Macromolecular properties from light-scattering experimental data using linear inverse problem theory

被引:5
作者
Virtuoso, Luciano S.
Sebastiao, Rita C. O.
Braga, Joao P. [1 ]
Da Silva, Luis H. M.
机构
[1] Univ Fed Minas Gerais, ICEx, Dept Quim, Belo Horizonte, MG, Brazil
[2] Ctr Univ Caratinga, FUNEC, Dept Quim, Caratinga, MG, Brazil
[3] Univ Fed Vicosa, Dept Quim, Vicosa, MG, Brazil
关键词
light scattering; Hopfield neural network; inverse problem;
D O I
10.1002/qua.21036
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The inversion of the temporal correlation function in dynamic light-scattering experimental data for polyethylene oxide + H2O + NaCl is treated in the present work. The relaxation time distribution function for this ill-posed problem is obtained by a recurrent neural network, using analytical inverse Laplace transform as the initial condition. Diffusion coefficient and particle size distributions can also be retrieved from this relaxation time distribution, providing important information for the experimental researcher. (C) 2006 Wiley Periodicals, Inc.
引用
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页码:2731 / 2736
页数:6
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