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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/19236
Title: Investigation of Quantitative NMR by Statistical Analysis
Authors: Lao, Lydia Lai-Mui
Advisor: Bain, A. D.
Department: Chemistry
Keywords: quantitative, NMR, statistical, analysis, mixtures, samples
Publication Date: Mar-1991
Abstract: <p> Quantitation by nuclear magnetic resonance (NMR) has been frequently done with integrals. The use of peak heights has been thought to be unreliable. The aim of this thesis is to examine the reliability of peak height method in achieving quantitative NMR measurements for small molecules such as water and sucrose.</p> <p> Isotope measurements have been traditionally done by isotope-ratio mass spectrometry. This is no doubt a highly sensitive technique for analyzing pure samples but the analysis of mixtures is not as straight-forward as it would be for the former. Ontario Hydro has encountered problems in measuring deuterium in DMSO/water mixtures. To solve the problem with NMR, an analytical method has been established to measure the deuterium content in waters and in DMSO/water mixtures. This involved testing a linear model for analyzing waters which were enriched or depleted with deuterium as well as applying the model to quantify DMSO/water mixtures. Both 1H and 2H NMR were employed. Satisfactory accuracy and precision of the results were obtained.</p> <p> For quantitative 13C work, the peak height method is often not recommended due to the variations in signal width, which is a result of varied T2 values and nuclear Overhauser enhancement (NOE). Sucrose molecules in cane sugar and beet sugar have different 13C isotopic ratios because they are synthesized by different photosynthetic pathways. To see the usefulness and limitation of the peak height method, 13C spectra of sucrose were acquired and the carbon peaks were quantified. Good precision was achieved but no predictable trend in the isotope difference could be found.</p>
URI: http://hdl.handle.net/11375/19236
Appears in Collections:Open Access Dissertations and Theses

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