Particle sizing by dynamic light scattering: non-linear cumulant analysis.

Area of Science:

• Colloid and Surface Science
• Materials Science
• Photonics and Optics

Background:

• Dynamic light scattering (DLS) is a key technique for particle sizing.
• The cumulant method analyzes DLS data by fitting the time correlation function to moments of the diffusion coefficient distribution.
• Previous work suggests non-linear analysis offers advantages over linear methods despite increased computational demands.

Purpose of the Study:

• To explore the potential and limitations of cumulant methods in particle sizing.
• To compare linear and non-linear analysis approaches for DLS data.
• To assess the accuracy of determining diffusion constant distribution parameters with noisy data.

Main Methods:

• Utilized computer-generated dynamic light scattering data with controlled noise.
• Applied both linear least-squares and non-linear iterative cumulant analysis methods.
• Explicitly set the parameters of the diffusion constant distribution for validation.

Main Results:

• Non-linear cumulant analysis is computationally feasible and robust with modern computing power.
• Accurate determination of the mean and variance of diffusion constants is achievable for distribution widths up to approximately 0.6.
• Obtaining meaningful higher moments of the diffusion constant distribution is unlikely with current cumulant methods.

Conclusions:

• Non-linear cumulant analysis is a reliable method for particle sizing using DLS data.
• The method is effective for characterizing the mean and variance of diffusion coefficients, even with moderate distribution widths.
• Limitations exist for accurately retrieving higher-order moments of the diffusion coefficient distribution.