Characterization of particle size distribution in slurries using ultrasonic attenuation spectroscopy: Addressing challenges of unknown physical properties

Ultrasonic attenuation spectroscopy (UAS) has many advantages in online in-process characterization of particle size distribution (PSD) slurries. It can be applied to systems with relatively high solid concentration and wide range from nanometres millimetres sized particles. The model used by a UAS instrument estimate the PSD an spectrum requires some physical properties both liquid phases known. For instance, most popular model, Epstein–Carhart Allegra–Hawley (ECAH) fourteen properties. Therefore, applications where all or required are unknown difficult measure, such as crystallization, pose major challenge its use. In this work, procedure for estimating is proposed. This done iteratively learning minimise difference between measured spectra that predicted ECAH model. One main challenges presence multiple local minima but these eliminated combination global optimisation algorithm, use distributions concentrations. was validated using Silica Titania standard reference materials, estimation relevant saturated aqueous solution SrCl2.6H2O Sr(OH)2.8H2O. thus obtained acoustic monitoring real-time evolution during batch cooling crystallization water.