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Doctor of Philosophy / Department of Biological & Agricultural Engineering / Lisa R. Wilken / Microalgae are a potential feedstock for renewable and sustainable bioproducts and energy but there are significant scientific and engineering challenges to address before widespread acceptance of this platform. In particular, biorefining microalgae serves to maximize biomass valorization and minimize waste to improve process economics. The overall goal of this dissertation was the development of a biological-based microalgae biorefinery to enhance the economic feasibility of Chlamydomonas reinhardtii as a source of multiple products including native proteins and lipids. Specific objectives included accumulating biomass enriched in target biomolecules and determining processing strategies that eliminated the need to dry biomass, employed mild conditions to maintain extractability and quality, and minimized application of petroleum-derived and toxic solvents during extraction. The microalgae biorefinery developed included biomolecule accumulation, biomass harvesting, and targeted enzymatic degradation of the cell wall and organelles for release of native proteins and lipids. Biomass was cultivated, and kinetic studies indicated that 48 h nitrogen deprivation was adequate for protein and lipid accumulation. Four lytic enzymes were screened for their ability to permeate the C. reinhardtii cell wall and the C. reinhardtii-produced enzyme, autolysin, led to >85% cell disruption. TEM imaging confirmed cell disruption and retention of lipid droplets in organelle remnants indicating that protein, lipids, and starch could be distinctly partitioned and recovered. A design of experiments optimization study determined that incubation of disrupted biomass at pH 12 for 4 h at 45°C resulted in up to 65% of total protein released from disrupted biomass followed by 40-50% protein recovery with isoelectric precipitation. The cell disruption and protein extraction steps were subsequently integrated to minimize unit operations, processing time, and energy inputs. Secondary application of trypsin led to release of ~73% of total lipids (enriched in triacylglycerols) from the disrupted biomass. Characterization by thin layer chromatography and GC-FID of released lipids revealed similar profiles of enzymatically released lipids as compared to those released by conventional extraction procedures. Finally, the composition of released lipids indicated favorable combustion behavior, high oxidation stability, and suitability as biodiesel. The developed biological-based biorefinery is a promising step towards adoption of microalgae as a source of bioproducts to provide energy and food to meet the needs of a growing population. The second focus of the work was mitigation strategies for isolation of critical impurities (or potential co-products) while processing microalgae and plant hosts. Specific emphasis was placed on evaluating the impact of proteases, polysaccharides, phenolic compounds and pigments, phytic acid, and host cell proteins on the processing of microalgae and other plant hosts for extraction, recovery, and purification of therapeutic proteins. This review served as evaluation of the broader implications of application of the biorefinery to transgenic microalgae and other plants.

Thesis(MTech( Engineering))--Cape Peninsula University of Technology, 2012 / Platinum is a precious metal which may be processed under acidic conditions. Accordingly, the extraction of platinum from an acidic chloride media is of immense practical importance. In this study, the extraction of platinum was investigated in a Pt(IV)-HCl-Cyanex 921 matrix in order to establish the effect of temperature, extractant concentration, pH and the initial platinum concentration which had been used in the evaluated solvent extraction (SX) process. The extractant phase contained a mixture of Cyanex 921 and kerosene. In addition, the extraction mechanism of platinum, and the extracted species, are also described in the study, including the determination of the following: extraction ratio, extractant loading, distribution ratio, thermodynamic parameters, and the kinetic mechanism involved in the Pt(IV)-HCl-Cyanex 921 system used. Inductively coupled plasma emission spectroscopy (ICP-ES) was used to measure the platinum concentration in the aqueous phase with a mass balance being used to determine the concentration of platinum in the organic phase. Using a combination of the variables under investigation, the experiments which were evaluated indicated that it is possible to extract sufficient platinum chlorocomplex under the following conditions: pH of 1, Cyanex 921 concentration of 8% (v/v), temperature of 298 K and an initial platinum concentration of 55.22 mg/L. Under these conditions the maximum organic-phase loading of 253.9 mg/L was achieved as compared to the theoretical loading of 507.24 mg/L. The equilibrium loading of ~50% of the platinum chlorocomplex in the organic phase was achieved after 2400 seconds of reactor operation. In this case, a distribution ratio of 9.4 was achieved. This value was observed to be higher as compared to the other SX conditions evaluated in this study.

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A study of the extraction of cobalt II ions from an aqueous growing drop into a continuous medium of di-2-ethylhexylphosphoric acid (D2EHPA) is made. The apparatus for this technique is described and a flow injection analysis method for measuring the cobalt remaining in the aqueous phase has been developed. In this study the feed concentration of cobalt has varied between 8.48 x 10-3 and 16.97 x 10-3 mole 9-1. The D2EHPA held in n-heptane, has been altered between 0.143 and 2.41 mole P. Also, pH has been adjusted between 3.10 and 4.44. The principal temperature applied to this study was 25 ±0.5*C. Acetate buffers have been used, but it is shown by calculation that about 70% of the cobaltous ion is in an uncomplexed form. The kinetics of the extraction have been modelled using a method based upon reaction in an aqueous zone near to the liquid-liquid interface with diffusion of species towards and away from the interface. This model provided a fundamental parameter 01 which incorporates the chemical rate constant kR, the D2EHPA partition coefficient PHR, the acid dissociation constnat KD for D2EHPA and the metal ion diffusivity in the interface diffusion region. The results have been compared with those of other workers who studied the transfer of cobalt into an organic drop from an aqueous continuum. The diffusion controlling film is the aqueous one. The rate constant for, the extraction reaction equation is, from this work, kR - 106.34 M3 kmol-1 sec-1 which can be compared with that found by another worker using the reverse transfer system, i. e. kR - 106.18 m3 kmol-I sec-i. . Finally, the mass transfer coefficients were found to change with varying feed concentrations and pH, this is also in agreement with other workers who have studied different liquid-liquid systems.

There is an abundance of information being generated constantly, most of it encoded as unstructured text. The information expressed this way, although publicly available, is not directly usable by computer systems because it is not organized according to a data model that could inform us how different data nuggets relate to each other. Information extraction provides a way of scanning unstructured text and extracting structured knowledge suitable for querying and manipulation. Most information extraction research focuses on machine learning approaches that can be considered black boxes when deployed in information extraction systems. We propose a declarative language designed for the information extraction task. It allows the use of syntactic patterns alongside token-based surface patterns that incorporate shallow linguistic features. It captures complex constructs such as nested structures, and complex regular expressions over syntactic patterns for event arguments. We implement a novel information extraction runtime system designed for the compilation and execution of the proposed language. The runtime system has novel features for better declarative support, while preserving practicality. It supports features required for handling natural language, like the preservation of ambiguity and the efficient use of contextual information. It has a modular architecture that allows it to be extended with new functionality, which, together with the language design, provides a powerful framework for the development and research of new ideas for declarative information extraction. We use our language and runtime system to build a biomedical information extraction system. This system is capable of recognizing biological entities (e.g., genes, proteins, protein families, simple chemicals), events over entities (e.g., biochemical reactions), and nested events that take other events as arguments (e.g., catalysis). Additionally, it captures complex natural language phenomena like coreference and hedging. Finally, we propose a rule learning procedure to extract rules from statistical systems trained for information extraction. Rule learning combines the advantages of machine learning with the interpretability of our models. This enables us to train information extraction systems using annotated data that can then be extended and modified by human experts, and in this way accelerate the deployment of new systems that can still be extended or modified by human experts.

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The work outlined in this thesis was sponsored, in part, by Anglo American and concerns the development of new technologies to achieve the concentration and separation of base metal values in chloride hydrometallurgical circuits. New processes for the production of zinc, cobalt and nickel aim to use solvent extraction to achieve the separation of metal values in highly concentrated acid chloride feeds containing iron and this thesis involves new extractants for potential use in these circuits. Anion exchange solvent extraction was chosen as the most practical approach and so a range of new reagents are described which remove zinc(II), cobalt(II) and iron(III) chlorometallates from acid chloride solutions via the reaction: nL(org) + nH+ + MClx n- [(LH)nMClx](org) Chapter 1 reviews the literature which concerns base metal chloride hydrometallurgy, presents a range of commercial processes and discusses the chemistry which underpins them. This chapter also outlines the new Anglo American circuits and the general approach to the design of base metal chlorometallate extractants. In Chapter 2, the analytical methods are discussed. These methods include the solvent extraction experiments that were used to define the behaviour of the new ligands and the techniques that were employed to examine the interactions between an extractant and a chlorometallate anion. Chapter 3 presents a series of five new amido-functionalised pyridine reagents that were designed to investigate the affect of hydrogen bond donor functionality on the extraction of zinc, cobalt and iron chlorometallates. The pyridine nitrogen atom is sterically hindered in the new reagents to suppress formation of inner-sphere complexes. Solvent extraction performance was found to vary considerably with hydrogen bond donor functionality and ligand structure. The ligand 2-(4,6-di-tertbutylpyridin- 2-yl)-N,N’-dihexylmalonamide (L2) was the strongest and most efficient extractant in this series and this was attributed to a ‘proton chelate’ six-membered ring interaction between the malonamide oxygens and the protonated pyridine nitrogen that resulted in a pre-organised array of N-H and C-H donors that could interact favourably with the chlorometallate anion. Chapter 4 explores a series of six new tertiary amine-based ligands which contain varying amido-functionality, e.g. 3-(di-2-ethylhexylamino)-N-hexylpropanamide (MAA). Zinc, cobalt and iron chlorometallate extraction studies show the amide and malonamide-functionalised ligands are notably stronger than the tertiary alkylamine control, tris-2-ethylhexylamine (TEHA). Platinum(IV) extraction is also discussed, showing that some of the new reagents are more efficient than the tren-based ligands previously described,{Bell Katherine, 2008 #93} which were the most efficient known. The enhanced extraction performance of the new ‘MAA-type’ ligands was again attributed to the formation of a ‘proton chelate’ six-membered ring forming [(LH)2MCl4] assemblies in the organic phase. Conditions have been identified which would allow separation of Fe(III), Co(II) and Zn(II) in circuits which use the ‘MAAtype’ reagents. Chapter 5 explores a series of three new malonamide reagents which contain varying alkyl-chain functionality, e.g. N,N’-dimethylhexylpentadecylmalonamide (M1), which are thought to extract chlorometallate anions via protonation of the carbonyl oxygens. Zinc, cobalt and iron chlorometallate extraction studies demonstrate that the malonamide ligands show high efficiency and selectivity for iron over zinc and cobalt. Performance as chlorometallate extractants was found to vary considerably with ligand structure and hydrogen bond donor functionality in all three ligand series, with a number of ligands showing potential for commercial application. Analysis of anion-host interactions suggests that chlorometallate binding in the organic phase probably proceeds via an array of both N-H and C-H weak hydrogen bonding interactions between the extractant and the outer-sphere of the metallate complex.

Artificial Intelligence Lab, Department of MIS, University of Arizona / The World-Wide Web WWW based Internet services have become a major channel for information delivery. For the same reason, information overload also has become a serious problem to the users of such services. It has been estimated that the amount of information stored on the Internet doubled every 18 months. The speed of increase of homepages can be even faster, some people estimated that it doubled every 6 months. Therefore, a scalable approach to support Internet searching is critical to the success of Internet services and other current or future National Information Infrastructure NII applications. In this paper, we discuss a modified version of simulated annealing algorithm to develop an intelligent personal spider agent, which is based on automatic textual analysis of the Internet documents and hybrid simulated annealing.