A COHERENCE-COLORED LOOK INSIDE REVERSE MICELLES: ADVANCING MAGNETIC RESONANCE RELAXOMETRY TO CHARACTERIZE INTERNAL WATER POOL DYNAMICS

<p>Traditional data acquisition methods in Nuclear Magnetic Resonance (NMR) collect a subset of the total amount of generated data and discard the rest. In this work, a modified approach toward NMR data acquisition and analysis is formalized and applied in a series of different contexts, ultimately illustrating the utility of collecting and considering this traditionally discarded data. In particular, it is shown that this approach both facilitates and improves NMR data acquisition capabilities at low field (15 MHz), enabling one to overcome challenges arising from, for example, fluctuations in the static magnetic field.With these developments in hand, the dual resonance (nuclear/electron) liquid state relaxometry technique, Overhauser Dynamic Nuclear Polarization (ODNP), is extended for the first time to the thorough characterization of the translational dynamics of water within reverse micelles (RMs). These results are supplemented with high field (400 MHz 1H) deuterium relaxometry measurements to study additional properties of these internal water pools, such as the rotational dynamics of the water. Additional high field applications of this approach to data acquisition and processing are described, with promising outlook for addressing common concerns in standard NMR and pulse EPR experiments. This work also describes the construction of a modular ODNP spectrometer, highlighting the importance of this modified data acquisition and processing technique toward this endeavor. Additionally, alternative ODNP processing and acquisition schemes are outlined, with the potential to simplify data handling and reduce experimental time. Finally, instrumental improvements facilitated by the modular spectrometer design adopted here has enabled the study of RM water pools in fully protonated solvents, providing access to systems otherwise deemed not suitable for low field ODNP analysis.

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Chemistry

Year

2022

Author dc:creator

• Beaton, Alec

Contributors dc:contributor

• Franck, John

• Chemistry
• Physical Chemistry

Repository record dc:identifier

https://surface.syr.edu/etd/1581

OAI identifier oai:identifier

oai:surface.syr.edu:etd-2582