Post-processing noise reduction via all-photon recording in dynamic light scattering

Abstract

Dynamic light scattering (DLS) is widely used for the characterization of the size distributions of polymers and nanoparticles in dispersions. The time correlation function of the scattered light intensity can be calculated from the intensity fluctuation with time and converted into the size of the scatterers. It has been difficult to apply DLS to a dispersion containing large pollutant particles, however, because the pollutants moving in the dispersion can give rise to intense noise signals from time to time during data acquisition. In conventional DLS, this type of noise renders the entire measurement useless. Here we report a novel software-based DLS system in which the arrival times of all the scattered photons are recorded using a time-to-digital converter, and the time correlation function is calculated exclusively from the uncontaminated parts of the data in post-processing. We demonstrate the validity of this noise reduction scheme by evaluating the silica nanoparticle size in a dispersion containing a small number of micrometer-sized PMMA particles as a model contaminant.

Keywords

• dynamic light scattering
• noise reduction
• nanoparticles
• particle size determination
• all-photon recording