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Diffusion-ordered spectroscopy (DOSY) is an important tool in NMR mixture analysis that has found use in most areas of chemistry, including organic synthesis, drug discovery, and supramolecular chemistry. Typically the aim is to disentangle the overlaid, and often overlapped, NMR spectra of individual mixture components and/or to obtain size and interaction information from their respective diffusion coefficients. The most common processing method, high-resolution DOSY, breaks down where component spectra overlap; here multivariate methods can be very effective, but only for small numbers (2-5) of components. In this study, we present a hybrid method, local covariance order DOSY (LOCODOSY), that breaks a spectral data set into suitable windows and analyzes each individually before combining the results. This approach uses a multivariate algorithm (e.g., SCORE or DECRA) to resolve only a small number of components in any given window. Because a small spectral region should contain signals from only a few components, even when the spectrum as a whole contains many more, the total number of resolvable chemical components rises dramatically. It is demonstrated here that complete resolution of component spectra can be achieved for mixtures that are much more complex than could previously be analyzed with DOSY. Thus, LOCODOSY is a powerful, flexible tool for processing NMR diffusion data of complex mixtures. |
