Model-based optimization of batch- and continuous crystallization processes

Crystallization is an important separation process, extensively used in most chemical industries and especially in pharmaceutical manufacturing, either as a method of production or as a method of purification or recovery of solids. Typically, crystallization can have a considerable impact on tuning the critical quality attributes (CQAs), such as crystal size and shape distribution (CSSD), purity and polymorphic form, that impact the final product quality performance indicators and inherent end-use properties, along with the downstream processability. Therefore, one of the critical targets in controlled crystallization processes, is to engineer specific properties of the final product. The purpose of this research is to develop systematic computer-aided methodologies for the design of batch and continuous mixed suspension mixed product removal (MSMPR) crystallization processes through the implementation of simulation models and optimization frameworks. By manipulating the critical process parameters (CPPs), the achievable range of CQAs and the feasible design space (FDS) can be identified. Paracetamol in water and potassium dihydrogen phosphate (KDP) in water are considered as the model chemical systems.The studied systems are modeled utilizing single and multi-dimensional population balance models (PBMs). For the batch crystallization systems, single and multi-objective optimization was carried out for the determination of optimal operating trajectories by considering mean crystal size, the distribution s standard deviation and the aspect ratio of the population of crystals, as the CQAs represented in the objective functions. For the continuous crystallization systems, the attainable region theory is employed to identify the performance of multi-stage MSMPRs for various operating conditions and configurations. Multi-objective optimization is also applied to determine a Pareto optimal attainable region with respect to multiple CQAs. By identifying the FDS of a crystallization system, the manufacturing capabilities of the process can be explored, in terms of mode of operation, CPPs, and equipment configurations, that would lead to the selection of optimum operation strategies for the manufacturing of products with desired CQAs under certain manufacturing and supply chain constraints. Nevertheless, developing reliable first principle mathematical models for crystallization processes can be very challenging due to the complexity of the underlying phenomena, inherent to population balance models (PBMs). Therefore, a novel framework for parameter estimability for guaranteed optimal model reliability is also proposed and implemented. Two estimability methods are combined and compared: the first is based on a sequential orthogonalization of the local sensitivity matrix and the second is Sobol, a variance-based global sensitivities technic. The framework provides a systematic way to assess the quality of two nominal sets of parameters: one obtained from prior knowledge and the second obtained by simultaneous identification using global optimization. A multi-dimensional population balance model that accounts for the combined effects of different crystal growth modifiers/ impurities on the crystal size and shape distribution of needle-like crystals was used to validate the methodology. A cut-off value is identified from an incremental least square optimization procedure for both estimability methods, providing the required optimal subset of model parameters. In addition, a model-based design of experiments (MBDoE) methodology approach is also reported to determine the optimal experimental conditions yielding the most informative process data. The implemented methodology showed that, although noisy aspect ratio data were used, the eight most influential and least correlated parameters could be reliably identified out of twenty-three, leading to a crystallization model with enhanced prediction capability. A systematic model-based optimization methodology for the design of crystallization processes under the presence of multiple impurities is also investigated. Supersaturation control and impurity inclusion is combined to evaluate the effect on the product's CQAs. To this end, a morphological PBM is developed for the modelling of the cooling crystallization of pure KDP in aqueous solution, as a model system, under the presence of two competitive crystal growth modifiers/ additives: aluminum sulfate and sodium hexametaphosphate. The effect of the optimal temperature control with and without the additives on the CQAs is presented via utilizing multi-objective optimization. The results indicate that the attainable size and shape attributes, can be considerably enhanced due to advanced operation flexibility. Especially it is shown that the shape of the KDP crystals can be affected even by the presence of small quantity of additives and their morphology can be modified from needle-like to spherical, which is more favourable for processing. In addition, the multi-impurity PBM model is extended by the utilization of a high-resolution finite volume (HR-FV) scheme, instead of the standard method of moments (SMOM), in order for the full reconstruction and dynamic modelling of the crystal size and shape distribution to be enabled. The implemented methodology illustrated the capabilities of utilizing high-fidelity computational models for the investigation of crystallization processes in impure media for process and product design and optimization purposes

Computational Intelligence and Complexity Measures for Chaotic Information Processing

This dissertation investigates the application of computational intelligence methods in the analysis of nonlinear chaotic systems in the framework of many known and newly designed complex systems. Parallel comparisons are made between these methods. This provides insight into the difficult challenges facing nonlinear systems characterization and aids in developing a generalized algorithm in computing algorithmic complexity measures, Lyapunov exponents, information dimension and topological entropy. These metrics are implemented to characterize the dynamic patterns of discrete and continuous systems. These metrics make it possible to distinguish order from disorder in these systems. Steps required for computing Lyapunov exponents with a reorthonormalization method and a group theory approach are formalized. Procedures for implementing computational algorithms are designed and numerical results for each system are presented. The advance-time sampling technique is designed to overcome the scarcity of phase space samples and the buffer overflow problem in algorithmic complexity measure estimation in slow dynamics feedback-controlled systems. It is proved analytically and tested numerically that for a quasiperiodic system like a Fibonacci map, complexity grows logarithmically with the evolutionary length of the data block. It is concluded that a normalized algorithmic complexity measure can be used as a system classifier. This quantity turns out to be one for random sequences and a non-zero value less than one for chaotic sequences. For periodic and quasi-periodic responses, as data strings grow their normalized complexity approaches zero, while a faster deceasing rate is observed for periodic responses. Algorithmic complexity analysis is performed on a class of certain rate convolutional encoders. The degree of diffusion in random-like patterns is measured. Simulation evidence indicates that algorithmic complexity associated with a particular class of 1/n-rate code increases with the increase of the encoder constraint length. This occurs in parallel with the increase of error correcting capacity of the decoder. Comparing groups of rate-1/n convolutional encoders, it is observed that as the encoder rate decreases from 1/2 to 1/7, the encoded data sequence manifests smaller algorithmic complexity with a larger free distance value

Photophysical and Photocatalytic Properties of Covalent Organic Frameworks

This dissertation is most interested in how a class of materials known as covalent organic frameworks (COFs) can be designed to capture photon energy to initiate chemical reactions. Different COF designs change how long the energy is held, how it migrates, and how it is dispersed – and these differences can be used to change their performance as artificial photosynthesis platforms. Thus, it is helpful to have an informative discussion about the processes behind natural photosynthesis, that is, nature’s light harvesting strategies and photocatalytic schemes (Section 1.2) and will lead into an introduction of COFs and why they possess unique potential as artificial photosynthesis platforms (Section 1.3). Their beneficial physical qualities are complemented by understanding their electronic structures from theoretically predicted properties with specific focus on topological symmetry (Section 1.4). Synthesizing and characterizing COF systems then becomes an important consideration (Section 1.5) along with how their excited state behaviors are probed and interpreted at reaction timescales by ultrafast spectroscopic techniques (Section 1.6). Finally, a look is taken at how COF structure versatility adds unique potential in catalyst engineering (Section 1.7). The main body of this dissertation will present five main research projects that seek to test theoretical predictions, assess the impact of COF planarity, or fine tune electronic structures. To test theoretical predictions, “Tuning Photoexcited Charge Transfer in Imine-Linked Two-Dimensional Covalent Organic Frameworks, which involves exploring nodal symmetry in topologically similar COFs by varying monomers, is reported. This work has implications on charge separation characteristics of COFs which is important to retain activated catalytic sites for chemical reactions. The second project, “Impact of πConjugation Length on the Excited-State Dynamics of Star-Shaped Carbazole-π-Triazine Organic Chromophores,” doesn’t directly probe COF systems, but looks at the role of dihedral angles on intersystem crossing (ISC) rates in organic chromophores with similar star-shaped motifs like those often found in COFs. Another study on planarity is “Conjugation- and Aggregation-Directed Design of Covalent Organic Frameworks as White-Light-Emitting Diodes” that explores planar and non-planar COFs and the how this affects the deactivation of their photoexcited states. “Wavelength Dependent Excitonic Properties of Imine-Linked Covalent Organic Frameworks,” explores how subtle changes in donor-acceptor arrangements can lead to differences in excited state populations. Finally, the seminal work in this dissertation, “Imine Reversal Mediates Charge Separation and CO2 Photoreduction in Covalent Organic Frameworks,” explores the effect of the imine bond on photophysical and photocatalytic properties

Mechanical deformation of aperiodic organic systems in response to electrostatic fields: molecular piezoelectricity

Piezoelectricity as a bulk phenomenon in crystals is well understood from scientific, mathematical and engineering perspectives and has found wide use in many devices that convert electrical to mechanical energy or vice versa. Many strong piezoelectric compounds are inorganic, stiff ceramics that possess large piezoelectric coefficients but may have non-ideal properties for some applications e.g. related to cost, toxicity, biocompatibility, and incidence of fracture over time. Currently work is being done to create flexible and soft piezoelectric materials from organic compounds to make new, smart materials that could be used in medical, industrial, robotic and other technological applications. To this end the ability to screen for good organic piezoelectrics is necessary and requires a fundamental understanding of piezoelectricity at the molecular and nanoscale level. At the heart of macroscopic piezoelectric properties are inter- and intramolecular interactions and the different deformation response properties of these interactions in an applied electric field. This thesis investigates the linear response properties of molecules and small (aperiodic) systems the building blocks for macroscopic and nano-scale piezoelectric materials and develops methods and formalisms with roots in strain theory to help better understand which types of inter- and intramolecular interactions are best suited to yield piezoelectric systems with specifically tailored responses to applied electric fields. At the same time, the methods and formalism presented here have potential applications in the control of nanomachines via electric fields

Photonic Biosensors: Detection, Analysis and Medical Diagnostics

The role of nanotechnologies in personalized medicine is rising remarkably in the last decade because of the ability of these new sensing systems to diagnose diseases from early stages and the availability of continuous screenings to characterize the efficiency of drugs and therapies for each single patient. Recent technological advancements are allowing the development of biosensors in low-cost and user-friendly platforms, thereby overcoming the last obstacle for these systems, represented by limiting costs and low yield, until now. In this context, photonic biosensors represent one of the main emerging sensing modalities because of their ability to combine high sensitivity and selectivity together with real-time operation, integrability, and compatibility with microfluidics and electric circuitry for the readout, which is fundamental for the realization of lab-on-chip systems. This book, “Photonic Biosensors: Detection, Analysis and Medical Diagnostics”, has been published thanks to the contributions of the authors and collects research articles, the content of which is expected to assume an important role in the outbreak of biosensors in the biomedical field, considering the variety of the topics that it covers, from the improvement of sensors’ performance to new, emerging applications and strategies for on-chip integrability, aiming at providing a general overview for readers on the current advancements in the biosensing field

Rastertunneluntersuchungen auf strukturierten Edelmetall-(111)-Oberflächen

This thesis comprises low temperature UHV STM and STS experiments. Firstly, the electronic structure of decorated Ag(111) surfaces is explored, with focus on quasielectron lifetimes in Shockley surface states, made accessible by constructing monatomically deep hexagonal and triangular surface vacancies, by argon ion bombardment and tip-substrate impact. Within the resonators, the surface electrons are confined to broadened standing wave states, described well by a particle-in-a-box model. The linewidths show an approximately linear increase with binding energy. The two main contributions identified are the intrinsic lifetime, due to electron-electron and electron-phonon interaction, and lossy scattering at the boundary. An estimate of the relative strength shows that the latter is the limiting factor for lifetime. Comparison of various previously published lifetime data yields a consistent picture. Supplemental experiments on one-dimensional atomic chains and vacancy rows yield the surface state dispersion, and a transmission resonance peak at 1.7 V on the chain. Comparison to adsorbed Ag oligomers shows a decrease in energy with cluster size. Fowler-Nordheim spectroscopy finds a reduced sample work function on the nanostructures. The second part explores the adsorption characteristics of submonolayers of the perylene-3,4,9,10-tetracarboxylic-dianhydride (PTCDA) molecule on the vicinal Au(111) surfaces Au(788), Au(433), and Au(877). Substrate areas with a high step density prefer formation of molecular chains along the steps, with a strong preference for {111} type steps. Otherwise island formation in the known herringbone and square phases is seen. With increasing sample bias, the molecules undergo a contrast transition in STM, at an energy shifted by 0.35 V between the two phases. A DFT calculation suggests that the transition correlates to the LUMO, and the shift is due to a variation in intermolecular hydrogen bond strength.Die Arbeit beinhaltet Tieftemperatur-UHV-STM- und STS-Experimente. Die elektronische Struktur von dekorierten Ag(111)-Oberflächen wird untersucht, insbesondere Quasielektronen-Lebensdauern von Shockley-Oberflächenzuständen, die zugänglich gemacht werden durch Erzeugung einatomar tiefer sechs- und dreieckiger Fehlstellen, mittels Argonionen-Beschuss und Spitze-Probe-Kontakten. In den Resonatoren werden die Elektronen in energetisch verbreiterten Stehende-Welle-Zuständen gebunden, die gut durch ein Potentialtopfmodell beschrieben werden. Die Linienbreiten steigen etwa linear mit der Bindungsenergie. Die Hauptbeiträge sind die intrinsische Lebensdauer, aufgrund von Elektron-Elektron- und Elektron-Phonon-Wechselwirkungen, und verlustbehaftete Streuung an den Rändern. Eine Abschätzung der relativen Stärken zeigt, dass letztere den begrenzenden Faktor für die Lebensdauer darstellt. Vergleich mit Daten aus der Literatur ergibt somit ein konsistentes Bild. Experimente auf eindimensionalen Atom- und Fehlstellenketten ergeben die Dispersion des Oberflächenzustands, und auf den Atomketten eine Resonanz bei 1.7 V. Vergleich mit adsorbierten Ag-Oligomeren ergibt eine mit der Clustergröße sinkende Energie. Fowler-Nordheim-Spektroskopie zeigt eine Senkung der Austrittsarbeit auf den Ketten. Der zweite Teil behandelt die Adsorption von Submonolagen von Perylen-3,4,9,10-tetracarboxyl-dianhydrid (PTCDA) auf den Au(111)-vizinalen Oberflächen Au(788), Au(433) und Au(877). Substrate mit hoher Stufendichte begünstigen die Bildung von Molekülketten entlang der Stufen, vornehmlich des {111}-Typs. Andere Substrate zeigen Inselwachstum in den von Au(111) bekannten Quadrat- und Fischgrätenphasen. Ansteigende Probenspannung ergibt in STM einen Kontrastübergang, dessen Energie phasenabhängig um 0.35 V verschoben ist. Eine DFT-Rechnung identifiziert den Übergang mit dem LUMO und erklärt die Verschiebung durch geänderte Bindungsstärke der Wasserstoffbrücken

Characterization of bacteria, antibiotics of the fluoroquinolone type and their biological targets DNA and gyrase utilizing the unique potential of vibrational spectroscopy

Im Rahmen dieser Arbeit wurden verschiedene Schwingungsspektroskopische Techniken (IR-Absorptions-, Mikro-Raman-, UV-Resonanz-Raman-, oberflächenverstärkte und spitzenverstärkte Raman-Spektroskopie) dazu verwandt, Bakterien zu charakterisieren. Einen besonderen Einblick in die Zusammensetzung und Dynamik der äußeren Bakterienschicht bietet die erstmalige Anwendung der spitzenverstärkte Raman- Spektroskopie auf komplexe biologische Systeme wie Bakterien. Die Technik erlaubt die Gewinnung detaillierter chemischer Informationen mit hoher Ortsauflösung (wenige 10 nm). Ebenso konnten die Änderungen der chemischen Zusammensetzung während des Bakterienwachstums in Abwesenheit und in Gegenwart von Antibiotika aus der Gruppe der Fluorochinolone mit Hilfe schwingungsspektroskopischer Methoden verfolgt werden. Die Fluorochinolone greifen als biologische Zielstrukturen das Enzym Gyrase und die bakterielle DNA an, was schließlich zum Zelltod führt. Die am Wirkmechanismus beteiligten Komponenten Wirkstoff, DNA und Gyrase wurden zunächst in In-vitro-Experimenten schwingungsspektroskopisch charakterisiert und die Ergebnisse schließlich zur Interpretation der In-vivo-Experimente mit Bakterien verwandt. Mit Hilfe statistischer Auswertemethoden konnten die durch das Antibiotikum hervorgerufenen Änderungen in den Bakterienspektren auf Veränderungen an den Protein- und DNA-Bausteinen zurückgeführt werden, was den angenommenen Wirkmechanismus der Fluorochinolone unterstützt