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Trust-Region Algorithm for the Inversion of Molecular Diffusion NMR Data
journal contribution
posted on 2014-01-07, 00:00 authored by Kaipin Xu, Shanmin ZhangDiffusion NMR experiments are very
useful in studying structural and dynamical properties of
molecules and in sorting out components from mixtures. A number of
numerical approaches have been developed for the processing of diffusion
NMR data. In this paper, numerical problems of the direct regularization
methods such as CONTIN, MaxEnt, and the newly proposed ITAMeD approach
are illustrated by analyzing simulated and experimental data. It allows
us to further develop a new method to calculate the distribution of
diffusion coefficients. Therefore, we present here an iterative regularization
method based on the Trust-Region Algorithm for the Inversion (TRAIn)
of molecular diffusion NMR data. It is demonstrated in this paper
that our approach overcomes major numerical difficulties of the direct
regularization methods mentioned above. Besides, this method reconstructs
more reliable diffusion coefficient distributions, especially for
real world samples of which the diffusion coefficients are nonsymmetrically
distributed.