Process Intensification through Spherical Crystallization: Novel Experimental and Modeling Approaches

Process intensification is defined as the use of innovative techniques and technologies to create sustainable solutions to industrial production difficulties. Continuous spherical crystallization is a process intensification technique that could resolve production issues for pharmaceutical and solids processing industries, consequently, allowing for the integration of upstream and downstream manufacturing units. Spherical crystallization is carried out through emulsion based crystallization and/or agglomeration in suspension of fine crystals to produce aggregates of improved bulk and micromeritic properties. The advantages of spherical crystallization include: (i) replacing downstream particle correction units (i.e., milling, granulation), (ii) providing control of crystalline properties by decoupling crystallization and agglomeration mechanisms, and (iii) reducing plant foot print and allowing for reconfigurable units. The overall aim of the thesis is to further develop the scientific understanding of spherical crystallization mechanisms and introduce a systematic approach for implementing continuous spherical crystallization as a smart manufacturing platform enabled by a quality-by-design framework. Experimentally, the thesis achieves: (i) better mechanistic understanding of spherical crystallization in semi-batch systems using process analytical technologies (PAT); and (ii) the assessment of the feasibility of continuous spherical crystallization in mixed suspension mixed product removal (MSMPR) and oscillatory flow baffled crystallizer (OFBC) systems. Computationally, a coupled population balance model is developed that leads to an optimization framework for bioavailability and manufacturability through spherical crystallization. Together the experimental and modeling approaches deliver a model-based framework for process intensification that can lead to adaptive manufacturing systems for high value-added particulate products

Particle size prediction in reactive precipitation processes

The aqueous reductive precipitation of palladium metal has been studied in semibatch stirred tank reactors. Scale-up from the bench scale to the 20 gallon scale has been studied using empirical scale-up rules. Some of the well-known difficulties and benefits associated with empirical methods for scale-up have been observed in this system.;In order to accurately predict particle size distributions (PSDs) in precipitation reactions, local variations in hydrodynamics, degree of supersaturation, and particle size distributions need to be accurately tracked. Discretized Population Balance (DPB) methods can accurately model precipitation process in well-mixed, uniform shear environments, but the implementation of DPB routines into CFD codes results in intractable problems.;One excellent alternative to the DPB is the Quadrature Method of Moments (QMOM), which provides a very useful closure to the moment-transformed population balance equations. The QMOM is very attractive for CFD applications because of its excellent accuracy and computational efficiency. Here, Monte Carlo (MC) simulations have been completed in order to validate the QMOM for aggregation processes. The accuracy of the QMOM has been demonstrated through excellent agreement with the MC simulations for aggregation by the hydrodynamic and Brownian kernels.;In order to realize the full benefits of the QMOM in a CFD simulation, accurate kinetic data for the fundamental steps in precipitation reactions are essential. Kinetic data for the precipitation of aniline hydrochloride have been experimentally characterized with the use of a static mixing tube. The final PSDs resulting from reactions at different initial levels of supersaturation have been measured. The QMOM, combined with an ODE solver, was coupled with an optimization routine in order to determine kinetic parameters for the precipitation reaction.;Using these kinetic parameters and the QMOM, the precipitation of aniline hydrochloride in a Taylor-Couette reactor has been simulated with a CFD code. This precipitation process has also been experimentally studied in a TC reactor, which had the same geometry as the simulated reactor and was operated under conditions identical to the simulated conditions. Results from the experiments are compared with simulated results

Modelling and control of crystal purity, size and shape distributions in crystallization processes

Crystallization is a key unit operation used for obtaining purified products by many process industries. The key properties of the crystalline products, such as size and shape distribution, purity and polymorphic form are controlled by the crystallization process. All these properties impact significantly the downstream operations such as drying or filtration. Therefore, monitoring and controlling this process is fundamental to ensure the quality of the final product. Process analytical technology (PAT) brings numerous new methods and opportunities in the process analytics and real time process monitoring systems, which can be integrated into the control algorithm and provide high level optimal control strategies as well as deeper understanding of the process. Process monitoring helps develop mathematical models which can, in one hand, help in better understanding the processes and consecvently the development and application of advanced control methods in order to achieve better product quality. In this work, image processing and image analysis based direct nucleation control (IA-DNC) is developed in order to investigate the evolution of the crystal properties, such as crystal size, and crystal shape distribution. The IA-DNC approach is also compared to alternative DNC techniques, in which particle number were measured by Focused Beam Reflectance Measurement (FBRM) in order to control crystal size. A control approach is introduced that control the nucleation and disappearance of crystals during cooling and heating segments related to the changes of the number of counts (measured by Particle Vision Measurment, so called PVM or combination of FBRM and PVM). The approach was applied to investigate crystallization of compounds with different behavior: potassium dihydrogen phosphate (KDP) water, contaminated KDP -water and Ascorbic acid water systems. The results demonstrate the application of imaging technique for model-free feedback control for tailoring crystal product properties. The second main aim of the thesis is to investigate and control crystallization processes in impure media in the presence of multiple impurities, with an impact on the crystal shape via growth kinetics. The broad impact of the crystal growth modifiers (impurities) on the growth kinetics is observed in real time by using in situ video imaging probe and real-time image analysis. A morphological population balance model is developed, which incorporates a multi-site, competitive adsorption mechanism of the impurities on the crystal faces. The kinetic parameters of primary nucleation, growth and impurity adsorption for a model system of potassium dihydrogen phosphate crystallization in water in the presence of two impurities, were estimated and validated with experimental results. It was demonstrated that the model can be used to describe the dynamic evolution of crystal properties, such as size and aspect ratio during crystallization for different impurity profiles in the system. Manual, feedback and hybrid feedback-feedforward control techniques are developed and investigated numerically for continuous processes, while model-based and model-free control approach for crystal shape are developed for batch processes. The developed morphological population balance model is implemented and applied in the model-based control approaches, which are suitable to describe multicomponent adsorption processes and their influence on the crystal shape. Case studies show the effectiveness of crystal growth modifiers based shape control techniques. Comparison of different control approaches shows the effectiveness of the techniques. The third part of the thesis deals with purification of crystals when adsorption of impurities on crystal surfaces and its incorporation into crystals are considered. A purification method, called competitive purity control (CPC) is proposed and investigated. A morphological population balance model, including nucleation, growth and competitive impurity adsorption kinetics is developed to describe the case when multiple impurities can adsorb competitively on the crystal surface. The model is also combined with liquid phase chemical reaction model, in order to investigate the purity control case when an additive is introduced in the system that reacts with the impurity forming a non-adsorbing reaction product. Both competitive purity control approaches proposed: the adsorption based competitive purity control (A-CPC) and the reaction based competitive purity control (R-CPC); are investigated using detailed numerical simulations then compared with the alternative widely used purification method, called recrystallization. In the last contribution chapter, an integrated process optimization of a continuous chemical reactor and crystallizer is performed and studied numerically. The purpose of this study is to show the way in which the byproduct produced in the chemical reactor may affect the crystallization process and how its negative effect can be reduced by applying integrated process optimization. Sensitivity analysis of the system was performed by considering the flow rate and the concentration of substances in the input stream of the chemical reactor as manipulated process variables. Model based integrated process optimization and the sensitivity analysis in order to obtain improved quality product in terms of crystal size, shape and purity

Quantifying the effects of mass transport in the curing and leaching of agglomerated ores using X-ray Microtomography

Agglomeration and subsequent curing are widely used as pre-treatments for ore prior to heap leaching as they both improve the permeability of the heap and bring leaching solution into close contact with the ore, initializing the leaching reactions. In this thesis, a low-grade copper sulphide ore was used for the experiments and two different agglomeration/leaching solutions were tested, namely a more standard sulphuric acid solution including ferric/ferrous ions, and a solution which also contained chloride ions. A novel image processing methodology was developed to track grains over both the curing and leaching process, taking into account the anisometric changes experienced by the agglomerates and the formation and depletion of species. A combination of XMT and SEM/EDX was used to characterise the chemical and mineralogical changes occurring over both processes. The formation and depletion of mineral components were quantified and tracked beyond the typical time scales used industrially, highlighting that the presence of chloride ions makes a substantial difference to the chemical and structural evolution of the agglomerates. Over the curing process, at least 20 days are required to perceive a significant degree of dissolution. Reprecipitation of metal containing species was observed, especially near the agglomerate surfaces. These precipitates are water-soluble species, and 50% of the initial sulphides were extracted from the agglomerates containing chloride ions, but only 20% from the other agglomerates after curing and water washing. A model of the agglomerate behaviour over the curing process is proposed based on the results observed from the XMT measurements. This model considers both the metal dissolution extent, as well as the reprecipitation of species due to water evaporation. The mathematical model is explained together with the computational approach used to solve it, and the simulation results are compared with the experimental results. This model is able to successfully predict the trends seen in the experiments, with the relative reaction and evaporation rates being a controlling factor. The leach performance was assessed for agglomerates leached using the same recipes used for the agglomeration stage. The compaction and changes in microporosity in the sample were quantified, showing that these changes do not significantly influence the leaching performance. By taking advantage of the more selective leaching that takes place when chloride ions are added to the leach solution, the leaching variability in the system was assessed. SEM/EDX measurements were then used to calibrate the XMT quantifications, isolating the dissolution of copper-containing grains from the pyrite dissolution. It was, thus, possible to quantify the surface kinetics of the hundreds of thousands of grains in the sample, with these kinetics being represented by a family of bi-modal curves. It was shown that the mass transport and mineralogical changes occurring throughout the curing and leaching processes could be quantified both at the grain-scale and the macro-scale by using the developed methodology for combining SEM/EDX measurements with XMT. By incorporating this data into particle scale and, ultimately, heap scale leach models, improved predictions and optimisation of leach performance can be made.Open Acces

The role of alveolar macrophages in biokinetics and biological effects of inhaled nanoparticles

Manche schwerlösliche Nanopartikel (NP) verursachen Lungenentzündungen nach Inhalation. Die histopathologischen Effekte verschiedener NP unterscheiden sich in der Art der initialen Entzündung und in den Langzeiteffekten nach chronischer Exposition. Überraschenderweise unterscheidet sich auch die pulmonale Clearance. Alveolarmakrophagen (AM) spielen sowohl in der pulmonalen Immunantwort als auch bei der Clearance eine vorrangige Rolle. Daher untersuchte diese Arbeit einerseits ob AM das Auflösungsverhalten von NP wie z.B. BaSO4 beeinflussen. Andererseits wurden polarisierte AM in Lungen NP-exponierter Tiere identifiziert, um eine Korrelation mit Langzeiteffekten zu erkennen. Unter sauren Bedingungen, wie sie in Lysosomen vorherrschen, zusammen mit den dynamischen Bedingungen der gut perfundierten Lunge, lösten sich BaSO4 NP deutlich schneller auf, als aufgrund ihres Löslichkeitsproduktes in Wasser erwartet. Immunohistochemische Untersuchungen von Lungengewebe ergaben eine Korrelation der relativen Zellzahl pro-inflammatorischer M1 und anti-inflammatorischer M2 AM mit akuter Entzündung nach 5-tägiger NP-Exposition, wie z.B. TiO2 oder CeO2. Es wurde keine Korrelation mit der Qualität der histopathologischen Effekte gefunden. Eine Prädiktion von Langzeiteffekten ist auf Basis der Daten nicht möglich. Das Verständnis der Mitwirkung von AM an der Entstehung krankhafter Lungenveränderungen könnte Biomarker identifizieren, die zu einer Vorhersage von Langzeiteffekten von NP befähigen.Some poorly-soluble nanoparticles (NPs) cause pulmonary inflammation upon inhalation. Histopathological effects of different NPs differ in types of initial inflammation as well as in long-term effects after chronic exposure. Surprisingly, also their lung clearance differs. Alveolar macrophages (AMs) are chiefly involved in pulmonary immune responses as well as in pulmonary clearance mechanisms. Thus, this dissertation project investigated on one hand whether AMs accelerate the biodissolution of e.g. BaSO4 NPs. On the other, it aimed at identifying AM subpopulations in lungs of animals exposed to NPs such as TiO2 or CeO2, and to find a correlation between early AM polarization and long-term outcome. It could be shown that under acidic conditions, as present in AM lysosomes, and in synergy with the dynamic conditions, which prevail in the well perfused lungs, BaSO4 NPs undergo accelerated biodissolution. Immunohistochemistry of lung specimen revealed a correlation of proinflammatory M1 and anti-inflammatory M2 AM relative numbers with acute inflammation after 5-day exposure to different NPs. A correlation with the quality of histopathological effects could not be found. Current data do not allow for the prediction of long-term outcome. An understanding of the contribution of AMs in the pathogenesis of pulmonary morphological changes might identify powerful, specific biomarkers, which potentially might allow for the prediction of the long-term outcome following NP exposure

Examining Mechanism of Toxicity of Copper Oxide Nanoparticles to Saccharomyces Cerevisiae and Caenorhabditis Elegans

Copper oxide nanoparticles (CuO NPs) are an up and coming technology increasingly being used in industrial and consumer applications and thus may pose risk to humans and the environment. In the present study, the toxic effects of CuO NPs were studied with two model organisms Saccharomyces cerevisiae and Caenorhabditis elegans. The role of released Cu ions during dissolution of CuO NPs in growth media were studied with freshly suspended, aged NPs, and the released Cu2+ fraction. Exposures to the different Cu treatments showed significant inhibition of S. cerevisiae cellular metabolic activity. Inhibition from the NPs was inversely proportional to size and was not fully explained by the released Cu ions. S. cerevisiae cultures grown under respiring conditions demonstrated greater metabolic sensitivity when exposed to CuO NPs compared to cultures undergoing fermentation. The cellular response to both CuO NPs and released Cu ions on gene expression was analyzed via microarray analysis after an acute exposure. It was observed that both copper exposures resulted in an increase in carbohydrate storage, a decrease in protein production, protein misfolding, increased membrane permeability, and cell cycle arrest. Cells exposed to NPs up-regulated genes related to oxidative phosphorylation but also may be inducing cell cycle arrest by a different mechanism than that observed with released Cu ions. The effect of CuO NPs on C. elegans was examined by using several toxicological endpoints. The CuO NPs displayed a more inhibitory effect, compared to copper sulfate, on nematode reproduction, feeding, and development. We investigated the effects of copper oxide nanoparticles and copper sulfate on neuronal health, a known tissue vulnerable to heavy metal toxicity. In transgenic C. elegans with neurons expressing a green fluorescent protein reporter, neuronal degeneration was observed in up to 10% of the population after copper oxide nanoparticle exposure. Additionally, nematode mutant strains containing gene knockouts in the divalent-metal transporters smf-1 and smf-2 showed increased tolerance to copper exposure. These results lend credence to the hypothesis that some toxicological effects to eukaryotic organisms from copper oxide nanoparticle exposure may be due to properties specific to the nanoparticles and not solely from the released copper ions

Crystallization process development and spherical agglomerates for pharmaceutical processing applications

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 102-107).The control of crystallization steps is essential in the production of many materials in the pharmaceutical, materials, and chemical industries. Additionally, due to increasing costs of research and development, reductions in manufacturing costs by moving from batch to continuous manufacturing are necessary to sustain profitability of the pharmaceutical industry. Two different projects were researched to progress towards this goal. The first was the demonstration of a continuous manufacturing platform. The second goal was the development of new crystallization techniques. Two continuous crystallization processes were developed as part of a demonstration unit for continuous manufacturing of Aliskiren hemifumarate. The first process was an anti-solvent crystallization of an intermediate. The second process was a continuous reactive crystallization developed for the final product. The processes were able to crystallize the two compounds with both high yield (>90%) and purity (>99%). Population balance modeling was performed and experimental data were fit to the model to obtain kinetic parameters for crystal growth and nucleation for both systems. The models were used to optimize crystal purity and yield of the products. In addition, this thesis describes two separate projects involving spherical agglomerates. In the first study, acetaminophen was shown to crystallize significantly faster in the presence of spherical agglomerates of lactose than single crystal lactose. An epitaxy study and molecular dynamics simulations showed that the (141̄)/(001) pairing of faces showed coincident lattice matching and favorable energy interaction. Maximizing the number of substrate faces available for interaction increases the chance for a lattice match between the substrate and the crystallizing material which can be useful for controlling and increasing nucleation kinetics. Finally, water-in-oil emulsions were used to make composite spherical agglomerates with two components: a heterosurface, and a target compound that does not typically crystallize as spherical agglomerates on its own. The generated composite agglomerates were relatively monodisperse and were characterized using optical microscopy, scanning electron microscopy, x-ray powder diffraction, and differential scanning calorimetry. This technique could potentially be applied to other hydrophilic compounds, in particular water-soluble pharmaceuticals compounds, in order to change crystal morphology to spherical agglomerates in order to simplify downstream processing.by Justin Quon.Ph.D

Enabling precision manufacturing of active pharmaceutical ingredients: workflow for seeded cooling continuous crystallisations

Continuous manufacturing is widely used for the production of commodity products. Currently, it is attracting increasing interest from the pharmaceutical industry and regulatory agencies as a means to provide a consistent supply of medicines. Crystallisation is a key operation in the isolation of the majority of pharmaceuticals and has been demonstrated in a continuous manner on a number of compounds using a range of processing technologies and scales. Whilst basic design principles for crystallisations and continuous processes are known, applying these in the context of rapid pharmaceutical process development with the associated constraints of speed to market and limited material availability is challenging. A systematic approach for continuous crystallisation process design is required to avoid the risk that decisions made on one aspect of the process conspire to make a later development step or steps, either for crystallisation or another unit operation, more difficult. In response to this industry challenge, an innovative system-wide approach to decision making has been developed to support rapid, systematic, and efficient continuous seeded cooling crystallisation process design. For continuous crystallisation, the goal is to develop and operate a robust, consistent process with tight control of particle attributes. Here, an innovative system-based workflow is presented that addresses this challenge. The aim, methodology, key decisions and output at each at stage are defined and a case study is presented demonstrating the successful application of the workflow for the rapid design of processes to produce kilo quantities of product with distinct, specified attributes suited to the pharmaceutical development environment. This work concludes with a vision for future applications of workflows in continuous manufacturing development to achieve rapid performance based design of pharmaceuticals