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Thin films are used in many energy conversion applications, ranging from photodetectors to solar cells. Accurately predicting the radiative properties of thin films when they possess rough surfaces is critical in many instances, but can be challenging due to the complexity arising from light scattering and interferences at the microscale. This work describes measurements of the spectral transmittance and reflectance of several thin-film materials (including crystalline silicon wafers and a polycrystalline diamond film) in the mid-infrared spectral region (2 20 m) using a Fourier-transform infrared (FT-IR) spectrometer. The transmittance and reflectance were calculated using thin-film optics for the double-side polished samples and scalar scattering theory for the single-side polished samples. The effects of partial coherence are considered using a fringe smoothing technique. The interval used for fringe smoothing was assumed to be linearly dependent on the wavenumber. Good agreement between the predicted and measured transmittance was achieved for the double-side polished silicon wafers and for the diamond film. The disagreement for some single-side polished silicon wafers may be inherently related to their surface microstructures, as suggested from surface topographic data and images obtained from surface profilometry and microscopy. By comparing the intervals used for fringe smoothing with the instrumental resolution, beam divergence in the spectrometer was found to be a major factor contributing to the partial coherence. Future research is proposed to investigate the correlation between the detailed surface characteristics and the conical-conical transmittance and reflectance.

Thesis (M.S.)--West Virginia University, 2002. / Title from document title page. Document formatted into pages; contains xiii, 187 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 171-175).

Thesis (Ph.D)--Chemical Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Sujit Banerjee; Committee Co-Chair: Wm. James Frederick, Jr.; Committee Member: John D. Muzzy; Committee Member: Kristiina Iisa; Committee Member: Preet Singh. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Variable-temperature Fourier transform infrared (VT-FTIR) spectroscopy in conjunction with 2D correlation analysis was employed to study the unfolding of aspartate transcarbamylase (ATCase) and its individual subunits. The regulatory subunit (RSU) was uniformly labeled with 13C/15N and then reconstituted with the unlabeled catalytic subunit (CSU) to form the holoenzyme. The activity of the holoenzyme was shown to be unaffected by the isotopic labeling of the RSU. The VT-FTIR investigation of the isolated CSU and the CSU in the holoenzyme revealed that the CSU is more thermally stable when bound to the RSU (i.e., in the holoenzyme). The RSU also showed more thermal stability when bound to the CSU. The sequences of events leading to the unfolding of the isolated CSU and RSU and the CSU in the holoenzyme were deduced by 2D correlation analysis of the VT-FTIR spectra. The results for the isolated CSU demonstrated that beta-sheets unfold first, followed by a-helices and then turns, and finally aggregates form. The sequence of unfolding of the RSU showed an increase of turns followed by a loss of intramolecular beta sheets, then a loss of alpha-helices and the formation of aggregates. The CSU in the holoenzyme exhibited a slightly different unfolding pathway and was observed to unfold subsequent to the unfolding of the RSU, consistent with the two thermal transitions observed by differential scanning calorimetry.

Infrared spectra of microbial cells are highly specific, fingerprint-like signatures which can be used to differentiate microbial species and strains from each other. In this study, the potential applicability of Fourier transform infrared (FTIR) spectroscopy for the classification of yeast strains in terms of their biological taxonomy, their use in the production of wine, beer, and bread, and their sensitivity to killer yeast strains was investigated. Sample preparation, spectral data preprocessing methods and spectral classification techniques were also investigated. All yeast strains were grown on a single growth medium. The FTIR spectra were baseline corrected and the second derivative spectra were computed and employed in spectral analysis. The classification accuracy was improved when the principal component spectra (calculated from the second derivative spectra) were employed rather than the second derivative spectra or raw spectra alone. Artificial neural network (ANN) with 10 units in the input layer and 12 units in the hidden layer produced a robust prediction model for the identification of yeasts. Cluster analysis was employed for the classification of yeast strains in terms of their use in the production of wine, beer, and bread and in terms of their sensitivity to killer yeast strains. The optimum region for the classification in the former case was found to be between 1300 and 800 cm-1 in the infrared spectrum whereas the optimum region for the classification of yeast strains in terms of their sensitivity was between 900 and 800 cm-1 . The results of this work demonstrated that FTIR spectroscopy could be successfully employed for the classification and identification of yeast strains with minimal sample preparation.

Fourier transform near-infrared (FT-NIR) spectroscopy was investigated as a means of quantitative analysis of edible fats and oils. Initially, a method of simultaneously determining the cis and trans content, iodine value and saponification number of neat fats and oils using a heated transmission flow cell was developed. Two partial least squares (PLS) calibrations were devised, a process-specific calibration based on hydrogenated soybean oil and a more generalized calibration based on many oil types, the latter able to analyze oils from a variety of sources accurately and reproducibly. Methodology for the quantitative determination of the peroxide value (PV) of edible oils using a novel glass-vial sample handling system was subsequently developed, based on the stoichiometric reaction of triphenylphosphine with hydroperoxides to form triphenylphosphine oxide. The PV calibration was derived using PLS regression, and the results of a validation study demonstrated that PV could be quantitated accurately if a normalization routine was used to compensate for the inherent dimensional variability of the vials. The vial sample handling system was then used in the development of PLS IV calibrations for the process analysis of commercial oil samples, and these samples were also used to evaluate a global IV calibration devised by Bomem Inc. The discriminant features available through PLS were shown to enhance the accuracy of the IV predictions by facilitating the selection of the most appropriate calibrations based on the spectral characteristics of closely related oils. The predictions obtained using the global IV calibration provided clear evidence that a generalized calibration based on a large and varied selection of oils could provide a means of IV determination by FT-NIR spectroscopy. Subsequently, a generalized FT-NIR trans calibration was developed and shown to yield trans values that were in good agreement with those obtained by the AOCS mid-FTIR single-bounce hori