Lin Yulan, Liang Wei, Chen Longxiang, Liu Chaoxing, Cui Mengqi, Chen Hongrong, Chen Zhong
Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, State Key Laboratory of Physical Chemistry of Solid Surfaces, Xiamen University, Xiamen, 361005, China.
Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, State Key Laboratory of Physical Chemistry of Solid Surfaces, Xiamen University, Xiamen, 361005, China.
Anal Chim Acta. 2025 Oct 15;1371:344429. doi: 10.1016/j.aca.2025.344429. Epub 2025 Jul 14.
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.
高分辨率一维（1D）核磁共振（NMR）光谱在对复杂样品进行详细分析、精确确定分子结构以及研究分子间相互作用方面发挥着关键作用。然而，当两个自旋具有非常相似的化学位移时，就会出现挑战，这可能会干扰信号分离。在具有重叠光谱特征的复杂混合物中识别低浓度成分变得更加困难。因此，应对从拥挤或重叠的NMR光谱中提取低强度峰这一挑战至关重要。
我们引入双量子滤波纵向多自旋序（DQF-LMO）方法，以从拥挤或重叠的NMR光谱中提取低强度峰。这种方法能够获取稀疏的一维光谱，该光谱可分离与一个激发自旋耦合的单个自旋，从而提高灵敏度和分辨率。在此方法的基础上，我们进一步开发了DQF-LMO-TOCSY方法，该方法结合了来自TOCSY技术的各向同性混合，以检测特定自旋系统内的所有自旋。我们通过将这些技术应用于实际样品（包括橙汁和功能性饮料）来证明其实际效用，其中蔗糖、葡萄糖、柠檬酸和乙醇等关键化合物被成功分离和鉴定。此外，对与谷氨酸混合的谷氨酰胺进行准确定量，突出了这些方法解析紧密重叠光谱特征的能力。
这些创新为分子表征提供了一种更高效、精确的方法，能够在复杂环境中进行更好的化学分析。我们的工作为基于NMR的化学分析和成分鉴定的改进铺平了道路，使NMR成为现代分析化学的关键工具。
