UC Berkeley

Nuclear magnetic resonance (NMR) is among the most powerful analytical tools available to the chemical and biological sciences for chemical detection, characterization, and structure elucidation. NMR experiments are usually performed in large magnetic fields in order to maximize sensitivity and increase chemical shift resolution. However, the high magnetic fields required for conventional NMR necessitate large, immobile, and expensive superconducting magnets, limiting the use of the technique. New hyperpolarization and non-inductive detection methods have recently allowed for NMR measurements in the inverse regime of extremely low magnetic fields. Whereas a substantial body of research has been conducted in the high-field regime, taking advantage of the efficient coherent control afforded by a spectroscopy dominated by coupling to the spectrometer, the zero- and ultra-low-field (ZULF) regime has remained mostly unexplored. In this dissertation, we investigate the applicability of ZULF-NMR as a novel spectroscopic technique complimentary to high-field NMR.

In particular, we consider various aspects of the ZULF-NMR experiment and the dynamics of nuclear spins under various local spin coupling Hamiltonians. We first survey zero-field NMR experiments on systems dominated by the electron-mediated indirect spin-spin coupling (J-coupling). The resulting J-spectra permit precision measurement of chemically relevant information due to the exquisite sensitivity of J-couplings to subtle changes in molecular geometry and electronic structure. We also consider the effects of weak magnetic fields and residual dipolar couplings in anisotropic media, which encode information about nuclear magnetic moments and geometry, and further resolve topological ambiguities by lifting degeneracies. By extending the understanding of the interactions that contribute to ZULF-NMR spectra, this work represents a significant advancement towards a complete description of zero- and ultra-low-field nuclear magnetic resonance spectroscopy.