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Crystallization Development Physical Sciences  December 2011
Crystallization - one of the oldest unit ops….  Crystallization of sugar - Duhamel du Monceau's "Art de rafiner le sucre" 1764 … .and still one of the most challenging
Crystallization challenges Purity Yield CSD Solids handling SLS Polymorphism Crystal shape Scale-up Solvation Encrustation
Consider the Whole Process Preferred Form Desired properties Solid liquid separation Issues: Purity Yield Particle size Polymorph Drying Issues: Solvent removal Polymorph Particle size Agglomeration Lumping Breakage Micronise Issues: Form change De-lumping Particle size reduction Provides consistency Crystallization Issues: Supersaturation Nucleation Polymorph Purity Yield Particle size Habit Final Product Preferred Form Desired properties
Case studies: manufacturing ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Background ,[object Object],[object Object],[object Object],Monohydrate Trihydrate Anhydrate
Experimental - measure solubility and metastable zone width Temperature cycling experiments indicate wide MSZW ( ~30°C) This provides larger space for experimental design
MSZW
Solubility & MSZW - issues Temperature C Concentration Wide metastable zone, growth requires high supersaturation Slow growth and  desupersaturation High end point solubility
Instrumentation Lasentec Focussed Beam Reflectance Measurement  (FBRM)  and Particle Video Microscope  (PVM)  used for initial reactor-scale Screening Experiments ,[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object]
Quantifying the Effect of Seeding Temperature Unweighted Data Weighted Data Seeding at 20 ° C yields an average size ~30% smaller than seeding at 30°C. At 20 ° C more smaller crystals than at 30°C. Unweighted data emphasizes the behaviour of the smaller particles.  Weighted data emphasized the behaviour of larger particles.
Weighted vs. Unweighted Distributions  ,[object Object],[object Object],[object Object],FBRM ® No Weight FBRM ® Square Weight ,[object Object],[object Object],This simple example of a population of cubes helps highlight what the number and volume distribution of the particle system looks like.
Visualising the Effect of Seeding Temperature PVM images. The product consists of agglomerated crystals.  Seeding at 30 ° C crystals & agglomerates are larger than seeding at 20 ° C.
Quantifying Rate and Degree of Change Track the rate & degree of change to particles as they occur in the process. Can be used to directly compare crystal behaviour. #/sec <10 μ m #/sec 10-50 μ m Seeding at 20 ° C rapid increase in small crystals over 1 one hour followed by gradual increase thereafter. Seeding at 30 ° C an initial modest increase in small crystals, and then a gradual increase over a seven hour period.
Comparing Seeding Events Weighted Data Seeding at 30 ° C, much greater degree of growth & agglomeration. Weighted Data Weighted distributions show changes to crystal size and number for the period after seeding and cooling to 2°C.
Visualising Seeding Events at 20 °C Weighted Data Seeding at 20 ° C the particles are small agglomerates. During the cool to 2 ° C visible increase in the number & size of the agglomerates.
Visualising Seeding Events at 30 °C Weighted Data Compared to seeding at 20 ° C, the initial hold after seeding at 30 ° C results in modest nucleation and growth.  However, at the end of the cooling to 2 ° C, the agglomerated crystals are already very large.
Quantifying the Effect of Attrition Unweighted Data The population of crystals smaller than 50 μ m has increased by about 35%. However, there is very little effect on the large crystal population – suggesting that the fine particles are small crystals that were attached to the surfaces of the agglomerates, but have now become detached due to the higher agitation. The effect of increased agitation is very much less than the effect of changing the seeding temperature.
Visualising The Effect of Attrition Unweighted Data These PVM images show the crystal system before and after the increase in agitator speed. After 120 minutes of higher speed agitation a greater number of very small particles, very little change to the large crystals and agglomerates.
[object Object],[object Object],[object Object],Conclusion

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Cryst Dev Case Study Dec 2011

  • 1. Crystallization Development Physical Sciences December 2011
  • 2. Crystallization - one of the oldest unit ops…. Crystallization of sugar - Duhamel du Monceau's &quot;Art de rafiner le sucre&quot; 1764 … .and still one of the most challenging
  • 3. Crystallization challenges Purity Yield CSD Solids handling SLS Polymorphism Crystal shape Scale-up Solvation Encrustation
  • 4. Consider the Whole Process Preferred Form Desired properties Solid liquid separation Issues: Purity Yield Particle size Polymorph Drying Issues: Solvent removal Polymorph Particle size Agglomeration Lumping Breakage Micronise Issues: Form change De-lumping Particle size reduction Provides consistency Crystallization Issues: Supersaturation Nucleation Polymorph Purity Yield Particle size Habit Final Product Preferred Form Desired properties
  • 5.
  • 6.
  • 7. Experimental - measure solubility and metastable zone width Temperature cycling experiments indicate wide MSZW ( ~30°C) This provides larger space for experimental design
  • 9. Solubility & MSZW - issues Temperature C Concentration Wide metastable zone, growth requires high supersaturation Slow growth and desupersaturation High end point solubility
  • 10.
  • 11.
  • 12. Quantifying the Effect of Seeding Temperature Unweighted Data Weighted Data Seeding at 20 ° C yields an average size ~30% smaller than seeding at 30°C. At 20 ° C more smaller crystals than at 30°C. Unweighted data emphasizes the behaviour of the smaller particles. Weighted data emphasized the behaviour of larger particles.
  • 13.
  • 14. Visualising the Effect of Seeding Temperature PVM images. The product consists of agglomerated crystals. Seeding at 30 ° C crystals & agglomerates are larger than seeding at 20 ° C.
  • 15. Quantifying Rate and Degree of Change Track the rate & degree of change to particles as they occur in the process. Can be used to directly compare crystal behaviour. #/sec <10 μ m #/sec 10-50 μ m Seeding at 20 ° C rapid increase in small crystals over 1 one hour followed by gradual increase thereafter. Seeding at 30 ° C an initial modest increase in small crystals, and then a gradual increase over a seven hour period.
  • 16. Comparing Seeding Events Weighted Data Seeding at 30 ° C, much greater degree of growth & agglomeration. Weighted Data Weighted distributions show changes to crystal size and number for the period after seeding and cooling to 2°C.
  • 17. Visualising Seeding Events at 20 °C Weighted Data Seeding at 20 ° C the particles are small agglomerates. During the cool to 2 ° C visible increase in the number & size of the agglomerates.
  • 18. Visualising Seeding Events at 30 °C Weighted Data Compared to seeding at 20 ° C, the initial hold after seeding at 30 ° C results in modest nucleation and growth. However, at the end of the cooling to 2 ° C, the agglomerated crystals are already very large.
  • 19. Quantifying the Effect of Attrition Unweighted Data The population of crystals smaller than 50 μ m has increased by about 35%. However, there is very little effect on the large crystal population – suggesting that the fine particles are small crystals that were attached to the surfaces of the agglomerates, but have now become detached due to the higher agitation. The effect of increased agitation is very much less than the effect of changing the seeding temperature.
  • 20. Visualising The Effect of Attrition Unweighted Data These PVM images show the crystal system before and after the increase in agitator speed. After 120 minutes of higher speed agitation a greater number of very small particles, very little change to the large crystals and agglomerates.
  • 21.

Notes de l'éditeur

  1. Import to consider the whole process SLS of small crystals and needles are a big problem If isolating a metastable phase or solvate be aware that these could change during the drying step
  2. This simple example of a population of cubes helps highlight what the number and volume distribution of the particle system looks like.