Batch Cooling Crystallization Research Articles

Influence of Viscosity on Variously Scaled Batch Cooling Crystallization from Aqueous Erythritol, Glucose, Xylitol, and Xylose Solutions.

This study presents a comprehensive comparison of the batch cooling crystallization performance of aqueous solutions containing sugars and sugar alcohols, namely, erythritol, glucose, xylitol, and xylose. Erythritol and xylitol are commonly used alternative sweeteners to replace sucrose. They can be obtained by fermentation-based bioprocesses, where glucose and xylose are typical raw materials. These model compounds were selected based on their differing rheological nature: saturated erythritol solution has a viscosity lower than 3 mPa·s, whereas xylitol has the highest viscosity: greater than 90 mPa·s in the studied temperature range. Viscosities and densities of saturated solutions as well as apparent viscosities of crystal-mother liquor suspensions were measured. The purpose was to evaluate their crystallization behavior within a specific temperature range from 40 to 20 °C and batch time of 2 h, with the aim of understanding the influence of viscosity on the process more comprehensively. The comparison within the selected compound systems was carried out in terms of the physical properties of the mother liquor and the crystalline product. In addition to empirical laboratory-scale (0.1 and 1 L) studies, larger-scale simulations (1 and 100 m3) were performed with the experimental data obtained on average particle size, density, and viscosity for mother liquor and crystal-mother liquor suspensions. Mixing characteristics, such as the dissipation energy, mass transfer coefficient, energy of collisions, and micromixing time, were calculated with VisiMix software when using a single or dual impeller mixer. Furthermore, the scaling up of erythritol, xylitol, glucose, and xylose batch cooling crystallization from 40 to 20 °C based on the scaling-up rule of constant tip speed and energy of dissipation was done with VisiMix to obtain overall data on mixing conditions with crystallizers of 1 and 100 m3 in volume. Furthermore, ANSYS CFD software was used to determine the strain rates close to the impeller tip and velocity profiles on various crystallizer scales.

Comparative Study on Adaptive Bayesian Optimization for Batch Cooling Crystallization for Slow and Fast Kinetic Regimes.

Crystallization kinetic parameter estimation is important for the classification, design, and scale-up of pharmaceutical manufacturing processes. This study investigates the impact of supersaturation and temperature on the induction time, nucleation rate, and growth rate for the compounds lamivudine (slow kinetics) and aspirin (fast kinetics). Adaptive Bayesian optimization (AdBO) has been used to predict experimental conditions that achieve target crystallization kinetic values for each of these parameters of interest. The use of AdBO to guide the choice of the experimental conditions reduced material usage up to 5-fold when compared to a more traditional statistical design of experiments (DoE) approach. The reduction in material usage demonstrates the potential of AdBO to accelerate process development as well as contribute to Net-Zero and green chemistry strategies. Implementation of AdBO can lead to reduced experimental effort and increase efficiency in pharmaceutical crystallization process development. The integration of AdBO into the experimental development workflows for crystallization development and kinetic experiments offers a promising avenue for advancing the field of autonomous data collection exploiting digital technologies and the development of sustainable chemical processes.

Development of a Digital Twin for the Prediction and Control of Supersaturation during Batch Cooling Crystallization.

Fine chemicals produced via batch crystallization with properties dependent on the crystal size distribution require precise control of supersaturation, which drives the evolution of crystal size over time. Model predictive control (MPC) of supersaturation using a mechanistic model to represent the behavior of a crystallization process requires less experimental time and resources compared with fully empirical model-based control methods. Experimental characterization of the hexamine-ethanol crystallization system was performed in order to collect the parameters required to build a one-dimensional (1D) population balance model (PBM) in gPROMS FormulatedProducts software (Siemens-PSE Ltd.). Analysis of the metastable zone width (MSZW) and a series of seeded batch cooling crystallizations informed the suitable process conditions selected for supersaturation control experiments. The gPROMS model was integrated with the control software PharmaMV (Perceptive Engineering Ltd.) to create a digital twin of the crystallizer. Simulated batch crystallizations were used to train two statistical MPC blocks, allowing for in silico supersaturation control simulations to develop an effective control strategy. In the supersaturation set-point range of 0.012-0.036, the digital twin displayed excellent performance that would require minimal controller tuning to steady out any instabilities. The MPC strategy was implemented on a physical 500 mL crystallizer, with the simulated solution concentration replaced by in situ measurements from calibrated attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy. Physical supersaturation control performance was slightly more unstable than the in silico tests, which is consistent with expected disturbances to the heat transfer, which were not specifically modeled in simulations. Overall, the level of supersaturation control in a real crystallizer was found to be accurate and precise enough to consider future adaptations to the MPC strategy for more advanced control objectives, such as the crystal size.

Modeling of Nucleation, Growth, and Dissolution of Paracetamol in Ethanol Solution for Unseeded Batch Cooling Crystallization with Temperature-Cycling Strategy

Controlling crystal size distributions is critical to ensure the quality of products and operational efficiency for downstream processing. In batch cooling crystallization, temperature cycling strategies are often employed to control the crystal size distribution and minimize fines. Optimizing the complex operation of this strategy, where crystallization and dissolution occur in a single batch run, remains a challenge. For this problem, we develop a model of the process by a population balance considering nucleation, growth, and dissolution of crystals. In a case study of paracetamol in ethanol, the parameters in the population balance model were estimated from multiple experimental runs. The developed model was validated against additional experimental data sets, where the concentration and crystal size distributions of the final crystal products were predicted successfully. R2 values are greater than 0.96 in all cases.

Data-Driven Operation Modeling and Optimal Design for Batch Cooling Crystallization with a Case Study on β-LGA

In this paper, a data-driven modeling and optimization method is proposed for batch operation of the cooling crystallization process based on the design of experiments (DoE) in the operation ranges of cooling rate and initial solution supersaturation. The proposed model reflecting a mapping relationship between the manipulated variables of operating conditions and the product crystal size distribution (CSD) is established by two classes of basis functions, one is the wavelet basis function for reshaping the CSD and the other is the polynomial basis function for weighting the chosen wavelet basis functions to reflect the nonlinear relationship between the manipulated variables and the size distribution of product crystals. Meanwhile, a fractional factorial design of DoE is presented to reduce the number of experiments for the above modeling, in comparison with the classical full factorial design. The optimal operating conditions are designed by introducing a comprehensive objective function that combines the information entropy of the product CSD and the ratio of desired product yield with respect to the target crystal size. A particle swarm optimization algorithm with guaranteed convergence is given to solve the nonconvex optimization problem based on the established CSD prediction model. Simulation studies and experiments on the batch seeded β-form L-glutamic acid (LGA) crystallization process are conducted to demonstrate the effectiveness and advantage of the proposed method.

Digital Design of Batch Cooling Crystallization Processes: Computational Fluid Dynamics Methodology for Modeling Free-Surface Hydrodynamics in Agitated Crystallizers

A framework for the digital design of batch cooling crystallization processes is presented comprising three stages, which are based on different levels of process complexity, integrating crystallizer hydrodynamics with crystallization kinetics and consequently with expected crystal size distribution. In the first stage of the framework, a computational fluid dynamics methodology is developed to accurately assess hydrodynamics in a typical batch crystallizer configuration, comprising a 20 L scale dish-bottom vessel with a single beavertail baffle agitated by a retreat curve impeller, used in the pharmaceutical as well as in the fine chemical industries. The hydrodynamics of crystallizers with such configurations is characterized by vortex formation on the free liquid surface. It is therefore important to model the free surface using the Volume-of-Fluid (VoF) method. Comparison of the predicted mean velocity components with experimental measurements using laser Doppler anemometry reveals that improved predictions are obtained using a differential Reynolds-stress transport model for turbulence coupled with the VoF for modeling the gas-liquid interface compared with those using the Shear-stress transport model and with a flat liquid surface. This study demonstrates that an accurate treatment of the liquid free surface for capturing vortex formation is essential for reliable predictions of the crystallizer’s flow field. While the vortex depth is predicted to increase with increasing impeller Reynolds number, the dependence of hydrodynamic macroparameters, including power number, impeller flow number, and secondary circulation flow number, on Reynolds number reveals that they are essentially constant within the turbulent regime but fluctuate when the flow is in the transitional and laminar regimes as fluid viscosity increases.

Parameter Estimation of the Stochastic Primary Nucleation Kinetics by Stochastic Integrals Using Focused-Beam Reflectance Measurements

The kinetic parameters of stochastic primary nucleation were estimated for the batch-cooling crystallization of L-arginine. It is difficult for process analytical tools to detect the first nucleus. In this study, the latent period for the total number of crystals to be increased to a predetermined threshold was repeatedly measured with focused-beam reflectance measurements. Consequently, the latent periods were different in each measurement due to the stochastic behavior of both primary and secondary nucleation. Therefore, at first, the distribution of the latent periods was estimated by a Monte Carlo simulation for some combinations of the kinetic parameters of primary nucleation. In the simulation, stochastic integrals of the population and mass balance equations were solved. Then, the parameters of the distribution of latent periods were estimated and correlated with the kinetic parameters of primary nucleation. The resulting correlation was represented by a mapping. Finally, the parameters of the actual distribution were input into the inverse mapping, and the kinetic parameters were estimated as the outputs. The estimated kinetic parameters were validated using statistical techniques, which implied that the observed distribution function of the latent periods for the thresholds used in the estimation coincided reasonably with the simulated one based on the estimated parameters.

Partial Seeding Policy for Controlling the Crystal Quality in Batch Cooling Crystallization

AbstractPartial seeding, in which the nuclei originating from seed crystals grow to yield the product crystals, was simulated and optimized for controlling the batch cooling crystallization process of L‐arginine. The product quality was evaluated by the coefficient of variation (CV) of the crystal size distribution. First, the optimum seed amount for partial seeding was estimated by simulation. Then, the simulated values of the optimum seed amount and the resulting local minimum CV were correlated with the seed crystal size and the cooling rate. The correlation can be utilized for estimating the seed amount in the case that the seed crystals are added in a slurry. Finally, these simulated values were compared to the measured ones. Consequently, the optimum seed amount was suggested to be reasonably predicted.

Quantitative Link between Secondary Nucleation and Mixing Hydrodynamics in Batch Cooling Crystallization: A New Approach in Process Development

Precise control of a crystallization process requires a clear understanding of nucleation kinetics. Interpreting secondary nucleation threshold (SNT) of a given crystallization process under optimized hydrodynamic conditions can highlight the impact of critical process variables on product particle size distribution (PSD). In this work, a new approach is proposed in industrial crystallization process development in which a quantitative link was developed between batch cooling crystallization and fluid turbulent shear stress (TSS). The experiments involve solution crystallization of paracetamol in isopropanol. A novel method was adopted in which a large single seed crystal of paracetamol was held stationary in an agitating reactor. Using particle imaging velocimetry, a constant TSS was obtained across different scales which resulted in a constant SNT because of crystal nuclei breeding. This led to better control over the crystallization process which eventually resulted in a consistent PSD, independent of ...

Partial Seeding Policy for Controlling Size Distribution of Product Crystal by Batch Cooling Crystallization

Partial Seeding Policy for Controlling Size Distribution of Product Crystal by Batch Cooling Crystallization

Purification of Nickel Sulfate by Batch Cooling Crystallization

AbstractCooling crystallization was successfully carried out in a batch cooling crystallizer from impure acidic solutions to recover nickel as nickel sulfate salt with three different cooling rates. The compositions of the solutions included impurities of sodium, magnesium, chloride, and sulfuric acid to mimic industrial nickel electrowinning process solutions. The results show that NiSO4·6H2O mainly crystallized, and its solubility and purity decreased with the increase in the mass ratio of chloride to sulfate. Cooling rates did not have a significant influence on crystal purity; however, it did affect the filter cake moisture; lower moisture can be obtained with a lower cooling rate. The sequence of impurity removal efficiency from high to low was Cl > Na > Mg.

Seed Recipe Design for Batch Cooling Crystallization with Application to l-Glutamic Acid

In this paper, a seed recipe design is proposed for batch cooling crystallization to obtain the desired product attributes including product yield and product size distribution, based on simulation studies and experiments on β-l-glutamic acid (β-LGA) crystallization. The impact of seed recipe on product attributes is investigated based on the population balance model (PBM) simulations with respect to the size-dependent growth of crystals. It is found that the product yield is primarily affected by the seed loading ratio (SLR) and the batch time, but less affected by the mean size and variance of seeds. Smaller seeds could improve the product yield, and in contrast, larger seeds facilitate the growth into larger crystals but require a larger SLR to ensure the product yield. By introducing an objective function for optimization with the above PBM, a seed recipe design is given for obtaining the desired product attributes as above-mentioned. In addition, it is found that washing seeds by the solvent is necessary to ensure seed quality for quantitative seed recipe design and implementation, by comparing three different seed preparation methods. Simulation tests and experiments well demonstrate the effectiveness of the proposed seed recipe design for seeded batch cooling crystallization.

Multiobjective Optimization of Unseeded and Seeded Batch Cooling Crystallization Processes

Multiobjective optimization (MOO) of batch cooling crystallization is carried out for the development of optimal operating recipes for unseeded and seeded crystallization processes. Mean size and coefficient of variation (CV) are the two objectives considered for unseeded batch cooling crystallization of paracetamol, whereas mean size, CV, and nucleated mass are considered as objectives for the seeded batch cooling crystallization of potassium nitrate. In this work, along with finding the optimal temperature trajectories, the effect of choice of objectives on the final achievable Pareto front is analyzed using two different objective functions, namely number mean size and surface-weighted mean size. Further, the capability of MOO is also exploited to determine the feasible ranges of combinations of seed properties like initial seed mass and seed mean size for better crystal size distribution (CSD).

Modeling of Nucleation and Growth Kinetics for Unseeded Batch Cooling Crystallization

Both primary and secondary nucleation rates are considered in a model developed for unseeded batch crystallization. A carefully designed strategy was employed to minimize the effects of the stochastic nature of induction time; nucleation was induced at designed supersaturations on known temperature plateaus. Crystallization kinetics of paracetamol from ethanolic solutions were extracted from measurements of in situ solute concentrations and combined with sieve (ex situ) data on the final product. Parameters in models for primary and secondary nucleation and for crystal growth rate were estimated by fitting a full population balance model to the measurements, and the evolution of the crystal size distribution was compared against in situ estimation from focused-beam reflectance measurements using the technique that we previously developed. The resulting models suggest that primary nucleation produces fewer surviving crystals than had been expected and that most of the product crystals from the process invo...

Kinetic modeling on batch-cooling crystallization of zinc lactate: The influence of malic acid

Influence of malic acid, which acts as an impurity, on the crystallization kinetics of zinc lactate has been investigated in this work. Crystallization of zinc lactate with a linear cooling profile was carried out in a batch crystallizer and a population balance model was used to estimate the crystallization kinetics for each studied system by using the nonlinear optimization method. The predicted results related to the concentration profile of zinc lactate are in good agreement with the experimental data. The influence of malic acid on the crystallization of zinc lactate is discussed herein.

バッチ冷却晶析プロセスのモデルベース精密温度制御設計ベンチマーク

バッチ冷却晶析プロセスのモデルベース精密温度制御設計ベンチマーク

Multiobjective Optimization of an Unseeded Batch Cooling Crystallizer for Shape and Size Manipulation

The optimization of unseeded batch cooling crystallization systems is studied in a multiobjective framework. The length mean size and target aspect ratio (AR) of final crystals were considered as objectives, which give rise to a set of optimal solutions known as Pareto-optimal solutions. Two model compounds were considered: paracetamol and potassium dyhidrogen phosphate (KDP), nucleation and growth dominated systems, respectively. The optimization of KDP showed a dependence between the optimal profile and the target objectives weights. The optimal profile for paracetamol did not vary from a cubic cooling profile due to the low sensitivity of the AR to temperature changes. Furthermore, the longer batch time has a greater impact on the optimal AR that could be achieved due to the variation in supersaturation dependence. Moreover, it was shown that there is a relation between the classification of crystallization kinetics based on growth and nucleation mechanisms and the set of optimal cooling profiles for s...

Adjustment of Process Conditions in Seeded Batch Cooling Crystallization

AbstractThe influence of seed addition temperature, seed surface area, and seeds of different origin on granulometric characteristics and polymorphism of glycine was examined. At sufficient surface seed area, a regular and narrow crystal size distribution (CSD) was obtained. Polymorphism was investigated by differential scanning calorimetry and X‐ray diffraction analysis. Differences in seed size and seed mass couple affected the granulometric properties but did not cause changes in polymorphic structure. Four experiments with different origin seeds were carried out under optimal process conditions determined by preliminary experiments. Various seed origins caused differences in supersaturation level and CSD but the structure of the obtained crystals remained the same as the loaded seed.

Investigation of Batch Cooling Crystallization in a Liquid–Liquid Separating System by PAT

Crystallization of butyl paraben from water–ethanol mixtures has been investigated. The liquid–liquid phase separation and the solid–liquid solubility have been determined from 1 to 50 °C. Cooling crystallizations have been performed at different starting compositions, and the processes have been recorded by in-situ infrared spectroscopy, focused beam reflectance measurement, and particle video microscopy. In pure water the butyl paraben solubility is below 1 mg/g, while in pure ethanol the solubility is more than 3 orders of magnitude higher. While the solution saturated with butyl paraben is homogeneous at 1 °C, at the higher temperatures butyl paraben induces a liquid–liquid phase separation of the ethanol–water mixture, and the ternary phase diagram contains up to five different regions. The size of the liquid–liquid phase separation region increases with increasing temperature. At 50 °C, even the binary butyl paraben water system separates into two different liquid phases. In the cooling crystallizat...

Influence of Batch Cooling Crystallization on Mannitol Physical Properties and Drug Dispersion from Dry Powder Inhalers

This study provides, for the first time, an evaluation of the physicochemical properties of batch cooling crystallized mannitol particles combined with how these properties correlated with the inhalation performance from a dry powder inhaler (Aerolizer). The results showed that the type of polymorph changed from β-form (commercial mannitol) to mixtures of β- + δ-mannitol (cooling crystallized mannitol crystals). In comparison to mannitol particles, crystallized at a higher supersaturation degree, a lower degree of supersaturation favored the formation of mannitol crystals with a more regular and elongated habit, smoother surface, higher specific surface area, higher fine particle content, higher bulk density, and higher tap density. Cooling crystallized mannitol particles demonstrated considerably lower salbutamol sulfate–mannitol adhesion in comparison to commercial mannitol, with a linear reduction as surface roughness decreased and fines content increased. Also, mannitol crystals with smoother surfaces demonstrated a reduction in salbutamol sulfate content uniformity (expressed as %CV) within salbutamol sulfate–mannitol formulations. Despite the different physical properties, all mannitol products showed similar flow properties and similar emission of salbutamol sulfate upon inhalation. However, mannitol crystals grown from lower supersaturation (reduced roughness and increased fines) generated a finer aerodynamic size distribution and consequently deposited higher amounts of salbutamol sulfate on lower stages of the impactor. Regression analysis indicated linear relationships showing higher fine particle fraction of salbutamol sulfate in the case of mannitol particles having a more elongated shape, higher fines content, higher specific surface area, higher bulk density, and higher tap density. In conclusion, a cooling crystallization technique could be controlled to produce mannitol particles with controlled physical properties that could be used to influence aerosolization performance of a dry powder inhaler product.