This dissertation explores the effect of nanometer-scale changes in structure on the energetics of photocatalytic and photovoltaic materials. Of particular interest are semiconductor nanocrystals (NCs), which have interesting chemical properties that lead to novel structures and applications. Chief among these properties are quantum confinement and the high surface area-to-volume ratio, which allow for chemical tuning of the energetics and structure of NCs. This tunable energetic landscape has led to increasing application of NCs in various areas of research, including solar energy conversion, light-emitting diode technologies, and photocatalysis. However, spectroscopic methods to determine the energetics of NCs have not been well developed, due to chemical complexities of relevant NCs such as polydispersity, capping ligand effects, core-shell structures, and other chemical modifications. In this work, we demonstrate and expand the utility of photoelectron spectroscopy (PES) to probe the energetics of NCs by considering the physical processes that lead to background and secondary photoemission to enhance photoemission from the sample of interest. A new methodology for the interpretation of UP spectra was devised in order to emphasize the minute changes to the UP spectra line shape that arise from nanoscopic changes to the NCs. We applied various established subtractions that correct for photon source satellites, secondary photoelectrons, and substrate photoemission. We then investigated the effect of ligand surface coverage on the surface chemistry and density of states at the top of valence band (VB). We systematically removed ligands by increasing numbers of purification steps for two diameters of NCs and found that doing so increased photoemission density at the top of the VB, which is due to undercoordinated surface atoms. Deeper VB structure was also altered, possibly due to reorganization of the atoms in the NC. Using the new UPS interpretation methodology, we examined the evolution of the valence band energy (EVB) of CdSe NCs as it was modified from spherical NC to rod to Au-NP tipped nanorod (NR). We also employed potential-modulated attenuated total reflectance spectroscopy (PM-ATR) to probe the conduction band energy (ECB) of the series. The EVB decreased with each modification, which is predicted with a band-bending model. This trend was also observed in the ECB, as revealed by spectroelectrochemistry, along with the appearance of new metal-semiconductor states in the band gap. UPS was finally used to investigate the even more complex Pt-NP tipped CdSe@CdS core@shell NR heterostructure. The addition of the CdS shell decreases the EVB relative to CdSe, as expected from common cation II-VI compounds. The Pt-NC increases the EVB, which, like the Au-CdSe NR, is predicted by employing a band-bending model. XPS revealed that PtSx-like chemical states were formed near the CdS-Pt interface. These experiments, along with the improved UP spectra interpretation methodology, demonstrate the wealth of information regarding surface chemistry and energetics that can be obtained with PES which can be applied to not only NCs, but also to metal oxide or molecular thin films.

The focus of the projects presented here was to develop possible solutions to three issues commonly encountered during chemometric analysis of comprehensive two-dimensional liquid chromatography diode array detector (LCxLC-DAD) data. The focus of the first project was to determine a means of performing background correction that removed two background ridges. The methods of simply subtracting out a mean blank sample, singular value decomposition based background correction (SVD-BC) and asymmetrically weighted least squares (AWLS) were compared. AWLS was found to be the only background correction technique to fully remove the ridges. However, AWLS was also found to attenuate the peak intensity by approximately 25% due to over fitting of the background at the lower wavelengths. The focus of the second project was the investigation of five common interpolation strategies for the reconstruction of the sampled first dimension peak. The interpolation strategy that best reproduced the original first dimension retention time was Gaussian fitting. This was expected given that the simulated data set was generated using a Gaussian model for the peak shape. An algorithm, semi-automated alignment method (SAAM), was then developed that allowed for each peak to be aligned independently of the other peaks in the data set. SAAM was validated using both simulated and experimental data. The simulated results indicated that SAAM produced percent recoveries close to 100%. SAAM was also compared to iterative key set factor analysis-alternating least squares (IKSFA-ALS) for the analysis of phenytoin in a waste water treatment plant effluent. SAAM produced a concentration of 26±3 ppb compared to 39±9 ppb from IKSFA-ALS. While these results are very different, the result produced by SAAM is still within the experimental error of the reference 2D-LC/MS/MS method, 42±19. Finally, SAAM was compared to two existing literature methods. A mixture of simulated and experimental data sets was used to measure the accuracy and precision of the results. SAAM was found to be impacted less by intra- and inter-sample retention time shifting then PARAFAC2. SAAM and shifted candecomp/PARAFAC were found to produce very similar results. However, SAAM was found to experience some difficulty producing accurate and precise results with some of the experimental data sets.

Master of Science / Department of Statistics / Susan J. Brown / Haiyan Wang / DNA hybridization microarray technologies have made it possible to gain an unbiased perspective of whole genome transcriptional activity on such a scale that is increasing more and more rapidly by the day. However, due to biologically irrelevant bias introduced by the experimental process and the machinery involved, correction methods are needed to restore the data to its true biologically meaningful state. Therefore, it is important that the algorithms developed to remove any sort of technical biases are accurate and robust. This report explores the concept of background correction in microarrays by using a real data set of five replicates of whole genome tiling arrays hybridized with genetic material from Tribolium castaneum. It reviews the literature surrounding such correction techniques and explores some of the more traditional methods through implementation on the data set. Finally, it introduces an alternative approach, implements it, and compares it to the traditional approaches for the correction of such errors.

A quantitative evaluation of single photon emission computed tomography (SPECT) and planar scintigraphic imaging may be valuable for both diagnostic and therapeutic purposes. For an accurate quantification it is usually necessary to correct for attenuation and scatter and in some cases also for septal penetration. For planar imaging a background correction for the contribution from over- and underlying tissues is needed. In this work a few correction methods have been evaluated and further developed. Much of the work relies on the Monte Carlo method as a tool for evaluation and optimisation. A method for quantifying the activity of I-125 labelled antibodies in a tumour inoculated in the flank of a mouse, based on planar scintigraphic imaging with a pin-hole collimator, has been developed and two different methods for background subtraction have been compared. The activity estimates of the tumours were compared with measurements in vitro. The major part of this work is attributed to SPECT. A method for attenuation and scatter correction of brain SPECT based on computed tomography (CT) images of the same patient has been developed, using an attenuation map calculated from the CT image volume. The attenuation map is utilised not only for attenuation correction, but also for scatter correction with transmission dependent convolution subtraction (TDCS). A registration method based on fiducial markers, placed on three chosen points during the SPECT examination, was evaluated. The scatter correction method, TDCS, was then optimised for regional cerebral blood flow (rCBF) SPECT with Tc-99m, and was also compared with a related method, convolution scatter subtraction (CSS). TDCS has been claimed to be an iterative technique. This requires however some modifications of the method, which have been demonstrated and evaluated for a simulation with a point source. When the Monte Carlo method is used for evaluation of corrections for septal penetration, it is important that interactions in the collimator are taken into account. A new version of the Monte Carlo program SIMIND with this capability has been evaluated by comparing measured and simulated images and energy spectra. This code was later used for the evaluation of a few different methods for correction of scatter and septal penetration of I-123 brain SPECT. The methods were CSS, TDCS and a method where correction for scatter and septal penetration are included in the iterative reconstruction. This study shows that quantitative accuracy in I-123 brain SPECT benefits from separate modelling of scatter and septal penetration.

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