超强磁场下高分辨核磁共振新方法及其典型应用

The research on the physical property and process mechanism under ultrahigh magnetic field have become one of the most important topics in chemistry, biology, physics and material sciences. However, there are still large unknowns that how the concomitant non-linear effects of nuclear spins affect the spin resonances, thereafter restraining the ultrahigh-field high-resolution spin-resonance spectroscopy and imaging from wider applications. Meanwhile, under ultrahigh magnetic fields, the magnetic-field instability and inhomogeneity, anabatic transversal relaxation and high radiofrequency-energy accumulation arise new challenges to the spin-resonance spectroscopy and imaging. This project covers the following studies: 1) Exploring mechanisms of concomitant physical phenomena under ultrahigh magnetic fields and providing effective methods to control these non-linear effects; 2) Designing high-resolution one- and multi-dimensional spin-resonance spectroscopy for ultrahigh-field applications; 3) Proposing novel spatiotemporal-encoding MRI methods with low energy accumulations and less image distortions; 4) Setting up image and spectroscopy reconstruction models and optimization algorithms that exploit the structural sparsity and low rank of the physically excited resonance signals; 5) Applying designed methods to typical systems, e.g. heterogeneous in-situ chemical reactions, in-cell macromolecule elucidations and analyses of solid-state materials with quadrupolar nuclei; establishing a real-time, in-situ and in-vivo spin-resonance methodological system; realizing high-sensitivity and high-resolution analyses of chemical components and structures.

超强磁场下物质性质和过程机制的研究已成为化学、生物医学、物理和材料科学领域的前沿课题。本项目重点研究超强磁场下NMR自旋动力学中非线性效应引起的新的物理现象，开发超强磁场下高分辨磁共振波谱及成像新方法。通过发展和完善非线性效应的数理模型和理论表述，研究超强磁场下的自旋不稳定性和混沌机制，设计不同的反馈控制实现对混沌效应的抑制或增强。基于分子间多量子相干及新型时空编码技术，发展具有低射频能量聚积优点的能够在不均匀不稳定磁场下快速获得高分辨NMR波谱及成像的新方法，建立一套基于NMR信号特点的结构化稀疏和低秩信号模型与最优化算法，将NMR技术拓展到超强磁场下以生物组织和微小活体、非均相原位化学反应、含四极核固体材料等为代表的典型生物化学体系的研究，实现高分辨率、高灵敏度的化学组成和结构分析，从而实现NMR更深层次更广泛的应用。