Dissect and Divide: Putting NMR Spectra of Mixtures under the Knife
Dissect and Divide: Putting NMR Spectra of Mixtures under the Knife
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DOI：
10.1021/jacs.8b13290
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发表时间：
2019-04-10
影响因子：
15
通讯作者：
Nilsson, Mathias
中科院分区：
文献类型：
--
作者：
Dal Poggetto, Guilherme;Castanar, Laura;Nilsson, Mathias
复杂混合物的高效、实用和无损分析在化学的许多分支中至关重要。在这里，我们提出了一种新类型的NMR实验，允许非常具有挑战性的完整的混合物，其中可以提取单个组分的子光谱时，其他NMR手段失败的情况下，一个单一的，完整的，静态的（恒定的组合物）样品的研究。我们展示了新的方法，SCALPEL（光谱成分采集本地化PARAFAC提取线性成分），在天然发酵饮料，啤酒和其他碳水化合物的混合物，获得个人的碳水化合物组分的子光谱。这种新的NMR实验是基于解剖光谱而不是样品，使用定制的脉冲序列来生成适用于强大的张量分解方法的数据，以允许逐步分析高度复杂的光谱，一次一小部分。它显然有潜力解决当前方法无法解决的问题。
Efficient, practical, and nondestructive analysis of complex mixtures is vital in many branches of chemistry. Here we present a new type of NMR experiment that allows the study of very challenging intact mixtures, in which subspectra of individual components can be extracted when other NMR means fail, for the case of a single, intact, static (constant composition) sample. We demonstrate the new approach, SCALPEL (Spectral Component Acquisition by Localized PARAFAC Extraction of Linear components), on a natural fermented beverage, beer, and other carbohydrate mixtures, obtaining individual carbohydrate component subspectra. This new class of NMR experiment is based on dissecting the spectrum rather than the sample, using pulse sequences tailored to generate data suitable for powerful tensor decomposition methods to allow highly complex spectra to be analyzed stepwise, one small section at a time. It has the clear potential to attack problems beyond the reach of current methods.