Modelling particle disruption of an organic fine chemical compound using Lasentec focussed beam reflectance monitoring (FBRM) in agitated suspensions

Kougoulos, E.; Jones, Alan G.; Wood-Kaczmar, M.W.

doi:10.1016/j.powtec.2005.05.033

Cited by 25 publications

(22 citation statements)

References 8 publications

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“…A useful technique to measure dynamic solubility is the FBRM, as it can provide in situ monitoring of the changes in particle 'size' and 'counts', and unlike other forward or static light scattering techniques, the FBRM probe works particularly well with opaque or high concentration solutions (Barrett and Glennon, 1999;Heath et al ., 2002;Hu et al ., 2008;Kovalsky and Bushell, 2005;Kougoulos et al ., 2005b;Yu and Erickson, 2008). The applications of FBRM can be found in various fi elds, including crystallization (Doki et al ., 2004;Hermanto et al ., 2010;Kempkes et al ., 2008;Kougoulos et al ., 2005a;O'Sullivan et al ., 2003), granulation (Hu et al ., 2008;N ä rv ä nen et al ., 2009;N ä rv ä nen et al ., 2008;Tok et al ., 2008), fl occulation (Blanco et al ., 2002;Farrow et al ., 2000;Owen et al ., 2002;Swift et al ., 2004;Yoon and Deng, 2004) and dissolution (Sun et al ., 2009;Tajarobi et al ., 2009).…”

Section: Measurement Of Solubility Ratementioning

confidence: 99%

Food powder rehydration

Selomulya

Fang

2013

Handbook of Food Powders

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Section: Measurement Of Solubility Ratementioning

confidence: 99%

Food powder rehydration

Selomulya

Fang

2013

Handbook of Food Powders

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“…To overcome this problem, batch attrition experiments (Kougoulos et al, 2005c) were carried out. A suspension was agitated under zero supersaturation using different average energy dissipation rates.…”

Section: Cfd Compartmentalization Modeling For Crystallizers 1013mentioning

confidence: 99%

“…The change in the population density distribution is attributed to disruption effects only. The disruption rate can be expressed in terms of a disruption kernel (Kougoulos et al, 2005c), which depends on the local energy dissipation rate and the supersaturation as follows:…”

Section: Cfd Compartmentalization Modeling For Crystallizers 1013mentioning

confidence: 99%

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A Hybrid CFD Compartmentalization Modeling Framework for the Scaleup of Batch Cooling Crystallization Processes

Kougoulos

Jones

Wood-Kaczmar

2006

Chemical Engineering Communications

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Crystallizer design is often hindered by the lack of scaleup rules, hydrodynamic information, and predictive crystallization modeling tools. A hybrid CFD compartmentalization batch cooling crystallizer model is proposed to take into account localized mixing, heat transfer, and fluid hydrodynamics, combined with key process engineering information obtained on a laboratory scale. The compartments were identified using CFD simulations based on the crystallizer geometry and operating conditions. The population, mass, concentration, and energy balance of each compartment is modeled separately as a well-mixed MSMPR unit with input and output streams. The software gPROMS (Process Systems Enterprise Limited) is a process-modeling tool that can facilitate compartmental modeling and will be used for the prediction of the crystallization behavior upon scaleup.

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“…It does not require sampling that could affect the actual particle size distribution due to breakdown or aggregation. FBRM can be used to determine and monitor the chord length distribution (CLD), mean particle size and chord count of microparticles in real time, which are affected by the geometry, size and number of particles under analysis . Additionally, the measurement principle of FBRM differs fundamentally from that of other established particle sizing methods.…”

Section: Introductionmentioning

confidence: 99%

Effect of solvent type on preparation of ethyl cellulose microparticles by solvent evaporation method with double emulsion system using focused beam reflectance measurement

Muhaimin

Bodmeier

2017

Polym. Int

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The purpose of this study was to investigate the effect of solvent type on the solidification rate of ethyl cellulose (EC) microparticles and particle size/distribution of emulsion droplets/hardened microparticles during the solvent evaporation process using focused beam reflectance measurement (FBRM). EC microparticles were prepared with a water-in-oil-in-water solvent evaporation method using various solvents, including dichloromethane, dichloromethane-methanol (1:1), ethyl acetate and chloroform. The particle size/distribution of the emulsion droplets/hardened microparticles was monitored using FBRM. The morphology of EC microparticles was characterized using scanning electron microscopy (SEM). The transformation of the emulsion droplets into solid microparticles for all solvents occurred within the first 10-90 min. The square weighted mean chord length of EC microparticles prepared using chloroform was smallest, but the chord count was not the highest. The chord length distribution (CLD) measured by FBRM showed that a larger mean particle size gave longer CLD and a lower peak of particle number. SEM data revealed that the morphology of microparticles was influenced by the type of solvent. FBRM can be employed for online monitoring of the shift in the microparticle CLD and detect transformation of emulsion droplets into solid microparticles during the solvent evaporation process. The microparticle CLD and transformation process were strongly influenced by solvent type.

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Modelling particle disruption of an organic fine chemical compound using Lasentec focussed beam reflectance monitoring (FBRM) in agitated suspensions

Cited by 25 publications

References 8 publications

Food powder rehydration

Food powder rehydration

A Hybrid CFD Compartmentalization Modeling Framework for the Scaleup of Batch Cooling Crystallization Processes

Effect of solvent type on preparation of ethyl cellulose microparticles by solvent evaporation method with double emulsion system using focused beam reflectance measurement

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