This EMR Book will be based in part upon existing articles from the EMR, providing the basic background material on multidimensional NMR, data processing methods and applications, and in part on new articles summarising the recent advances in technique and applications. The introductory chapter will aim to integrate the subsequent articles, to elide the gaps between them, to provide a coherent overview, and where possible to give the reader a clear perspective asto the relative utility and applicability of the competing methods. This volume sets out to explain and exemplify a range of new techniques that circumventthese limitations, drastically decreasing the minimum time needed to measure multidimensional spectra. The methods used fall into two basic classes: spatial multiplex techniques, which use pulsed field gradients to map temporal variation in an NMR dimension onto spatial position within the sample, allowing many time evolution points to be measured from a single initial radiofrequency excitation; and sparse sampling techniques, in which the number of data points used to map out the spin evolution in indirect dimensions is sharply reduced, the missing data points being supplied using sophisticated data processing. Spatial multiplex methods have their origins in the technique of echo planar imaging commonly used in fast magnetic resonance imaging (MRI) experiments, and can allow a complete 2D spectrum to be acquired in as little as a few seconds. Sparse sampling methods are more varied, including simple extrapolation of a truncated time evolution using linear prediction or the filter diagonalisation method, maximum entropy reconstruction of non-uniformly sampled data, projection-reconstruction, three-way decomposition, Hadamard encoding and the G-matrix Fourier transform method.Professor Gareth Morris Department of Chemistry, The University of Manchester
- ISBN: 978-0-470-77075-7
- Editorial: John Wiley & Sons
- Encuadernacion: Cartoné
- Páginas: 576
- Fecha Publicación: 16/04/2010
- Nº Volúmenes: 1
- Idioma: Inglés