This dissertation research has focused on the design of two spectroscopic instruments that operate outside of the UV/visible region for the analysis of volatile organic hydrocarbons and hard-to-separate hydrocarbon mixtures. The first design was solid state near infrared spectrometer. The fast acquisition rate of the NIR spectrometer allowed the monitoring of the bromination of 1-hexene. The concentrations of 1-hexene and 1,2-dibromohexane were determined for the reaction using classical least squares. The root mean squared errors of prediction for 1-hexene and 1,2-dibromohexane concentrations were 0.01 and 0.003 M, respectively. This research project also focused on the investigation of the effects of instrumental parameters on partial least squares models by comparing the results obtained from four different spectrometers. The results indicate that instrumental parameters, such as resolution and wavelength coverage, have a larger effect on experimental results than the analysis method (NIR or Raman). The second instrument design investigated here was a vacuum ultraviolet ICP-AES which monitored the 130 to 200 nm wavelength range. Fifteen nonmetals were used to determine the quantitative characteristics of the design. All elements demonstrated detection limits in the ppb range. The most sensitive emission line in this work was the aluminum 167.079 nm line which had a detection limit of 200 ppt. A VUV atomic emission line database was developed to provide an analytical reference for future investigations. The database included the emission lines from 76 elements over the 130 to 195 nm wavelength region. Over 2200 lines were observed and reported. Over 1000 of the lines were previously unreported in the two major existing references for the VUV. This work is the first VUV reference to provide truly comparable intensities for a large number of elements. A GC-VUV-ICP-AES was developed to investigate the potential of VUV-ICP atomic emission spectroscopy to provide both quantitative and qualitative information for mixtures. Chlorine and carbon chromatograms were obtained simultaneously for volatile organic hydrocarbon (VOC) mixtures. The work showed that GC-VUV-ICP-AES has the potential of generating empirical formulas for compounds by simultaneously quantitating each element in the compound and determining their ratios.

Research was undertaken to explore the application of surface enhanced Raman scattering (SERS) to the understanding of electrosorption phenomena. In particular, the relative strength of interactions between the functional groups of imidazole (N₁, N₂ and the π orbitals) on Ag electrodes was examined. This information is useful in understanding how the presence of these functional groups contributes to the relative adsorption strength of nitrogen heterocycles. A Raman spectrometer equipped with a charge-coupled device (CCD) detector was required to obtain reproducible SERS spectra in this research. It was also necessary to obtain accurate Raman shifts so that small (ca. 1-2 cm⁻¹ vibrational frequency changes between adsorbed and solution species could be detected. Therefore, significant effort was expended to develop calibration and spectral acquisition procedures which would provide acceptable accuracy and efficiency. Instrumental factors affecting Raman spectral calibration were studied. Available Raman shift calibration standards are reviewed and improved Raman shift data for these standards are reported. Several methods for the conversion of CCD position (pixel number) data to wavelength and Raman shifts are appraised using both experimental and simulated Raman data. SERS spectra for imidazole, 1-methylimidazole, and 2-methylimidazole support the conclusion that these molecules are adsorbed to the Ag electrode through the "pyridine nitrogen" (N₃). This evidence includes vibrational frequency shifts and orientations of these molecules deduced from the consideration of SERS surface selection rules. These data also suggest that the π orbital of the C=N bond interacts with the electrode at potentials near -0.25 V (versus SCE reference electrode) producing a tilt of the ring relative to the surface at these potentials. At potentials near the potential of zero charge (ca. -0.80 V), this interaction is minimized and these molecules assume a more vertical position. At the most negative potentials examined, the methylimidazoles interact with the surface predominantly through the methyl group. Preliminary work on the application of SERS to obtain surface coverage information was performed. An increase in SERS intensity with increasing solution concentration suggests adsorption isotherm-like behavior.

Recovery rates of certain polar and non-polar volatile organic compounds were evaluated for bias associated with the use of a Nafion® dryer in the analyses of environmental samples. Analyses of dryer inlet verses dryer outlet concentrations of specific compounds were used to assess the extent of Nafion® bias. A select group of 22 polar and 6 non-polar compounds, as well as historical data from other authors was used to develop a stepwise multiple regression model to aid in predicting recovery rates. Specific compound physical parameters used in this model include water solubility, hydrogen bonding capacity, and dipole moment. The overall R squared or predictive value of this model is 0.7885. Typical recovery rates of non-polar and extremely polar compounds are 100% and <10% respectively. Compounds that possess moderate intermolecular interactions (aldehydes, ethers, esters, and ketones) resulted in recovery rates between 10% and 100%.

Amylose based chromatographic chiral stationary phases (CSPs) are widely used throughout liquid chromatography to separate enantiomers, although little is known about the interaction processes operating on these phases. / This thesis describes a systematic study into the retention and enantioselective separation capabilities of the tris (3,5-dimethylphenylcarbmate), tris (R-phenylethylcarbamate) and tris (S-phenylethylcarbamate) stationary phases. / The underlying aim of this work was to obtain an understanding of the solute-stationary phase interactions which are responsible for the chromatographic retention and separation of enantiomers. By development of quantitative structure-enantioselective retention relationships (QSERR), it was possible to identify the primary components involved in the molecular interaction process and describe those interactions in terms of non-empirical solute descriptors. / Results for several different series of racemic compounds indicate that multiple mechanisms are possible and that retention may be described by combinations of several key classes of interaction including hydrogen bonding, electrostatic, lipophilic, charge transfer and steric interactions. Progressive development of these properties from classical point interactions to molecular interactions, supports a proposed theory of chiral recognition which extends from the basic three-point model to a more complex dynamic molecular model. This new model, derived to explain obtained experimental results, addresses issues in chirality which are not adequately covered by previous theory. It is proposed that the original theory is a static model which does not authentically reflect real systems and as such, cannot account for all experimentally observed molecular interactions of an enantiospecific nature. A modified and improved theory of chiral recognition has been fashioned, which includes the vital aspects of conformational adjustment and molecular fit. / Finally, the first reported application of artificial neural networks in chiral chromatography is documented. Multi-layer feed forward neural networks, with error back propagation, have been used in combination with QSERR as a basis to development of chiral chromatographic expert systems. Resulting networks contained cross validated predictive ability ranging from 94 to 97%.

In this thesis, we applied both numerical methods and artificial intelligence techniques to NMR data processing and analysis. First, a comprehensive study of the Iterative Quadratic Maximum Likelihood (IQML) method applied to NMR spectral parameter estimation is reported. The IQML is compared to other conventional time domain data analysis methods. Extensive simulations demonstrate the superior performance of the IQML method. We also develop a new technique, which uses genetic algorithm with a priori knowledge, to improve the quantification of NMR spectral parameters. The new proposed method outperforms the other conventional methods, especially in the situations that there are signals close in frequencies and the signal-to-noise ratio of the FID is low. / The usefulness of Singular Value Decomposition (SVD) method in NMR data processing is further exploited. A new two dimensional spectral processing scheme based on SVD is proposed for suppressing strong diagonal peaks. The superior performance of this method is demonstrated on an experimental phase-sensitive COSY spectrum. / Finally, we studied the feasibility of using neural network predicted secondary structure information in the NMR data analysis. Protein chemical shift databases are compiled and are used with the neural network predicted protein secondary structure information to improve the accuracy of protein chemical shift prediction. The potential of this strategy for amino acid classification in NMR resonance assignment is explored.

The use of immobilized enzymes has steadily increased in recent years. Based upon the advantages that immobilized enzymes possess over soluble enzymes, numerous applications have emerged in medical and analytical fields. This work demonstrates the applicability of a liquid chromatographic system based upon coupled on-line immobilized enzyme reactors (IMERs) to organic synthesis, biochemistry and pharmacology. It is envisioned that the model system will grow into a modular process where synthetic chemists can add or subtract the enzymes necessary for their particular synthetic goal. The system allows for on-line chromatographic purification and structural identification of products and could greatly reduce time required to discover new synthetic pathways. In addition, the construction of a coupled enzyme system provides a number of approaches to basic research into synthetic and metabolic pathways as well as a rapid method for the discovery of new pharmaceutical substances. / A coupled system using extremely different enzymes with incompatible cofactors and reaction conditions has been constructed. The significance of the proposed project not only lies in the development of the liquid chromatographic on-line enzyme cascade but also in the biosynthetic pathway chosen for this study. The biosynthetic pathway involving dopamine beta-hydroxylase and phenylethanolamine N-methyltransferase encompass the synthesis of the key transmitters, norepinephrine and epinephrine. The results demonstrate for the first time the immobilization of dopamine beta-hydroxylase and phenylethanolamine N-methyltransferase. The IMERs are active and can be used in a liquid chromatographic format for qualitative and quantitative determinations. Studies with the IMER-HPLC systems have also shown that the activity of the immobilized enzymes reflects the non-immobilized enzymes. Thus, the IMER-HPLC system can be used to carry out standard Michaelis-Menten enzyme kinetic studies and to quantitatively determine enzyme kinetic constants, identify specific enzyme inhibitors, provide information regarding the mode of inhibition and the inhibitor constants (Ki). The immobilized enzyme reactors used independently or as a combination will provide a unique opportunity to explore the interrelationships between these enzymes, to investigate the source of catecholamine-related disorders and to design new drug entities for identified clinical syndromes.

An automated sequential assignment protocol for proteins is presented using heteronuclear 3D NMR. For the observed amino acid spin systems, the protocol includes an algorithm to determine their amino acid types. For the detected polypeptides, the protocol includes another algorithm to sequentially map them to the primary sequence. The former algorithm measures the similarity between the detected spin systems and the 20 standard amino acid patterns. Both chemical shift and topological likeness are considered. Knowing the amino acid types, the mapping algorithm assigns the detected polypeptides to proper positions within the protein primary sequence. The assignment protocol can be applied to spin systems generated from many different approaches. To demonstrate the assignment protocol, a few computer algorithms were designed to deduce the backbone and side-chain spin systems of proteins using heteronuclear 3D NMR. Magnetization transfer through peptide bonds can be observed in triple resonance 3D NMR. To automate the backbone assignment using the through-bond correlations, a generic algorithm is proposed. This algorithm searches and merges cross peaks among all available NMR spectra. Individual spin systems can be extracted and linked to create polypeptide chains based on the observed interresidue correlations. The algorithm is not restricted to any particular type of experiment. It is shown to be applicable to two sets of NMR spectra: the five experiment set of 3D HNCO, HNCA, HN(CO)CA, HCACO, $ sp{15}$N TOCSY-HMQC and the one-experiment set of 3D CBCANH. For the side chain assignment, an automated approach using a constrained partitioning algorithm has been developed to extract side chain spin systems of proteins by analyzing the 3D HCCH-COSY/TOCSY spectra. The extracted amino acid spin systems show the chemical shifts of the component nuclear spins as well as the connectivities between these spins. A 90-residue protein, the N-domain of chicken skeletal troponin-C

This thesis presents the first systematic study of the cobalt site preferences in iron rare-earth based compounds. The Mossbauer source technique employed in this work offers a direct and unambiguous way to quantitatively determine cobalt site preferences in these compounds at extremely low cobalt contents. Data quality as well as counting efficiency for the source ($ sp{57}$Co doped) samples is enhanced by constructing a resonant conversion electron detector utilising 90% $ sp{57}$Fe enriched stainless steel foil. Our results have produced the most convincing evidence that cobalt substitutes preferentially for iron in these compounds. We have demonstrated that the site volume is the dominant factor controlling the preferential cobalt substitutions at transition-metal sites with volume $<$12.2A$ sp3$. The cobalt preference for a site decreases linearly with increasing site volume at a rate of $ sim$0.9A$ sp{-3}$. In general, cobalt shows a preference for sites with volume $<$11.8A$ sp3$. As site volume becomes sufficiently large ($ ge$12.2A$ sp3$), the negative enthalpy of mixing between cobalt and rare-earth plays a significant role in modifying the cobalt site preferences in combination with the site volume effects. This results in cobalt preferring strongly those sites with the highest number of rare-earth nearest-neighbors.

A fast-beam collinear laser spectroscopy apparatus has been designed and tested with the $ sp{23}$Na D$ sb2$ line (wavelength = 589 nm) on continuous atomic beams. / A radio-frequency quadrupole ion trap and its associated electronics have been assembled and successfully operated, trapping $ sp{23}$Na$ sp{+}$ ions from an external source built for the purposes of this work. The bunched ions were extracted and detected; the effect of several injection, bunching and extraction parameters on the extracted bunches' size were studied. A simple model of the ion bunching and losses in the trap is proposed. / From the sensitivity limit of the collinear laser spectroscopy apparatus and the maximum bunched current output from the trap, the possibility of performing fast-beam collinear laser spectroscopy measurements on bunched atomic beams is examined.

Lactate is a key metabolite of glycolytic activity and as such, can be used as an indicator of the energy production of the whole organism, for the assessment of tissue perfusion and oxidative capacity. Estimating lactate levels in biological fluids allows the determination of anaerobic threshold during physical exercise. Likewise, lactate is of significant importance in several clinical situations, where a rapid and easy method is needed for diagnostic assessment and survival rate increase of the patient. / To achieve this objective, the potential of Near Infrared Spectroscopy (NIRS) to quantify lactate in biological fluids and tissues was evaluated. Initially, the project focused on quantifying of lactate in plasma samples taken from exercising humans. Using Partial Least Squares (PLS) and a leave-N-out cross validation routine, it was found that lactate concentration in human plasma could be estimated with a standard error of cross validation of 0.51 mmol/L. / To minimize sample preparation and reduce the time of analysis, NIRS was then evaluated as a technique for rapid analysis of lactate in whole blood from exercising rats and humans. Furthermore, standard addition method was used to expand the lactate concentration range and therefore cover a greater part of the physiological lactate concentration range. Regression analysis provided standard errors of cross validation of 0.29 mmol/L and 0.65 mmol/L for rats and humans respectively. / To improve precision, referenced lactate measurements were calculated. In this method, baseline spectra of subjects were subtracted from all collected spectra before chemometric routines were used. An improvement of the standard error of cross validation to 0.21 mmol/L was found by applying this procedure. / In vivo measurement of lactate during exercise in humans by NIRS was also evaluated. Using diffuse reflectance and 2D correlation spectroscopy, lactate was identified as the primary constituent monitored by in vivo measurements. Regression analysis resulted in a substantial error of 2.21 mmol/L for absolute measurements. However, results for referenced lactate measurements provided a significant improvement of the standard error of cross validation to 0.76 mmol/L. This finding suggests that NIRS may provide a valuable tool to assess in vivo physiological status for both research and clinical needs.