INGAR   05399
INSTITUTO DE DESARROLLO Y DISEÑO
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:
GEORGINA STEGMAYER,; GONZALES, DIEGO; LUIS GUGLIOTTA,; CHIOTTI, OMAR; JORGE VEGA,
Revista:
LATIN AMERICAN APPLIED RESEARCH
Referencias:
Año: 2008
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
normal-logarithmic 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 ill-conditioned inverse problems