Investigation and simulation of crystallization of high aspect ratio crystals with fragmentation

Abstract Background Crystallization is a widely used unit operation in the pharmaceutical industry where high aspect ratio crystals are often produced. To avoid undesired shape i.e. high aspect ratio crystals according to downstream operations, appropriate level of understanding process is necessary. Breakage often occurs during the process and gives rise to change the Crystal shape. A well-adjusted, detailed model can be usable tool for investigation and optimization of control. Method A two-dimensional population balance model of continuous cooling crystallization, involving nucleation, growth of two characteristic crystal facets and random binary breakage of high aspect ratio crystals is developed. The randomness of breakage is described by beta distribution of broken fractions. The population balance model is reduced into a closed moment equation model for the joint moments of the two size variables of crystals by means of which the influence of parameters of breakage on the dynamic and steady state behavior of crystallizer is analyzed according to understand the impact of complex kinetic on crystal shape. Results Analysis of the process provides information of breakage influence on aspect ratio of crystal. It is shown that the mean value of crystal width increases as the intensity of breakage along the crystal length resulted in increasing number of crystals.

[1]  L. L. Simon,et al.  Histogram Matching, Hypothesis Testing, and Statistical Control-Chart-Assisted Nucleation Detection Using Bulk Video Imaging for Optimal Switching between Nucleation and Seed Conditioning Steps , 2010 .

[2]  Z. Nagy,et al.  Evaluation of the Effect of Seed Preparation Method on the Product Crystal Size Distribution for Batch Cooling Crystallization Processes , 2010 .

[3]  James B. Rawlings,et al.  Particle-shape monitoring and control in crystallization processes , 2001 .

[4]  Influence of breakage on crystal size distribution in a continuous cooling crystallizer , 2012 .

[5]  K. Sundmacher,et al.  On the Prediction of Crystal Shape Distributions in a Steady State Continuous Crystallizer , 2009 .

[6]  Ali N. Saleemi,et al.  Enhancing crystalline properties of a cardiovascular active pharmaceutical ingredient using a process analytical technology based crystallization feedback control strategy. , 2012, International journal of pharmaceutics.

[7]  M. Jiang,et al.  The effects of anionic impurities on the growth habit and optical properties of KDP , 1999 .

[8]  D. O'grady,et al.  A Review of the Use of Process Analytical Technology for the Understanding and Optimization of Production Batch Crystallization Processes , 2005 .

[9]  B. Biscans.  Impact attrition in crystallization processes. Analysis of repeated impacts events of individual crystals , 2004 .

[10]  Richard D Braatz,et al.  Advances and new directions in crystallization control. , 2012, Annual review of chemical and biomolecular engineering.

[11]  Zoltan K. Nagy,et al.  Automatic differentiation‐based quadrature method of moments for solving population balance equations , 2012 .

[12]  François Puel,et al.  Simulation and analysis of industrial crystallization processes through multidimensional population balance equations. Part 2: a study of semi-batch crystallization , 2003 .

[13]  Konrad Hungerbühler,et al.  In-situ monitoring of pharmaceutical and specialty chemicals crystallization processes using endoscopy-stroboscopy and multivariate image analysis , 2012 .

[14]  Zoltan K. Nagy,et al.  Nonlinear Model-Based Control of a Semi-Industrial Batch Crystallizer Using a Population Balance Modeling Framework , 2012, IEEE Transactions on Control Systems Technology.

[15]  Q. Yin,et al.  Determination of growth and breakage kinetics of l-threonine crystals , 2006 .

[16]  James B. Rawlings,et al.  Industrial crystallization process control : Manipulating crystal size, shape, and structure , 2006 .

[17]  Zoltan K. Nagy,et al.  Combined Quadrature Method of Moments and Method of Characteristics Approach for Efficient Solution of Population Balance Models for Dynamic Modeling and Crystal Size Distribution Control of Crystallization Processes , 2009 .

[18]  B. Mazzarotta,et al.  Abrasion and breakage phenomena in mechanically stirred crystallizers , 1996 .

[19]  Z. Nagy,et al.  Systematic design of supersaturation controlled crystallization processes for shaping the crystal size distribution , 2012 .

[20]  L. L. Simon,et al.  Endoscopy-Based in Situ Bulk Video Imaging of Batch Crystallization Processes , 2009 .

[21]  Kevin J. Roberts,et al.  Multi-dimensional population balance modeling of the growth of rod-like L-glutamic acid crystals using growth rates estimated from in-process imaging , 2007 .

[22]  François Puel,et al.  Simulation and analysis of industrial crystallization processes through multidimensional population balance equations. Part 1: a resolution algorithm based on the method of classes , 2003 .

[23]  B. K. Paul,et al.  Effect of supersaturation and fluid shear on the habit and homogeneity of potassium dihydrogen phosphate crystals , 1974 .

[24]  D. L. Ma,et al.  High-Resolution Simulation of Multidimensional Crystal Growth , 2002 .

[25]  Daniel J. Burnett,et al.  Effect of Milling on Particle Shape and Surface Energy Heterogeneity of Needle-Shaped Crystals , 2012, Pharmaceutical Research.

[26]  B. Lakatos,et al.  Simulation and analysis of crystallization of high aspect ratio crystals with fragmentation , 2012 .

[27]  Zoltan K. Nagy,et al.  Bulk video imaging based multivariate image analysis, process control chart and acoustic signal assisted nucleation detection , 2010 .

[28]  Zhengxiao Guo,et al.  High-speed observation of the effects of ultrasound on liquid mixing and agglomerated crystal breakage processes , 2007 .

[29]  Narayan Variankaval,et al.  From Form to Function: Crystallization of Active Pharmaceutical Ingredients , 2008 .

[30]  Heiko Briesen,et al.  Simulation of crystal size and shape by means of a reduced two-dimensional population balance model , 2006 .

[31]  Michael F. Doherty,et al.  Shape evolution of 3‐dimensional faceted crystals , 2006 .

[32]  Marjatta Louhi-Kultanen,et al.  Crystal Shape Control by Manipulating Supersaturation in Batch Cooling Crystallization , 2006 .

[33]  Zoltan K. Nagy,et al.  Internal Fines Removal Using Population Balance Model Based Control of Crystal Size Distribution under Dissolution, Growth and Nucleation Mechanisms , 2011 .

[34]  Chao Y. Ma,et al.  Model identification of crystal facet growth kinetics in morphological population balance modeling of l-glutamic acid crystallization and experimental validation , 2012 .

[35]  L. L. Simon,et al.  Comparison of external bulk video imaging with focused beam reflectance measurement and ultra-violet visible spectroscopy for metastable zone identification in food and pharmaceutical crystallization processes , 2009 .

[36]  Peter J. Jansens,et al.  Two-dimensional population balance model with breakage of high aspect ratio crystals for batch crystallization , 2008 .

[37]  Carl M Schoellhammer,et al.  Computational and experimental investigation of needle-shaped crystal breakage. , 2011, International journal of pharmaceutics.

[38]  Zoltan K. Nagy,et al.  Model based robust control approach for batch crystallization product design , 2009, Comput. Chem. Eng..

[39]  Richard D. Braatz,et al.  First-principles and direct design approaches for the control of pharmaceutical crystallization , 2005 .

[40]  Kevin J. Roberts,et al.  Crystal growth measurement using 2D and 3D imaging and the perspectives for shape control , 2008 .

[41]  Ali N. Saleemi,et al.  Automated direct nucleation control for in situ dynamic fines removal in batch cooling crystallization , 2012 .