Abstract #2400

Artificial intelligence for high-resolution nuclear MRS under inhomogeneous magnetic fields

Qiu Wenqi¹, Wei Zhiliang¹, Ye Qimiao¹, Chen Youhe², Lin Yulan¹, and Chen Zhong¹

¹Department of Electronic Engineering, Xiamen University, Xiamen, China, People's Republic of, ²Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen, China, People's Republic of

High-resolution multi-dimensional nuclear magnetic resonance (NMR) spectroscopy serves as an irreplaceable and versatile tool in various chemical investigations. In this study, a method based on the concept of partial homogeneity is developed to offer two-dimensional (2D) high-resolution NMR spectra under inhomogeneous fields. Oscillating gradients are exerted to encode the high-resolution information, and a field-inhomogeneity correction algorithm based on pattern recognition is designed to recover high-resolution spectra. The proposed method improves performances of 2D NMR spectroscopy under inhomogeneous fields without increasing the experimental duration or significant loss in sensitivity, and thus may open important perspectives for studies of inhomogeneous chemical systems.

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