The research topic addressed in this thesis is the development of new ideas and techniques for acceleration and automation of processes involved in the design of chemical products with predefined properties. In particular, we demonstrate techniques that address the shortcomings of the existing methods and take a bird's-eye view over the new possible directions for chemical product development necessitated by the integration of bio-feedstocks into the existing supply chain. Futhermore, we introduce an approach for sequential, on-line multi-target product/process optimization in a scenario where: automation of the overall design process is sought; adequate physical models are not available; unknown constraints on the decision space may be present; and resources are limited or costly. We test the approach on a number of simulations. The results indicate that the approach is able to, in a modest number of iterations, find solutions associated with the targets to a satisfactory degree of accuracy. In addition, for supervised problems where categorical data are available, we introduce an approach that allows one to perform categorization of a given product composition according to a particular property. We test our solutions empirically on real data. The results show that the approach compares well with existing state of the art techniques. We also investigate the application of a variety of nonlinear dimensionality techniques to the visualisation of chemical product data.

No description available.

No description available.

Olfaction is one of the most important senses by which insects obtain information about their environment. In the early stages of olfactory perception in insects, odour molecules are carried across the sensillum lymph by small soluble Odorant Binding Proteins (OBPs). This is followed by activation of the appropriate olfactory receptor, resulting in an electrical impulse, and subsequent degradation of the initial signal. OBPs have been studied in a range of insect orders including Lepidoptera, Diptera and Orthoptera, and this study reports the cloning and characterisation of cDNAs with a potential olfactory role in the vetch aphid, Megoura viciae (Buckton, Homoptera: Aphididiae). Construction and sequencing of antennal cDNA libraries identified two cDNAs, MvicOBP1 and Mv164, which were approximately 0.8kb and 1kb respectively. The amino acid sequence of MvicOBP1 has the spacing pattern of six cysteine residues that is characteristic of insect OBPs, and Mv164 shows similarity to insect cytochrome P450 enzymes. RT-PCR showed that these cDNAs have specific or enhanced expression in the chemosensory tissues of M. viciae, and parallel expression patterns suggest a "linked" function. Related sequences are present and expressed in other aphid species, and sequencing of genomic fragments allowed the partial elucidation of the intron/exon organisation of these genes. Subtracted antennal cDNA libraries identified two cDNAs encoding proteins with significant similarity to insect chemosensory proteins (CSPs), cDNAs encoding Juvenile Hormone Binding Proteins (JHBPs), and a tissue-specific cDNA with a potential carrier role. These, coupled with the OBPs, add evidence to the suggestion that there is an insect superfamily of binding proteins. A PBP from Bombyx mori (BmorPBP1) was used as a model system for in vitro expression of an insect OBP and subsequent characterisation of the recombinant protein. Four forms of this protein, identified through their interaction with an anti-BmorPBP antibody, were resolved by isoelectric focusing.

Chapter One contains a brief overview of zeolites, their structure, uses and synthesis. Chapter Two relates to the attempted synthesis of quinuclidines via a novel 6-endo-trig radical cyclisation. Chapter Three contains a review of the 'Zip reaction' and the attempted synthesis of triazacyclopentadecane derivatives. Chapter Four relates to the synthesis of pyrrolidines via retro-Cope cyclisation methodology. Reviews of the Cope and retro-Cope reactions, nitrone synthesis and nucleophilic addition of carbon nucleophiles to nitrones are included. The synthetic work is split into three sections relating to the electron withdrawing group used to stabilise the carbanion of the nucleophile - ester, sulphone and sulphoxide - and attempts to indicate the utility of the retro-Cope reaction in the diastereoselective synthesis of substituted pyrrolidines.

This PhD thesis describes research for a medical application of electronic nose technology. There is a need at present for early detection of bacterial infection in order to improve treatment. At present, the clinical methods used to detect and classify bacteria types (usually using samples of infected matter taken from patients) can take up to two or three days. Many experienced medical staff, who treat bacterial infections, are able to recognise some types of bacteria from their odours. Identification of pathogens (i.e. bacteria responsible for disease) from their odours using an electronic nose could provide a rapid measurement and therefore early treatment. This research project used existing sensor technology in the form of an electronic nose in conjunction with data pre-processing and classification methods to classify up to four bacteria types from their odours. Research was performed mostly in the area of signal conditioning, data pre-processing and classification. A major area of interest was the use of artificial neural networks classifiers. There were three main objectives. First, to classify successfully a small range of bacteria types. Second, to identify issues relating to bacteria odour that affect the ability of an artificially intelligent system to classify bacteria from odour alone. And third, to establish optimal signal conditioning, data pre-processing and classification methods. The Electronic Nose consisted of a gas sensor array with temperature and humidity sensors, signal conditioning circuits, and gas flow apparatus. The bacteria odour was analysed using an automated sampling system, which used computer software to direct gas flow through one of several vessels (which were used to contain the odour samples), into the Electronic Nose. The electrical resistance of the odour sensors were monitored and output as electronic signals to a computer. The purpose of the automated sampling system was to improve repeatability and reduce human error. Further improvement of the Electronic Nose were implemented as a temperature control system which controlled the ambient gas temperature, and a new gas sensor chamber which incorporated improved gas flow. The odour data were collected and stored as numerical values within data files in the computer system. Once the data were stored in a non-volatile manner various classification experiments were performed. Comparisons were made and conclusions were drawn from the performance of various data pre-processing and classification methods. Classification methods employed included artificial neural networks, discriminant function analysis and multi-variate linear regression. For classifying one from four types, the best accuracy achieved was 92.78%. This was achieved using a growth phase compensated multiple layer perceptron. For identifying a single bacteria type from a mixture of two different types, the best accuracy was 96.30%. This was achieved using a standard multiple layer perceptron. Classification of bacteria odours is a typical `real world' application of the kind that electronic noses will have to be applied to if this technology is to be successful. The methods and principles researched here are one step towards the goal of introducing artificially intelligent sensor systems into everyday use. The results are promising and showed that it is feasible to used Electronic Nose technology in this application and that with further development useful products could be developed. The conclusion from this thesis is that an electronic nose can detect and classify different types of bacteria.

In this thesis, research on kinetic and equilibrium state properties of some new adsorption pairs and non-equilibrium models are investigated. In the first part, the equlilibrium characteristics of adsorption pairs using carbon dioxide as adsorbate are studied. The results showed that the performance of this kind of adsorption system is poor due to the low latent heat of carbon dioxide. New composite ammonia adsorbents, 12.3 wt. % CaCl2/C (3C), 17 wt. % CaCl2/Aluminia (SWS), and 59 wt. % BaCl2/vermiculite, were synthesized and studied. It was found that the modification of host matrices by the salt dramatically increases the ammonia uptake. Hysteresis between the synthesis and decomposition reaction was found and the van't Hoff equation was applied to describe the hysteresis. In the second part, kinetic experiments of the composite ammonia adsorbent, 59 wt. % BaCl2/vermiculite, were performed under isothermal conditions and conditions that would be experienced in a real system. Based on the experimental data, a modified linear driving force (LDF) model is used to simulate the dynamics of adsorption pair. In the model, two resistant constants were obtained empirically from the experimental data. In the third part, the dynamic model of concentration change with heat and mass transfer equation were used to simulate the performance of adsorption system. The results were very encouraging with a maximum COP of around 0.8 and a maximum SCP of around 600W kg-1 in an air conditioning application with one-bed basic cycle. Further studies could focus on the commercial analysis of this promising material in air conditioning. A real lab-scale compact bed could be set up and tested for the performance of adsorption pairs.

No description available.

No description available.

Thesis (Ph.D.) -- McMaster University, 1999. / Includes bibliographical references (leaves 231-245). Also available via World Wide Web.