Size Distribution of Nanoparticles by Dynamic Light Scattering. Comparison of Bayesian and Tikhonov Inversion Methods

CLEMENTI, L. A.; VEGA, J.R.; ORLANDE, H. R. B.; GUGLIOTTA, L.M.

INVERSE PROBLEMS IN SCIENCE AND ENGINEERING

TAYLOR & FRANCIS LTD

Año: 2011 vol. 20 p. 25 - 32

1741-5977

The diameter distribution of nanometric particles is estimated from multiangle dynamic light scattering (MDLS) measurements by solving an ill-conditioned nonlinear inverse problem through Tikhonov and Bayesian methods. For both methods, the data inputs are the angle-dependent average diameters of the particle size distribution (PSD), which are in turn calculated from the measured autocorrelation functions of the light intensity scattered by a dilute sample of particles. The performance of both methods were tested on the basis of: (i) three simulated polymer latexes that involved PSDs of different shapes, widths, and diameter ranges; and (ii) two real polystyrene latexes obtained by mixing two well-characterized standards of narrow PSDs (of known nominal diameters and standard deviations). For PSDs exhibiting highly-asymmetric modes, or modes of quite different relative concentrations, the Bayesian method produced PSD estimates better than those obtained through Tikhonov regularization.