Daisuke Sasakura & Sho Kimura
Abstract
The dispersion of granulated particles in a liquid is an important process that significantly affects the quality, stability, and functionality of industrial products. It is also a phenomenon of interest in fundamental science. Changes in the particle size distribution (PSD) in a suspension of granules are widely used as indicators of the progression of various dispersion behaviors. In this study, we used the time-domain laser diffraction method to observe dispersion in a granular suspension. We then applied principal component analysis (PCA) to analyze the measurement data, which were obtained as a time series, and extract the characteristic changes in particle size during the dispersion. By extracting the principal components from multidimensional data using PCA, we could characterize the dispersion-phase behavior and separate the peak components, which could not be captured by conventional analyses using representative values such as percentiles. In particular, by applying the PCA method—commonly used in spectroscopy—to PSD data, we obtained new insights suggesting the presence of complex dispersion pathways and intermediates. The findings of this study advance our understanding of granule dispersion dynamics and help establish a new framework for analyzing particle dispersion processes, which can assist in particle design, formulation optimization, and extending scientific knowledge in this area.
Keywords:
Particle size analysis, Granules, Dispersion, Principal component analysis, Laser diffraction