Agglomeration of needle-like crystals in suspension: I. Measurements
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Publication date
18.03.2015
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01A - Journal article
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Crystal Growth & Design
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15
Issue / Number
4
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American Chemical Society
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Abstract
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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1528-7483
1528-7505
1528-7505
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English
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No
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Published
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Peer review of the complete publication
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Green
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Ochsenbein, D. R., Vetter, T., Schorsch, S., Morari, M., & Mazzotti, M. (2015). Agglomeration of needle-like crystals in suspension: I. Measurements. Crystal Growth & Design, 15(4). https://doi.org/10.1021/acs.cgd.5b00094