Experimental Characterization and Population Balance Modeling of the Polymorph Transformation of <scp>l</scp>-Glutamic Acid

Cornel, Jan H.; Lindenberg, Christian; Mazzotti, Marco

doi:10.1021/cg800387a

Cited by 80 publications

(111 citation statements)

References 35 publications

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“…Crystals of the ␣ polymorph of l-glutamic acid have been precipitated by mixing equimolar amounts of l-glutamic acid monosodium salt hydrate (Sigma Aldrich, purity >99%) and hydrochloric acid (Fluka, 37%) in water and continuous stirring for 1 h at 5 • C (Cornel et al, 2009). The product suspension was split into two fractions.…”

Section: Preparation Of Crystalsmentioning

confidence: 99%

An optimization-based approach to extract faceted crystal shapes from stereoscopic images

Schorsch

Hours

Vetter

et al. 2015

Computers & Chemical Engineering

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a b s t r a c tThe size and shape of particles crucially influences the characteristics of solid products. Until recently these quantities were evaluated using light microscopy. However, extracting the three-dimensional shape of a faceted crystal from a single image is a formidable computer vision challenge. In this work we combine stereoscopic imaging devices (e.g., commercial stereoscopic microscopes or the stereoscopic flow through cell that continuously draws samples from a crystallizer ) with a model-based approach in which parametric polytopes are used to describe faceted crystals (Hours et al., 2014). In the shape reconstruction algorithm these parametric polytopes are scaled and rotated until their projections closely match the measured stereoscopic images, which is formulated as a nonlinear optimization problem. The proposed approach is assessed using simulated images and experimental data. We also assess in which cases the proposed approach does or does not provide advantages over concepts using generic particle shapes (Schorsch et al., 2012).

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Section: Preparation Of Crystalsmentioning

confidence: 99%

An optimization-based approach to extract faceted crystal shapes from stereoscopic images

Schorsch

Hours

Vetter

et al. 2015

Computers & Chemical Engineering

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“…Glu ðsolid Þ (4) where Glu 11 is the protonated form with an overall charge of 11; Glu 12 is the deprotonated form with an overall charge of 21, viz., MSG; Glu 22 is the fully deprotonated form with an overall charge of 22; Glu (aq) and Glu (solid) are the GA zwitterion with an overall charge of zero in aqueous solution and solid, respectively; K ai (i 5 1, 2, 3) are the respective equilibrium constants; and K sp is the solubility product for GA. 14 The four solute-related species can coexist in the solution, which change their respective concentrations or fractions in solution with varying pH, as shown in Figure 1.…”

Section: Kspmentioning

confidence: 99%

“…Finally, when the solute concentration is below the solubility of the a-form glutamic acid, the polymorphic transformation from the a-to b-form may occur through SMPT. Then, it is necessary to consider the dissolution of the aform in the kinetic scheme, which is given as 13,22 …”

Section: Crystallization Mechanisms and Kineticsmentioning

confidence: 99%

Modeling and Bayesian parameter estimation for semibatch pH‐shift reactive crystallization of l‐glutamic acid

Chiu

Braatz

2014

AIChE Journal

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A mathematical model for semibatch pH-shift reactive crystallization of L-glutamic acid is developed that takes into account the effects of protonation and deprotonation in the species balance of glutamic acid, crystal size distribution, polymorphic crystallization, and nonideal solution properties. The crystallization mechanisms of a-and b-forms of glutamic acid are addressed by considering primary and secondary nucleation, size-dependent growth rate, and mixing effects on nucleation. The kinetic parameters are estimated by Bayesian inference from batch experimental data collected from literature. Probability distributions of the estimated parameters in addition to their point estimates are obtained by Markov Chain Monte Carlo simulation. The first-principles model is observed in good agreement with the experimental data and can be further used for model predictions in robust control strategies.

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“…where, m Form II is the mass per volume of metastable polymorph (Form II) and k B1-3 are the parameters that should be estimated [23].…”

Section: Crystallization Kineticsmentioning

confidence: 99%

Kinetics Estimation and Polymorphic Transformation Modeling of Buspirone Hydrochloride

Trifkovic¹,

Rohani²,

Sheikhzadeh³

2012

JCPT

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In this work, solvent-mediated polymorphic transformation of metastable Form II to stable Form I of Buspirone Hydrochloride (BUS-HCl) was studied. The polymorphic transformation was monitored using in-situ Raman spectroscopy. The solvent-mediated transformation process is governed by the dissolution of Form II and the nucleation and subsequent growth of Form I. The model parameters for each of these sub-processes were determined with the aid of experimental data including polymorphic fraction in solid phase, solute concentration, and the crystal size distribution. In order to estimate the kinetic parameters, independent seeded batch sets of experiments were conducted, first to estimate the growth rate of Form I, and consequently to estimate the secondary nucleation of Form I and dissolution rate of Form II. The experimental data showed that the secondary nucleation of Form I occurred slightly after the dissolution of Form II was initiated. The estimated parameters for growth, nucleation and dissolution rates were successfully implemented in the population model and validated with the experiments.

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Experimental Characterization and Population Balance Modeling of the Polymorph Transformation of l-Glutamic Acid

Cited by 80 publications

References 35 publications

An optimization-based approach to extract faceted crystal shapes from stereoscopic images

An optimization-based approach to extract faceted crystal shapes from stereoscopic images

Modeling and Bayesian parameter estimation for semibatch pH‐shift reactive crystallization of l‐glutamic acid

Kinetics Estimation and Polymorphic Transformation Modeling of Buspirone Hydrochloride

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