Measurement of agglomeration during crystallization: Is the differentiation of aggregates and agglomerates via ultrasonic irradiation possible?

An online measurement setup is presented to measure the agglomeration processes occurring during batch cooling crystallization of adipic acid from aqueous solution. Quantification of agglomeration is enabled by image analysis and particle classification using a highly accurate artificial neural network. This model system has a strong tendency to agglomerate during crystallization and therefore a strong tendency to aggregate, too. Aggregates and agglomerates are visually indistinguishable though and, therefore, falsify the measurement by aggregates superimposing agglomerates. To counteract this phenomenon during measurement, it is tested whether ultrasonic irradiation can be used to disaggregate the particles before being measured. It was found that ultrasonic treatment of the sample at various frequencies and input powers resulted in particle breakage (low frequency, high input power) or disaggregation of very large particles that would lead to clogging of the setup. Complete disaggregation of the sample was not feasible as the frequency and input power variation of the ultrasonic setup has shown. However, it was concluded that continuous treatment with ultrasonic irradiation might be a way to reduce impurity inclusions within the agglomerates due to the continuous destruction of the particles.