Modeling reaction kinetics and mass transfer in ozonation in water solutions

This dissertation is based on four articles dealing with modeling of ozonation. The literature part of this considers some models for hydrodynamics in bubble column simulation. A literature review of methods for obtaining mass transfer coefficients is presented. The methods presented to obtain mass transfer are general models and can be applied to any gas-liquid system. Ozonation reaction models and methods for obtaining stoichiometric coefficients and reaction rate coefficients for ozonation reactions are discussed in the final section of the literature part. In the first article, ozone gas-liquid mass transfer into water in a bubble column was investigated for different pH values. A more general method for estimation of mass transfer and Henry’s coefficient was developed from the Beltrán method. The ozone volumetric mass transfer coefficient and the Henry’s coefficient were determined simultaneously by parameter estimation using a nonlinear optimization method. A minor dependence of the Henry’s law constant on pH was detected at the pH range 4 - 9. In the second article, a new method using the axial dispersion model for estimation of ozone self-decomposition kinetics in a semi-batch bubble column reactor was developed. The reaction rate coefficients for literature equations of ozone decomposition and the gas phase dispersion coefficient were estimated and compared with the literature data. The reaction order in the pH range 7-10 with respect to ozone 1.12 and 0.51 the hydroxyl ion were obtained, which is in good agreement with literature. The model parameters were determined by parameter estimation using a nonlinear optimization method. Sensitivity analysis was conducted using object function method to obtain information about the reliability and identifiability of the estimated parameters. In the third article, the reaction rate coefficients and the stoichiometric coefficients in the reaction of ozone with the model component p-nitrophenol were estimated at low pH of water using nonlinear optimization. A novel method for estimation of multireaction model parameters in ozonation was developed. In this method the concentration of unknown intermediate compounds is presented as a residual COD (chemical oxygen demand) calculated from the measured COD and the theoretical COD for the known species. The decomposition rate of p-nitrophenol on the pathway producing hydroquinone was found to be about two times faster than the p-nitrophenol decomposition rate on the pathway producing 4- nitrocatechol. In the fourth article, the reaction kinetics of p-nitrophenol ozonation was studied in a bubble column at pH 2. Using the new reaction kinetic model presented in the previous article, the reaction kinetic parameters, rate coefficients, and stoichiometric coefficients as well as the mass transfer coefficient were estimated with nonlinear estimation. The decomposition rate of pnitrophenol was found to be equal both on the pathway producing hydroquinone and on the path way producing 4-nitrocathecol. Comparison of the rate coefficients with the case at initial pH 5 indicates that the p-nitrophenol degradation producing 4- nitrocathecol is more selective towards molecular ozone than the reaction producing hydroquinone. The identifiability and reliability of the estimated parameters were analyzed with the Marcov chain Monte Carlo (MCMC) method. @All rights reserved. No part of the publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of the author.

Reaction Kinetics and Viscosity Modelling in the Fusion Syntheses of Ca- and Ca/Mg-resinates

Rosin is a natural product from pine forests and it is used as a raw material in resinate syntheses. Resinates are polyvalent metal salts of rosin acids and especially Ca- and Ca/Mg- resinates find wide application in the printing ink industry. In this thesis, analytical methods were applied to increase general knowledge of resinate chemistry and the reaction kinetics was studied in order to model the non linear solution viscosity increase during resinate syntheses by the fusion method. Solution viscosity in toluene is an important quality factor for resinates to be used in printing inks. The concept of critical resinate concentration, c crit, was introduced to define an abrupt change in viscosity dependence on resinate concentration in the solution. The concept was then used to explain the non-inear solution viscosity increase during resinate syntheses. A semi empirical model with two estimated parameters was derived for the viscosity increase on the basis of apparent reaction kinetics. The model was used to control the viscosity and to predict the total reaction time of the resinate process. The kinetic data from the complex reaction media was obtained by acid value titration and by FTIR spectroscopic analyses using a conventional calibration method to measure the resinate concentration and the concentration of free rosin acids. A multivariate calibration method was successfully applied to make partial least square (PLS) models for monitoring acid value and solution viscosity in both mid-infrared (MIR) and near infrared (NIR) regions during the syntheses. The calibration models can be used for on line resinate process monitoring. In kinetic studies, two main reaction steps were observed during the syntheses. First a fast irreversible resination reaction occurs at 235 °C and then a slow thermal decarboxylation of rosin acids starts to take place at 265 °C. Rosin oil is formed during the decarboxylation reaction step causing significant mass loss as the rosin oil evaporates from the system while the viscosity increases to the target level. The mass balance of the syntheses was determined based on the resinate concentration increase during the decarboxylation reaction step. A mechanistic study of the decarboxylation reaction was based on the observation that resinate molecules are partly solvated by rosin acids during the syntheses. Different decarboxylation mechanisms were proposed for the free and solvating rosin acids. The deduced kinetic model supported the analytical data of the syntheses in a wide resinate concentration region, over a wide range of viscosity values and at different reaction temperatures. In addition, the application of the kinetic model to the modified resinate syntheses gave a good fit. A novel synthesis method with the addition of decarboxylated rosin (i.e. rosin oil) to the reaction mixture was introduced. The conversion of rosin acid to resinate was increased to the level necessary to obtain the target viscosity for the product at 235 °C. Due to a lower reaction temperature than in traditional fusion synthesis at 265 °C, thermal decarboxylation is avoided. As a consequence, the mass yield of the resinate syntheses can be increased from ca. 70% to almost 100% by recycling the added rosin oil.

A generalized 1D particle transport method for convection diffusion reaction model

This work is devoted to the development of numerical method to deal with convection diffusion dominated problem with reaction term, non - stiff chemical reaction and stiff chemical reaction. The technique is based on the unifying Eulerian - Lagrangian schemes (particle transport method) under the framework of operator splitting method. In the computational domain, the particle set is assigned to solve the convection reaction subproblem along the characteristic curves created by convective velocity. At each time step, convection, diffusion and reaction terms are solved separately by assuming that, each phenomenon occurs separately in a sequential fashion. Moreover, adaptivities and projection techniques are used to add particles in the regions of high gradients (steep fronts) and discontinuities and transfer a solution from particle set onto grid point respectively. The numerical results show that, the particle transport method has improved the solutions of CDR problems. Nevertheless, the method is time consumer when compared with other classical technique e.g., method of lines. Apart from this advantage, the particle transport method can be used to simulate problems that involve movingsteep/smooth fronts such as separation of two or more elements in the system.

Combination of catalyst development and chemical reaction engineering : a key aspect to improve the hydrogen peroxide direct synthesis

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Finnish stock market reaction to quarterly earnings announcements

This thesis examines the stock market reactions to quarterly earnings announcements. The study covers the OMX Helsinki 25 index companies for the years 2007–2010. The stock market response to quarterly earnings announcements is tested by employing the event study –methodology and daily stock returns of Finnish listed companies. The thesis provides evidence that stock prices react to earnings announcements that exceed or fall below analyst forecasts. The most liquid stocks earn higher returns around positive earnings news than less traded stocks, which supports the evidence from previous studies. This thesis finds evidence for the authorization to sell stocks short reducing the post–earnings announcement drift induced by negative earnings news. In addition, the market’s reaction to earnings announcements seems to quicken during economic turmoil.

Design and testing of an armature-reaction-compensated permanent magnet synchronous generator for island operation

At present, permanent magnet synchronous generators (PMSGs) are of great interest. Since they do not have electrical excitation losses, the highly efficient, lightweight and compact PMSGs equipped with damper windings work perfectly when connected to a network. However, in island operation, the generator (or parallel generators) alone is responsible for the building up of the network and maintaining its voltage and reactive power level. Thus, in island operation, a PMSG faces very tight constraints, which are difficult to meet, because the flux produced by the permanent magnets (PMs) is constant and the voltage of the generator cannot be controlled. Traditional electrically excited synchronous generators (EESGs) can easily meet these constraints, because the field winding current is controllable. The main drawback of the conventional EESG is the relatively high excitation loss. This doctoral thesis presents a study of an alternative solution termed as a hybrid excitation synchronous generator (HESG). HESGs are a special class of electrical machines, where the total rotor current linkage is produced by the simultaneous action of two different excitation sources: the electrical and permanent magnet (PM) excitation. An overview of the existing HESGs is given. Several HESGs are introduced and compared with the conventional EESG from technical and economic points of view. In the study, the armature-reaction-compensated permanent magnet synchronous generator with alternated current linkages (ARC-PMSG with ACL) showed a better performance than the other options. Therefore, this machine type is studied in more detail. An electromagnetic design and a thermal analysis are presented. To verify the operation principle and the electromagnetic design, a down-sized prototype of 69 kVA apparent power was built. The experimental results are demonstrated and compared with the predicted ones. A prerequisite for an ARC-PMSG with ACL is an even number of pole pairs (p = 2, 4, 6, …) in the machine. Naturally, the HESG technology is not limited to even-pole-pair machines. However, the analysis of machines with p = 3, 5, 7, … becomes more complicated, especially if analytical tools are used, and is outside the scope of this thesis. The contribution of this study is to propose a solution where an ARC-PMSG replaces an EESG in electrical power generation while meeting all the requirements set for generators given for instance by ship classification societies, particularly as regards island operation. The maximum power level when applying the technology studied here is mainly limited by the economy of the machine. The larger the machine is, the smaller is the efficiency benefit. However, it seems that machines up to ten megawatts of power could benefit from the technology. However, in low-power applications, for instance in the 500 kW range, the efficiency increase can be significant.

Improving the competitiveness of electrolytic Zinc process by chemical reaction engineering approach

This doctoral thesis describes the development work performed on the leachand purification sections in the electrolytic zinc plant in Kokkola to increase the efficiency in these two stages, and thus the competitiveness of the plant. Since metallic zinc is a typical bulk product, the improvement of the competitiveness of a plant was mostly an issue of decreasing unit costs. The problems in the leaching were low recovery of valuable metals from raw materials, and that the available technology offered complicated and expensive processes to overcome this problem. In the purification, the main problem was consumption of zinc powder - up to four to six times the stoichiometric demand. This reduced the capacity of the plant as this zinc is re-circulated through the electrolysis, which is the absolute bottleneck in a zinc plant. Low selectivity gave low-grade and low-value precipitates for further processing to metallic copper, cadmium, cobalt and nickel. Knowledge of the underlying chemistry was poor and process interruptions causing losses of zinc production were frequent. Studies on leaching comprised the kinetics of ferrite leaching and jarosite precipitation, as well as the stability of jarosite in acidic plant solutions. A breakthrough came with the finding that jarosite could precipitate under conditions where ferrite would leach satisfactorily. Based on this discovery, a one-step process for the treatment of ferrite was developed. In the plant, the new process almost doubled the recovery of zinc from ferrite in the same equipment as the two-step jarosite process was operated in at that time. In a later expansion of the plant, investment savings were substantial compared to other technologies available. In the solution purification, the key finding was that Co, Ni, and Cu formed specific arsenides in the “hot arsenic zinc dust” step. This was utilized for the development of a three-step purification stage based on fluidized bed technology in all three steps, i.e. removal of Cu, Co and Cd. Both precipitation rates and selectivity increased, which strongly decreased the zinc powder consumption through a substantially suppressed hydrogen gas evolution. Better selectivity improved the value of the precipitates: cadmium, which caused environmental problems in the copper smelter, was reduced from 1-3% reported normally down to 0.05 %, and a cobalt cake with 15 % Co was easily produced in laboratory experiments in the cobalt removal. The zinc powder consumption in the plant for a solution containing Cu, Co, Ni and Cd (1000, 25, 30 and 350 mg/l, respectively), was around 1.8 g/l; i.e. only 1.4 times the stoichiometric demand – or, about 60% saving in powder consumption. Two processes for direct leaching of the concentrate under atmospheric conditions were developed, one of which was implemented in the Kokkola zinc plant. Compared to the existing pressure leach technology, savings were obtained mostly in investment. The scientific basis for the most important processes and process improvements is given in the doctoral thesis. This includes mathematical modeling and thermodynamic evaluation of experimental results and hypotheses developed. Five of the processes developed in this research and development program were implemented in the plant and are still operated. Even though these processes were developed with the focus on the plant in Kokkola, they can also be implemented at low cost in most of the zinc plants globally, and have thus a great significance in the development of the electrolytic zinc process in general.

Stock Market reaction to the CSR announcements of American fast food companies

The purpose of this study is to examine whether Corporate Social Responsibility (CSR) announcements of the three biggest American fast food companies (McDonald’s, YUM! Brands and Wendy’s) have any effect on their stock returns as well as on the returns of the industry index (Dow Jones Restaurants and Bars). The time period under consideration starts on 1st of May 2001 and ends on 17th of October 2013. The stock market reaction is tested with an event study utilizing CAPM. The research employs the daily stock returns of the companies, the index and the benchmarks (NASDAQ and NYSE). The test of combined announcements did not reveal any significant effect on the index and McDonald’s. However the stock returns of Wendy’s and YUM! Brands reacted negatively. Moreover, the company level analyses showed that to their own CSR releases McDonald’s stock returns respond positively, YUM! Brands reacts negatively and Wendy’s does not have any reaction. Plus, it was found that the competitors of the announcing company tend to react negatively to all the events. Furthermore, the division of the events into sustainability categories showed statistically significant negative reaction from the Index, McDonald’s and YUM! Brands towards social announcements. At the same time only the index was positively affected by to the economic and environmental CSR news releases.

Att använda Choice Reaction Time (CRT) paradigmet för att differentiera mellan sexualförbrytare med barnoffer, sexualförbrytare med vuxna offer, förbrytare skyldiga till andra brott än sexualbrott, samt kontroller från normalpopulationen

Pro graduavhanlingens svenska sammanfattning

Quantitative refinement of reaction-based biomodels

In the field of molecular biology, scientists adopted for decades a reductionist perspective in their inquiries, being predominantly concerned with the intricate mechanistic details of subcellular regulatory systems. However, integrative thinking was still applied at a smaller scale in molecular biology to understand the underlying processes of cellular behaviour for at least half a century. It was not until the genomic revolution at the end of the previous century that we required model building to account for systemic properties of cellular activity. Our system-level understanding of cellular function is to this day hindered by drastic limitations in our capability of predicting cellular behaviour to reflect system dynamics and system structures. To this end, systems biology aims for a system-level understanding of functional intraand inter-cellular activity. Modern biology brings about a high volume of data, whose comprehension we cannot even aim for in the absence of computational support. Computational modelling, hence, bridges modern biology to computer science, enabling a number of assets, which prove to be invaluable in the analysis of complex biological systems, such as: a rigorous characterization of the system structure, simulation techniques, perturbations analysis, etc. Computational biomodels augmented in size considerably in the past years, major contributions being made towards the simulation and analysis of large-scale models, starting with signalling pathways and culminating with whole-cell models, tissue-level models, organ models and full-scale patient models. The simulation and analysis of models of such complexity very often requires, in fact, the integration of various sub-models, entwined at different levels of resolution and whose organization spans over several levels of hierarchy. This thesis revolves around the concept of quantitative model refinement in relation to the process of model building in computational systems biology. The thesis proposes a sound computational framework for the stepwise augmentation of a biomodel. One starts with an abstract, high-level representation of a biological phenomenon, which is materialised into an initial model that is validated against a set of existing data. Consequently, the model is refined to include more details regarding its species and/or reactions. The framework is employed in the development of two models, one for the heat shock response in eukaryotes and the second for the ErbB signalling pathway. The thesis spans over several formalisms used in computational systems biology, inherently quantitative: reaction-network models, rule-based models and Petri net models, as well as a recent formalism intrinsically qualitative: reaction systems. The choice of modelling formalism is, however, determined by the nature of the question the modeler aims to answer. Quantitative model refinement turns out to be not only essential in the model development cycle, but also beneficial for the compilation of large-scale models, whose development requires the integration of several sub-models across various levels of resolution and underlying formal representations.

Bio and chemocatalysis for stereo and regioselective one-pot reaction applications

The development of cost efficient, selective and sustainable chemical processes for production of chiral building blocks is of great importance in synthetic and industrial organic chemistry. One way to reach these objectives is to carry out several reactions steps in one vessel at one time. Furthermore, when this kind of one-pot multi step reactions are catalyzed by heterogeneous chemo- and bio-catalysts, which can be separated from the reaction products by filtration, practical access to chiral small molecules for further utilization can be obtained. The initial reactions studied in this thesis are the two step dynamic kinetic resolution of rac-2-hydroxy-1-indanone and the regioselective hydrogenation of 1,2-indanedione. These reactions are then combined in a new heterogeneously catalyzed one-pot reaction sequence enabling simple recovery of the catalysts by filtration, facilitating simple reaction product isolation. Conclusively, the readily available 1,2-indanedione is by the presented one-pot sequence, utilizing heterogeneous enzyme and transition metal based catalysts, transferred with high regio- and stereoselectivity to a useful chiral vicinal hydroxyl ketone structure. Additional and complementary investigation of homogeneous half-sandwich ruthenium complexes for catalyzing the epimerization of chiral secondary alcohols of five natural products containing additional non-functionalized stereocenters was conducted. In principle, this kind of epimerization reactions of single stereocenters could be utilized for converting inexpensive starting materials, containing other stereogenic centers, into diastereomeric mixtures from which more valuable compounds can be isolated by traditional isolation techniques.

Implementation of Quantitative Reaction-based Model Refinement

Building a computational model for complex biological systems is an iterative process. It starts from an abstraction of the process and then incorporates more details regarding the specific biochemical reactions which results in the change of the model fit. Meanwhile, the model’s numerical properties such as its numerical fit and validation should be preserved. However, refitting the model after each refinement iteration is computationally expensive resource-wise. There is an alternative approach which ensures the model fit preservation without the need to refit the model after each refinement iteration. And this approach is known as quantitative model refinement. The aim of this thesis is to develop and implement a tool called ModelRef which does the quantitative model refinement automatically. It is both implemented as a stand-alone Java application and as one of Anduril framework components. ModelRef performs data refinement of a model and generates the results in two different well known formats (SBML and CPS formats). The development of this tool successfully reduces the time and resource needed and the errors generated as well by traditional reiteration of the whole model to perform the fitting procedure.

Computational models for and from biology : simple gene assembly and reaction systems

The advancement of science and technology makes it clear that no single perspective is any longer sufficient to describe the true nature of any phenomenon. That is why the interdisciplinary research is gaining more attention overtime. An excellent example of this type of research is natural computing which stands on the borderline between biology and computer science. The contribution of research done in natural computing is twofold: on one hand, it sheds light into how nature works and how it processes information and, on the other hand, it provides some guidelines on how to design bio-inspired technologies. The first direction in this thesis focuses on a nature-inspired process called gene assembly in ciliates. The second one studies reaction systems, as a modeling framework with its rationale built upon the biochemical interactions happening within a cell. The process of gene assembly in ciliates has attracted a lot of attention as a research topic in the past 15 years. Two main modelling frameworks have been initially proposed in the end of 1990s to capture ciliates’ gene assembly process, namely the intermolecular model and the intramolecular model. They were followed by other model proposals such as templatebased assembly and DNA rearrangement pathways recombination models. In this thesis we are interested in a variation of the intramolecular model called simple gene assembly model, which focuses on the simplest possible folds in the assembly process. We propose a new framework called directed overlap-inclusion (DOI) graphs to overcome the limitations that previously introduced models faced in capturing all the combinatorial details of the simple gene assembly process. We investigate a number of combinatorial properties of these graphs, including a necessary property in terms of forbidden induced subgraphs. We also introduce DOI graph-based rewriting rules that capture all the operations of the simple gene assembly model and prove that they are equivalent to the string-based formalization of the model. Reaction systems (RS) is another nature-inspired modeling framework that is studied in this thesis. Reaction systems’ rationale is based upon two main regulation mechanisms, facilitation and inhibition, which control the interactions between biochemical reactions. Reaction systems is a complementary modeling framework to traditional quantitative frameworks, focusing on explicit cause-effect relationships between reactions. The explicit formulation of facilitation and inhibition mechanisms behind reactions, as well as the focus on interactions between reactions (rather than dynamics of concentrations) makes their applicability potentially wide and useful beyond biological case studies. In this thesis, we construct a reaction system model corresponding to the heat shock response mechanism based on a novel concept of dominance graph that captures the competition on resources in the ODE model. We also introduce for RS various concepts inspired by biology, e.g., mass conservation, steady state, periodicity, etc., to do model checking of the reaction systems based models. We prove that the complexity of the decision problems related to these properties varies from P to NP- and coNP-complete to PSPACE-complete. We further focus on the mass conservation relation in an RS and introduce the conservation dependency graph to capture the relation between the species and also propose an algorithm to list the conserved sets of a given reaction system.