Glass materials surround us, impacting our lives on a daily basis, whether geologically deposited by volcanic activity or synthesized in large volume by industry. These amorphous oxide materials are vastly important due to their variety of applications including solid electrolytes, cookware, and storage of high-level nuclear waste. Although they are used for different applications, one common characteristic of these materials is the absence of long-range periodic order. This makes it difficult to use traditional solid-state characterization methods such as x-ray and neutron diffraction to study glass structure. Nuclear magnetic resonance (NMR), is ideally suited to study materials that exhibit short-range non-periodic order as it probes directly at a nucleus of interest and is sensitive to its local structural environment. This ability of solid-state NMR is illustrated by revealing local structural features in various oxide materials presented in this thesis. Within is a compilation of studies looking at basic borates, followed by borovanadates and complex borosilicate glasses. A multinuclear application of using quantum chemical calculations, single and double resonance methods and charge-balance models are discussed to deconvolute the complex structures of these disordered materials. This is followed by a study of a difficult low-gamma nucleus, 73Ge, (once considered “impossible” for solid-state NMR) which is explored for future material studies by looking at 73Ge NMR of crystalline and glassy germanates. 73Ge chemical shifts were related to coordination environments and quadrupolar coupling constants were related to bond length distortions.
| Identifer | oai:union.ndltd.org:MANITOBA/oai:mspace.lib.umanitoba.ca:1993/4305 |
| Date | 14 December 2010 |
| Creators | Michaelis, Vladimir K. |
| Contributors | Kroeker, Scott (Chemistry), Budzelaar, Peter (Chemistry) Cadogan, Sean (Physics and Astronomy) Jeffrey, Kenneth (Physics, University of Guelph) |
| Source Sets | University of Manitoba Canada |
| Language | en_US |
| Detected Language | English |
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