Please use this identifier to cite or link to this item: https://doi.org/10.1021/ac0491814
Title: Development of 2D band-target entropy minimization and application to the deconvolution of multicomponent 2D nuclear magnetic resonance spectra
Authors: Guo, L.
Wiesmath, A.
Sprenger, P.
Garland, M. 
Issue Date: 15-Mar-2005
Source: Guo, L., Wiesmath, A., Sprenger, P., Garland, M. (2005-03-15). Development of 2D band-target entropy minimization and application to the deconvolution of multicomponent 2D nuclear magnetic resonance spectra. Analytical Chemistry 77 (6) : 1655-1662. ScholarBank@NUS Repository. https://doi.org/10.1021/ac0491814
Abstract: Spectral reconstruction from multicomponent spectroscopic data is the frequent primary goal in chemical system identification and exploratory chemometric studies. Various methods and techniques have been reported in the literature. However, few algorithms/methods have been devised for spectral recovery without the use of any a priori information. In the present studies, a higher dimensional entropy minimization method based on the BTEM algorithm (Widjaja, E.; Li, C.; Garland, M. Organometallics 2002, 21, 1991-1997.) and related techniques were extended to large-scale arrays, namely, 2D NMR spectroscopy. The performance of this novel method had been successfully verified on various real experimental mixture spectra from a series of randomized 2D NMR mixtures (COSY NMR and HSQC NMR). With the new algorithm and raw multicomponent NMR alone, it was possible to reconstruct the pure spectroscopic patterns and calculate the relative concentration of each species without recourse to any libraries or any other a priori information. The potential advantages of this novel algorithm and its implications for general chemical system identification of unknown mixtures are discussed. © 2005 American Chemical Society.
Source Title: Analytical Chemistry
URI: http://scholarbank.nus.edu.sg/handle/10635/63719
ISSN: 00032700
DOI: 10.1021/ac0491814
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