Meeting Banner
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.

This abstract and the presentation materials are available to members only; a login is required.

Join Here