Filterability prediction of needle-like crystals based on particle size and shape distribution data
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Author (Corporation)
Publication date
18.03.2019
Type of student thesis
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01A - Journal article
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Parent work
Separation and Purification Technology
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Volume
211
Issue / Number
Pages / Duration
768-781
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Publisher / Publishing institution
Elsevier
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Abstract
The isolation and further treatment of particles generated in a crystallization process is dependent on their size and shape. The work presented here analyzes the filtration performance of needle-like particles, which often exhibit long filtration times or high retention of mother liquor. The size and shape of populations of l-Glutamic Acid and d-Mannitol particles are measured using an automated image analysis approach (as well as a standard light scattering method), and their associated cake resistance is determined in pressure filtration experiments. Using a partial least squares regression analysis we develop a model of the process and show that relative cake resistances can be predicted if the particle size distributions are accurately known. Furthermore, we show that the statistical model calibrated on a single compound (either of those used for this study), can be exploited to predict the relative cake resistances of another compound.
Keywords
Filtration, Needle-like crystals, Particle size and shape
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ISSN
1383-5866
1873-3794
1873-3794
Language
English
Created during FHNW affiliation
No
Strategic action fields FHNW
Publication status
Published
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Peer review of the complete publication
Open access category
Hybrid
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Citation
Perini, G., Salvatori, F., Ochsenbein, D. R., Mazzotti, M., & Vetter, T. (2019). Filterability prediction of needle-like crystals based on particle size and shape distribution data. Separation and Purification Technology, 211, 768–781. https://doi.org/10.1016/j.seppur.2018.10.042