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Agglomeration of Needle-like Crystals in Suspension: I. Measurements

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journal contribution
posted on 2015-04-01, 00:00 authored by David R. Ochsenbein, Thomas Vetter, Stefan Schorsch, Manfred Morari, Marco Mazzotti
A technique for the detection and measurement of the agglomeration of needle-like particles is presented. A novel image analysis routine, based on a supervised machine learning strategy, is used to identify agglomerates that are subsequently characterized by their volume. Through repeated measurement of a large number of agglomerates, a 1D particle size distribution of agglomerates is reconstructed. Concurrently, established tools are used to characterize needle-like primary crystals, whose shape is described by cylinders and whose population can be described by a separate two-dimensional particle size and shape distribution. The performance of the classifier is evaluated, and the reproducibility of the measurement is demonstrated for the case of β l-glutamic acid. For the same system, the agglomeration behavior is studied for varying operating conditions, and general trends are analyzed.

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