Enhanced detection of crowded NMR peaks using longitudinal multi-spin order for chemical analysis

High-resolution one-dimensional (1D) nuclear magnetic resonance (NMR) spectroscopy plays a critical role in enabling the detail analysis of complex samples, precise determination of molecular structures, and investigation of molecular interactions. However, challenges arise when two spins exhibit very similar chemical shifts, potentially interfering with signal separation. Identifying low-concentration components in complex mixtures with overlapping spectral features becomes even more difficult. Therefore, addressing the challenge of extracting low-intensity peaks from crowded or overlapping NMR spectra is of urgent importance.

We introduce double-quantum-filtered longitudinal multiple-spin orders (DQF-LMO) method to extract low-intensity peaks from crowded or overlapping NMR spectra. This approach enables the acquisition of sparse 1D spectra that isolate a single spin coupled to an excited spin, enhancing sensitivity and resolution. Building on this approach, we further develop the DQF-LMO-TOCSY method, incorporating isotropic mixing from the TOCSY technique to detect all spins within a particular spin system. We demonstrate the practical utility of these techniques by applying them to real-world samples, including orange juice and functional beverages, where key compounds such as sucrose, glucose, citric acid, and ethanol were successfully isolated and identified. Additionally, the accurate quantification of glutamine in mixtures with glutamate highlights the capability of these methods to resolve closely overlapping spectra features.

These innovations offer a more efficient and precise approach to molecular characterization, enabling better chemical analysis in complex environments. Our work paves the way for enhanced NMR-based chemical analysis and component identification, positioning NMR as a crucial tool for modern analytical chemistry.