Some aspects of data analysis of multi-angle dynamic light scattering

Citation
R. Buttgereit et al., Some aspects of data analysis of multi-angle dynamic light scattering, MACRO SYMP, 162, 2000, pp. 173-189
Citations number
17
Categorie Soggetti
Organic Chemistry/Polymer Science
Journal title
MACROMOLECULAR SYMPOSIA
ISSN journal
10221360 → ACNP
Volume
162
Year of publication
2000
Pages
173 - 189
Database
ISI
SICI code
1022-1360(200012)162:<173:SAODAO>2.0.ZU;2-0
Abstract
In dynamic light scattering the signal to noise ratio may become very low b ecause of short measurement times or low intensities. Then the analysis of the data becomes a central point and it is worthwhile to accept some numeri cal efforts and an increased calculation time caused by more sophisticated data analysis. In the following three aspects of an improved data analysis are discussed for multi-angle dynamic light scattering. In the first part of this paper, the influence of the correlation of the er rors of the autocorrelation time function is considered. With decreasing me asurement time the errors of the autocorrelation time function increase. Th e more the errors increase, however, the more important the error model bec omes. On the other hand, with increasing number of photons the correlations of the errors of the autocorrelation time function become important: The n on-diagonal elements of the covariance matrix of the data errors increase a nd may become of the order of the diagonal elements. In the second part the sensitivity of the nonlinear simultaneous multi-angl e regularization to aberrations in the experimental set-up is investigated. Therefore, far a given bimodal radii distribution and different scattering angles data were simulated taking into account the finite aperture of the detector as well as the laser light backscattered at the back of the cuvett e. This improved model is compared with the classical model, which neglects these aberrations in the experimental setup. Finally, the advantage of the simultaneous regularization method over avera ging over single-angle results is demonstrated. Estimating of the radii dis tribution from all multi-angle data at once leads to a higher solution comp ared to averaging over the single-angle results.