INTEC   05402
INSTITUTO DE DESARROLLO TECNOLOGICO PARA LA INDUSTRIA QUIMICA
Unidad Ejecutora - UE
artículos
Título:
Estimation of the Particle Size distribution of a Dilute Latex from Combined Elastic and Dynamic Light Scattering Measurements. A Method based on Neural Networks
Autor/es:
STEGMAYER, G. S.; GONZALEZ, V. D. G.; GUGLIOTTA, L. M.; CHIOTTI, O.; VEGA, J. R.
Revista:
LATIN AMERICAN APPLIED RESEARCH
Editorial:
PLAPIQUI(UNS-CONICET)
Referencias:
Año: 2009 vol. 39 p. 261 - 266
ISSN:
0327-0793
Resumen:
A method for estimating the particle
size distribution (PSD) of a dilute latex from light
scattering measurements is presented. The method
utilizes a general regression neural network
(GRNN), that estimates the PSD from 2 independent
sets of measurements carried out at several angles:
(i) light intensity measurements, by elastic light scattering
(ELS); and (ii) average diameters measurements,
by dynamic light scattering. The GRNN was
trained with measurements simulated on the basis of
typical asymmetric PSDs (unimodal normallogarithmic
distributions of variable mean diameters
and variances). First, the ability of the method was
tested on the basis of two synthetic examples. Then,
the obtained GRNN was used for estimating the PSD
of a narrow polystyrene (PS) latex standard of
nominal diameter 111 nm. The standard was also
characterized by 2 independent techniques: capillary
hydrodynamic fractionation, and transmission electron
microscopy (TEM). The PSD predicted by the
GRNN resulted close to that obtained by TEM. The
estimated PSDs were better than those obtained
through standard numerical techniques for illconditioned
inverse problems.