Dynamic nuclear polarization at 7 Tesla to enable and enhance the study of chemical structures and surfaces

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With this award, the Chemical Measurement and Imaging Program in the Division of Chemistry is supporting Professor Song-I Han at the University of California-Santa Barbara to pursue the development of advanced instrumentation and methodologies to exploit solid-state dynamic nuclear polarization (ssDNP) enhancement at 7 Tesla and liquid helium temperatures to significantly enhance the nuclear magnetic resonance (NMR) signal. The proposed research activities is desigend to provide up to 4 to 5 orders of magnitudes of NMR signal enhancement. If successful, this new apparatus will enable characterization of interfaces and surfaces in a way not feasible before. Consequently, the largest impact of the proposed research lies in the characterization of chemical systems and materials of interest to society; namley, catalysts and energy-related and/or biocompatible materials. The proposed research also offers interdisciplinary training opportunities to next generation graduate and undergraduate students by providing them with hands-on experience in technology and hardware development from the ground up.The overarching research goal is to advance ssDNP-enhanced NMR as a chemical characterization tool, with the focus on resolving local signatures of nanometer-scale domains and solid surfaces, where chemical processes occur and that are critical for material function. The intellectual merit of the proposed work is to address fundamental roadblocks in and mechanisms of ssDNP performance via studies of the temperature and microwave power dependence of DNP enhancements, frequency profiles and build-up time curves, as well as electron and nuclear spin relaxation times. Contemporary chemical systems from nanostructured hydrogels, mesoporous catalysts to supported catalysts will be studied, with the aim of selectively characterizing surface signatures and spatially heterogeneous solute/solvent composition. The prospect for DNP to transform NMR from offering atomistic details, but averaged over the entire sample into a surface sensitive and selective tool, is promising.