Continuous Crystallization Process Research Articles

Recovery of nitrogen as struvite from swine wastewater: Comparison study of batch and continuous fluidized-bed crystallization process

The recovery of valuable compounds from waste supports the idea of a circular economy. Two systems were introduced in this study to recover nitrogen as struvite from swine wastewater, including batch stirred and fluidized-bed homogeneous crystallization (FBHC) systems. MgCl2 and NaH2PO4 were applied as precipitants to form struvite. In the batch stirred system, the removal efficiency of NH4+, Mg2+, and PO43− reached the optimum condition of 92.1 %, 75.6 %, and 91.1 %, respectively, under the operating conditions of pH 9 and an Mg/P molar ratio of 1.2. In the same operating conditions, the Crystallization ratio (CR) and Total Removal (TR) of the FBHC system reached 83.2 % and 89.1 %; 86.7 % and 90.6 %; 71.2 % and 76.1 % for NH4+, Mg2+, and PO43−, respectively. The XRD and FT-IR analyses confirmed the high purity and quality of the struvite solid product. However, the water content of the FBHC product is much lower than that of the batch-stirred system (5.8 % and 95.3 %, respectively). The great potential of swine wastewater as a nitrogen source for fertilizer production is evidenced by the high purity struvite product (>85.0 %).

Single and Multiobjective Shutdown Optimization of a Multistage Continuous Crystallizer.

This study presents the first model-based optimal shutdown procedure of a multistage continuous crystallization process which aims at the maximization of on-spec production and minimization of the shutdown time. The cooling antisolvent crystallization of Aspirin (acetylsalicylic acid) in a three-stage continuous crystallizer was used as a case study. To address the optimal shutdown problem, several single optimization scenarios were considered to assess the impact of the degrees of freedom, discretization schemes, and optimization settings such as the constraints. The proposed optimal shutdown procedures showed that significant amounts of on-spec crystals can be produced both at fixed and variable shutdown times. Most importantly, the optimal shutdown procedures can match the steady-state productivity, based on the shutdown to steady-state productivity ratio (STSPR) which can easily reach 100%. Moreover, the residual shutdown material, considered as waste, can be dramatically reduced by >80% compared to the current standard shutdown procedures. Given the conflicting nature of the maximization of on-spec production and minimization of the shutdown time, multiobjective optimization of the shutdown operation was also addressed to identify the set of Pareto optimal solutions. Finally, a multicriteria decision-aiding method, based on multiattribute utility theory, was proposed to rank the Pareto optimal solutions to support the decision-making and help identify a suitable and feasible single optimal shutdown solution.

Continuous Microfluidic Antisolvent Crystallization as a Bottom-Up Solution for the Development of Long-Acting Injectable Formulations.

A bottom-up approach was investigated to produce long-acting injectable (LAI) suspension-based formulations to overcome specific limitations of top-down manufacturing methods by tailoring drug characteristics while making the methods more sustainable and cost-efficient. A Secoya microfluidic crystallization technology-based continuous liquid antisolvent crystallization (SCT-CLASC) process was optimized and afterward compared to an earlier developed microchannel reactor-based continuous liquid antisolvent crystallization (MCR-CLASC) setup, using itraconazole (ITZ) as the model drug. After operating parameter optimization and downstream processing (i.e., concentrating the suspensions), stable microsuspensions were generated with a final solid loading of 300 mg ITZ/g suspension. The optimized post-precipitation feed suspension consisted of 40 mg ITZ/g suspension with a drug-to-excipient ratio of 53:1. Compared to the MCR-CLASC setup, where the post-precipitation feed suspensions contained 10 mg ITZ/g suspension and had a drug-to-excipient ratio of 2:1, a higher drug concentration and lower excipient use were successfully achieved to produce LAI microsuspensions using the SCT-CLASC setup. To ensure stability during drug crystallization and storage, the suspensions' quality was monitored for particle size distribution (PSD), solid-state form, and particle morphology. The PSD of the ITZ crystals in suspension was maintained within the target range of 1-10 µm, while the crystals displayed an elongated plate-shaped morphology and the solid state was confirmed to be form I, which is the most thermodynamically stable form of ITZ. In conclusion, this work lays the foundation for the SCT-CLASC process as an energy-efficient, robust, and reproducible bottom-up approach for the manufacture of LAI microsuspensions using ITZ at an industrial scale.

Population balance model enabled digital design and uncertainty analysis framework for continuous crystallization of pharmaceuticals using an automated platform with full recycle and minimal material use

A systematic digital design framework for the development of a digital twin of a continuous crystallization process was presented using the model compound, diphenhydramine hydrochloride (DPH). The key features of the framework include operating space investigations, kinetic parameter estimation using population balance modeling, and systematic batch-to-continuous crystallization translation of the estimated parameters. An approach that compares experimental uncertainties with model-prediction uncertainties was used to justify the robustness of the parameter estimation procedure. For continuous crystallization development, a continuous configuration with full recycle and dissolution was developed, which enabled rapid process design with minimal material use. The results demonstrated successful model development for both batch and mixed-suspension-mixed-product-removal (MSMPR) crystallization configurations. This experimentally validated model, along with quantified uncertainty space of the kinetic parameters, serves as a digital twin of the process, which was later used to optimize the multistage MSMPR process to produce larger crystals with narrower distributions.

Geochemical Evidence for Genesis of Nb–Ta–Be Rare Metal Mineralization in Highly Fractionated Leucogranites at the Lalong Dome, Tethyan Himalaya, China

Leucogranites in the Lalong Dome are composed of two-mica granite, muscovite granite, albite granite, and pegmatite from core to rim. Albite granite-type Be–Nb–Ta rare metal ore bodies are hosted by albite granite and pegmatite. Based on field and petrographic observations and whole-rock geochemical data, highly differentiated leucogranites have been identified in the Lalong Dome. Two-mica granites, albite granites, and pegmatites yielded monazite ages of 23.6 Ma, 21.9 Ma, and 20.6 Ma, respectively. The timing of rare metal mineralization is 20.9 Ma using U–Pb columbite dating. Leucogranites have the following characteristics: high SiO2 content (>73 wt.%); peraluminosity with high Al2O3 content (13.6–15.2 wt.%) and A/CNK (mostly > 1.1); low TiO2, CaO, and MgO content; enrichment of Rb, Th, and U; depletion of Ba, Nb, Zr, Sr, and Ti; strong negative Eu anomalies; low εNd(t) values ranging from −12.7 to −9.77. These features show that the leucogranites are crust-derived high-potassium calc-alkaline and peraluminous S-type granites derived from muscovite dehydration melting under the water-absent condition, which possibly resulted from structural decompression responding to the activity of the South Tibetan detachment system (STDS). Geochemical data imply a continuous magma fractional crystallization process from two-mica granites through muscovite granites to albite granites and pegmatites. The differentiation index (Di) gradually strengthens from two-mica granite, muscovite granite, and albite granite to pegmatite, in which albite granite and pegmatite are highest (Di = 94). The Nb/Ta and Zr/Hf ratios of albite granite and pegmatite were less than 5 and 18, respectively, which suggests that albite granite and pegmatite belong to rare metal granites and have excellent potential for rare metal mineralization.

Nucleation Kinetics of Freeze Crystallization with Various Aqueous Solutions

AbstractThe nucleation kinetics of ice were investigated with four different types of aqueous solutions. The studied aqueous solutions, i.e., sucrose solution, ionic liquid (IL) solution, pyrolysis oil extract (PO) solution, and acetone‐1‐butanol‐ethanol (ABE) solution, were concentrated by batch suspension freeze crystallization. The nucleation kinetics were investigated using a temperature response method which results in data on nucleation rate per crystal. The obtained nucleation rate per crystal value can be used when dimensioning continuous crystallization processes: the nucleation rate per crystal is inversely proportional to the residence time in continuous crystallization. The subcooling degrees for different solutions were in the range of 0.33 °C to 1.89 °C. Aqueous sucrose solutions had the fastest nucleation kinetics. Ice crystallization from non‐ideal aqueous [DBNH][OAc] ionic liquid solutions required higher subcooling degrees and the nucleation rates per crystal were higher as well. Nucleation of ice formed from aqueous pyrolysis oil extract and aqueous ABE solutions occurred at a lower subcooling degree and the obtained nucleation rate per crystal values were lower.

Recent Advancements in Continuous Crystallization of Proteins

AbstractRecently, there have been many studies and reports on various continuous protein crystallization processes. Due to the increasing demand for pharmaceutical proteins such as insulin and monoclonal antibodies, it has become essential to optimize the current industrial processes to meet these demands. There are various comparisons to be made between current batch crystallization processes and continuous processes for proteins. This review paper aims to review the recent advancements in continuous protein crystallization processes, such as slug flow crystallizers, oscillatory baffled crystallizers, and mixed suspension mixed product removal (MSMPR) crystallizers.

Investigating the Role of Citric Acid as a Natural Acid on the Crystallization of Amoxicillin Trihydrate.

This study investigates the use of environmentally friendly citric acid as the main player in the process, rather than as an additive, to remove impurities from amoxicillin trihydrate (AMCT) crystals, aiming to optimize their purity and yield. By manipulating the concentration of citric acid, mixing speed, crystallization time, and pH, the researchers conducted experiments using a full factorial design. The dissolution stage was analyzed in both batch and continuous crystallization processes, emphasizing the significance of citric acid in enhancing crystallization. HPLC analyses were performed on the resulting crystals, and the data were analyzed using the Multi-Vari Chart program. The findings demonstrated that higher citric acid concentrations positively affected the yield, while factors such as crystallization time, mixing speed, and pH also contributed to the increased yield. The crystals obtained exhibited desirable dimensions sought after in the pharmaceutical industry, eliminating the need for additional purification steps. This study showcased the potential of citric acid in AMCT crystallization, offering advantages in product design, purification, and synthesis. The optimized conditions included a citric acid concentration of 2.0 M, mixing speed of 1000 rpm, crystallization time of 120 min, and pH of 5.5. Notably, the developed process proved to be environmentally friendly by avoiding the use of harmful chemicals, serving as a green alternative for crystallization processes, and producing purer AMCT products. Overall, this research contributes to the existing literature by highlighting the efficacy of citric acid in impurity removal and the optimization of AMCT crystal purity and yield.

Optimization of Batch Crystallization of Magnetic Lysozyme Crystals and Study of the Continuous Crystallization Process

Protein crystallization is a widely employed technique for purifying protein drugs, offering notable benefits such as cost-effectiveness and high purity. However, the success of this method is influenced by factors such as the molecular weight and spatial structure of proteins. The challenges associated with achieving crystallization and the prolonged duration required for crystallization induction pose limitations on its widespread industrial implementation. In this study, we employed lysozyme derived from egg white as a representative protein to investigate the polymer-assisted self-assembly of magnetic lysozyme. Through the optimization of the initial interstitial crystallization process of magnetic lysozyme, we manipulated the supersaturation level of lysozyme and applied magnetic nanoparticle treatment. As a result, we successfully reduced the crystallization time from 24 h to 60 min. Subsequently, the findings derived from the analysis of data pertaining to the interstitial crystallization process of lysozyme were utilized to optimize the design and configuration of a push flow crystallizer (PFC) as well as a slug flow crystallizer (SFC). The analysis encompassed the examination of various factors, including the residence time of crystallization, the yield of the process, the shape of the crystals formed, and the distribution of crystal sizes. Ultimately, it was determined that the SFC demonstrated optimal suitability for the crystallization of magnetic lysozyme. The typical V-PFC crystal size is 16 m and the yield is 60%. V-SFC crystals have an average size of 13 m and a yield of 85%.

Review of the Application of PAT in the Pharmaceutical Continuous Crystallization Process.

As an important pharmaceutical process, crystallization greatly impacts the final product. In recent years, the continuous crystallization process has attracted more attention from researchers, with the promotion of continuous manufacturing (CM) by the Food and Drug Administration (FDA). The continuous crystallization process has the advantages of high economic benefit, stable and uniform quality, a short production cycle, and personalization. To carry out continuous crystallization, some related process analytical technology (PAT) tools have become the focus of breakthroughs. Infrared (IR) spectroscopy, Raman spectroscopy, and focused beam reflection measurement (FBRM) tools have gradually become research hotspots due to their fast, non-destructive, and real-time monitoring characteristics. This review compared the advantages and disadvantages of the three technologies. Their applications in the upstream mixed continuous crystallization process, the middle reaches of crystal nucleation and growth, and the process of the downstream refining were discussed to provide corresponding guidance for the practice and further development of these three technologies in the continuous crystallization process and promote the development of CM in the pharmaceutical industry.

Rapid Assessment of Crystal Nucleation and Growth Kinetics: Comparison of Seeded and Unseeded Experiments.

In this work, we outlined an experimental workflow enabling the rapid assessment of primary and secondary nucleation and crystal growth kinetics. We used small-scale experiments in agitated vials with in situ imaging for crystal counting and sizing to quantify nucleation and growth kinetics of α-glycine in aqueous solutions as a function of supersaturation at isothermal conditions. Seeded experiments were required to assess crystallization kinetics when primary nucleation is too slow, especially at lower supersaturations often encountered in continuous crystallization processes. At higher supersaturations, we compared results from seeded and unseeded experiments and carefully analyzed interdependencies of primary and secondary nucleation and growth kinetics. This approach allows for the rapid estimation of absolute values of primary and secondary nucleation and growth rates without relying on any specific assumptions about functional forms of corresponding rate expressions used for estimation approaches based on fitting population balance models. Quantitative relationships between nucleation and growth rates at given conditions provide useful insights into crystallization behavior and can be explored to rationally manipulate crystallization conditions for achieving desirable outcomes in batch or continuous crystallization processes.

Enhanced struvite (MgNH4PO4·6H2O) granulation and separation from synthetic wastewater using fluidized-bed crystallization (FBC) technology

Struvite (MgNH4PO4·6H2O) could be recovered from wastewater containing phosphorus and showed high potential as an alternative source of phosphorus fertilizer. A comparison of batch experiment and continuous crystallization processes was carried out using batch reactor and fluidized bed reactor (FBR) methods, respectively. The continuous crystallization processes for phosphorus granulation were conducted both in a seeded (FBC) and unseeded (FBHC) system. Various seed materials such as dolomite-(CaMg(CO3)2), CaHPO4, and SiO2 were applied as seed material in FBC. In the batch reactor, the operating parameters, including pH, [Mg]0/[P]0 molar ratio, and initial phosphorus concentration were first optimized. The effects of the coexisting ions (SO42−, Cl−, NO3−, Na+, K+, Ca2+) and organic pollutants (Ethylenediaminetetraacetic acid-EDTA, and Citric acid) on phosphorus-containing wastewater treatment were also examined. The hydraulic parameters of FBR (Fluidized-bed reactor), including effluent pHe, and cross-sectional surface loading (L, kg m−2 h−1) were investigated to recover phosphorus and ammonium as struvite pellets. Under optimum conditions (pHe 8.8, [Mg]0/[P]0 = 1.3/1, L = 2.4 kg-P m−2 h−1), FBC using dolomite as seed resulted in higher phosphorus removal efficiency than the FBHC system with total removal (TR) = 93.0 % and a crystallization ratio (CR) = 85.0 %. As confirmed by the XRD pattern, the solid products consist of magnesium ammonium phosphate (MgNH4PO4·6H2O) from both FBC and FBHC processes. The high crystallization ratio (CR = 85 %) and the recovery of crystal pellets (>1 mm) in the FBC process reduce the production of sludge compared to traditional chemical precipitation and FBHC processes.

Process Performance and Operational Challenges in Continuous Crystallization: A Study of the Polymorphs of L-Glutamic Acid.

The crystallization of the two polymorphs of l-glutamic acid (LGA) is carried out in a continuous crystallization process, and its performance according to different criteria is evaluated. The study aims at identifying suitable operating conditions for producing either αLGA or βLGA with a high polymorphic purity. To this end, we investigate the process both from a theoretical perspective and through experiments using either a single stirred-tank crystallizer or a cascade of two stirred-tank crystallizers in series. In terms of theory, we extend the MSMPR-based steady-state stability analysis of Farmer et al. (Farmer, T. C. et al. AIChE J.2016, 62, 3505-3514) by accounting for the possibility of a nonrepresentative withdrawal of the solid phase from the crystallizer. Additionally, the process is simulated using population balance equations, thereby investigating the effect of operating conditions on polymorphic purity, yield, and productivity. Guided by the model-based conclusions, we identified suitable operating conditions and experimentally tested them. The experimental campaign has demonstrated that βLGA could be successfully and continuously produced in both process configurations according to the theory with performance as expected, whereas that was not possible for αLGA. The difference between the two stems from different operational challenges, whose consequence is that steady-state operation is attained in the case of βLGA but not in that of αLGA. In the former case, the needle-like βLGA crystals, which exhibit no agglomeration, tend to be only slightly oversampled; in the latter case, the prismatic αLGA crystals undergo major agglomeration and hence are very difficult to suspend and effectively withdraw from the crystallizer.

Modeling and Optimization of the Para-Xylene Continuous Suspension Crystallization Separation Process via a Morphology Technique and a Multi-Dimensional Population Balance Equation

In this study, we carried out a para-xylene crystallization experiment at constant temperature and concentration levels. Throughout the process, the kinetics of nucleation, growth, breakage, and aggregation of para-xylene particles were measured and built using a morphological approach. An additional a three-stage continuous suspension crystallization separation experiment was carried out, the process for which was simulated using the population balance model based on correlated kinetic equations. The population balance equation was solved using an extended moment of classes algorithm, and the solving process was implemented in MATLAB. In this case, the predicted particle size distribution of the products matched well with the experiment. In order to provide references for the optimization of the industrial para-xylene crystallization process, a three-stage suspension crystallization separation experiment was designed and conducted, in which each crystallizer had a distinct operating temperature and mean residence time. The effects of operating parameters on the final product were investigated further. The proposed models and algorithms can also be applied in other cases and provide an alternative approach for optimizing continuous crystallization processes.

Improvement of drug processability in a connected continuous crystallizer system using formulation additive

Continuous crystallization in the presence of polymer additives is a promising method to omit some drug formulation steps by improving the technological and also pharmacological properties of crystalline active ingredients. Accordingly, this study focuses on developing an additive-assisted continuous crystallization process using polyvinylpyrrolidone in a connected ultrasonicated plug flow crystallizer and an overflow mixed suspension mixed product removal (MSMPR) crystallizer system. We aimed to improve the flowability characteristics of small, columnar primary plug flow crystallizer-produced acetylsalicylic acid crystals as a model drug by promoting their agglomeration in MSMPR crystallizer with polyvinylpyrrolidone. The impact of the cooling antisolvent crystallization process parameters (temperature, polymer amount, total flow rate) on product quality and quantity was investigated. Finally, a spatially segmented antisolvent dosing method was also evaluated. The developed technology enabled the manufacture of purified, constant quality products in a short startup period, even with an 85% yield. We found that a higher polymer amount (7.5–14%) could facilitate agglomeration resulting in “good” flowability without altering the favorable dissolution characteristics of the primary particles.

Continuous Crystallization Process of Cefminox Sodium in MSMPR Crystallizer

Continuous crystallization technology has attracted rising attention from chemists and material scientists. In this paper, cefminox sodium is selected as a model drug for consecutive antisolvent crystallization using a multistage mixed suspension mixed product removal (MSMPR) crystallizer. The effects of operating parameters on the product crystal particle size, crystal habit, and yield under steady-state conditions are investigated in detail: operating parameters such as the initial concentration of the crystallization solution, the volume ratio of the crystallization solution to antisolvent, the total flow rate, the amount of seed crystals added, the crystallization temperature, and the mixing rate. The kinetic solubility data of cefminox sodium in two binary aqueous mixed solvents at 278.15–303.15 K are determined by laser dynamic method, and two empirical models are subsequently borrowed to fit the obtained data. This work provides a new crystallization process for cefminox sodium. After optimization, the mass yield is increased to 89.11%, the average particle size Dv(50) is about 164 µm.

Phase Diagram Determination and Process Development for Continuous Antisolvent Crystallizations

The development of an antisolvent crystallization process requires the construction of an accurate phase diagram for this ternary system of compound, solvent and antisolvent, preferably as a function of temperature. This study gives an efficient methodology to systematically determine such antisolvent phase diagrams, exemplified with four model compounds: Sodium bromate, DL-Asparagine Monohydrate, Mefenamic acid and Lovastatin. Using clear point temperature measurements, single solvent and mixed solvent-antisolvent solubilities are obtained, showing strongly non-linear solubility dependencies as well as more complex solubility behaviour as a function of antisolvent fraction. A semi-empirical model equation is used to describe the phase diagram of the antisolvent crystallization system as a function of both temperature and antisolvent fraction. The phase diagram model then allows for the identification of condition ranges for optimal productivity, yield, and suspension density in continuous antisolvent crystallization processes.

Deep learning-based on-line image analysis for continuous industrial crystallization processes

In situ microscopic imaging is a useful tool in monitoring crystallization processes, including crystal nucleation, growth, aggregation and breakage, as well as possible polymorphic transition. To convert the qualitative information to be quantitative for the purpose of process optimization and control, accurate analysis of crystal images is essential. However, the accuracy of image segmentation with traditional methods is largely affected by many factors, including solid concentration and image quality. In this study, the deep learning technique using mask region-based convolutional neural network (Mask R-CNN) is investigated for the analysis of on-line images from an industrial crystallizer of 10 m3 operated in continuous mode with high solid concentration and overlapped particles. With detailed label points for each crystal and transfer learning technique, two models trained with 70,908 and 7,709 crystals respectively are compared for the effect of training data amount. The former model effectively segments the aggregated and overlapped crystals even at high solid concentrations. Moreover, it performs much better than the latter one and traditional multi-scale method both in terms of precision and recall, revealing the importance of large number of crystals in deep learning. Some geometrical characteristics of segmented crystals are also analyzed, involving equivalent diameter, circularity, and aspect ratio.

Insight into the fast crystallization process of SSZ-13 Zeolite by addition of K+ cation

Hydrothermal synthesis of SSZ-13 zeolite from precursors comprises many unanswered fundamental questions, in which understanding the effects of alkali metal cations on the structural rearrangement during the crystallizing period is an active and expanding area of research. Experimental results showed that the continuous crystallization process of SSZ-13 crystals can be easily hindered by the amorphous gel during the synthesis process. Accordingly, we carefully explored and repeated the crystallization period of SSZ-13 zeolite with different K+ mole ratios, which demonstrated significant effects on their crystallization behaviors with the easy breaking of amorphous gel state. The crystallization time was obviously shortened to 18 h. Theoretical calculation results also demonstrated that K+ cation in the precursor solution is more inclined to control the successive deprotonation process due to the higher activation energies for Si–O–Al bonds formation. Accordingly, the SSZ-13 zeolite sample tend to realize fast synthesis and transform into scattered crystals without aggregation by addition of K+ cation.

Evolutionary neural architecture search for surrogate models to enable optimization of industrial continuous crystallization process

Optimal performance of the crystallization process is of utmost importance for industries handling bulk commodity chemicals to pharmaceuticals. Such an optimization exercise becomes extremely time expensive as the mathematical models mimicking such complex processes involve the solution of Integro-Differential Population Balance Equations using High Resolution Finite Volume Methods. In order to build a fast and robust data based alternative model, a surrogate assisted approach using Artificial Neural Networks has been proposed here. To overcome the heuristics-based estimation of the hyper-parameters in ANNs, we aim to contribute a novel Neural Architecture Search strategy for the auto-tuning of hyper-parameters integrated with sample size determination techniques. While solving a multi-objective optimization of crystallization process ensuring maximum productivity, the results from surrogates are compared with those of a high-fidelity physics driven model, which reports five order of magnitude speed improvement without sacrificing much on accuracy.