic solution for the monitoring and analysis of data that: accommodates temporal constraints; bridges the gap between expert knowledge and raw data; and enables data to be effectively interpreted and exploited in a transparent manner, be identified? The approach proposed in this dissertation acquires, analyses and processes data in a manner that is free of the constraints of any particular analysis technique, while at the same time facilitating these techniques where appropriate. Constraints are applied by defining a workflow based on the production, interpretation and consumption of data. This supports the application of different analysis techniques on the same raw data without the danger of incorporating hidden bias that may exist. To illustrate and to realise this approach a software platform has been created that allows for the transparent analysis of data, combining analysis techniques with a maintainable record of provenance so that independent third party analysis can be applied to verify any derived conclusions. In order to demonstrate these concepts, a complex real world example involving the near real-time capturing and analysis of neurophysiological data from a neonatal intensive care unit (NICU) was chosen. A system was engineered to gather raw data, analyse that data using different analysis techniques, uncover information, incorporate that information into the system and curate the evolution of the discovered knowledge. The application domain was chosen for three reasons: firstly because it is complex and no comprehensive solution exists; secondly, it requires tight interaction with domain experts, thus requiring the handling of subjective knowledge and inference; and thirdly, given the dearth of neurophysiologists, there is a real world need to provide a solution for this domain