Latex particle size distribution by dynamic light scattering: novel data processing for multiangle measurements

• Published in: Journal of colloid and interface science Vol. 261; no. 1; pp. 74 - 81
• Main Authors: Vega, Jorge R., Gugliotta, Luis M., Gonzalez, Verónica D.G., Meira, Gregorio R.
• Format: Journal Article
• Language: English
• Published: San Diego, CA Elsevier Inc 01.05.2003; Elsevier
• Subjects: Applied sciences; DLS; Exact sciences and technology; Inverse problem; Multiangle; Organic polymers; Physicochemistry of polymers; Polymer latex; Properties and characterization; PSD; Surface properties; PSD; DLS; Multiangle; Polymer latex; Inverse problem; Light scattering; Least squares problem; Theoretical study; Polymer; Data processing; Latex; Particle size distribution; Weighting; Dynamical scattering; Measurement method
• ISSN: 0021-9797; 1095-7103; 1095-7103
• DOI: 10.1016/S0021-9797(03)00040-7

Multiangle dynamic light scattering (DLS) provides a better estimate of particle size distributions (PSD) than single-angle DLS. However, multiangle data treatment requires appropriate weighting of each autocorrelation measurement prior to calculation of the PSD. The weighting coefficients may be directly obtained from (i) the autocorrelation baselines or (ii) independent measurement of the average light intensity by elastic light scattering. However, the propagation of errors associated with such procedures may intolerably corrupt the PSD estimate. In this work, an alternative recursive least-squares calculation is proposed that estimates the weighting coefficients on the basis of the complete autocorrelation measurement. The method was validated through a numerical example that simulates the analysis of a polystyrene latex with a bimodal PSD and with “measurements” taken at 10 detection angles. The ill-conditioned nature of the problem determines that the “true” PSD cannot be recovered, even in the absence of errors. A sensitivity analysis was carried out to determine the effect of errors in the weighting coefficients on the PSD recoveries.