Solid-state reference and ion-selective electrodes : towards portable potentiometric sensing

Potentiometric sensors are very attractive tools for chemical analysis because of their simplicity, low power consumption and low cost. They are extensively used in clinical diagnostics and in environmental monitoring. Modern applications of both fields require improvements in the conventional construction and in the performance of the potentiometric sensors, as the trends are towards portable, on-site diagnostics and autonomous sensing in remote locations. The aim of this PhD work was to improve some of the sensor properties that currently hamper the implementation of the potentiometric sensors in modern applications. The first part of the work was concentrated on the development of a solid-state reference electrode (RE) compatible with already existing solid-contact ion-selective electrodes (ISE), both of which are needed for all-solid-state potentiometric sensing systems. A poly(vinyl chloride) membrane doped with a moderately lipophilic salt, tetrabutylammonium-tetrabutylborate (TBA-TBB), was found to show a satisfactory stability of potential in sample solutions with different concentrations. Its response time was nevertheless slow, as it required several minutes to reach the equilibrium. The TBA-TBB membrane RE worked well together with solid-state ISEs in several different situations and on different substrates enabling a miniature design. Solid contacts (SC) that mediate the ion-to-electron transduction are crucial components of well-functioning potentiometric sensors. This transduction process converting the ionic conduction of an ion-selective membrane to the electronic conduction in the circuit was studied with the help of electrochemical impedance spectroscopy (EIS). The solid contacts studied were (i) the conducting polymer (CP) poly(3,4-ethylienedioxythiophene) (PEDOT) and (ii) a carbon cloth having a high surface area. The PEDOT films were doped with a large immobile anion poly(styrene sulfonate) (PSS-) or with a small mobile anion Cl-. As could be expected, the studied PEDOT solid-contact mediated the ion-toelectron transduction more efficiently than the bare glassy carbon substrate, onto which they were electropolymerized, while the impedance of the PEDOT films depended on the mobility of the doping ion and on the ions in the electrolyte. The carbon cloth was found to be an even more effective ion-to-electron transducer than the PEDOT films and it also proved to work as a combined electrical conductor and solid contact when covered with an ion-selective membrane or with a TBA-TBB-based reference membrane. The last part of the work was focused on improving the reproducibility and the potential stability of the SC-ISEs, a problem that culminates to the stability of the standard potential E°. It was proven that the E° of a SC-ISE with a conducting polymer as a solid contact could be adjusted by reducing or oxidizing the CP solid contact by applying current pulses or a potential to it, as the redox state of the CP solid-contact influences the overall potential of the ISE. The slope and thus the analytical performance of the SC-ISEs were retained despite the adjustment of the E°. The shortcircuiting of the SC-ISE with a conventional large-capacitance RE was found to be a feasible instrument-free method to control the E°. With this method, the driving force for the oxidation/reduction of the CP was the potential difference between the RE and the SC-ISE, and the position of the adjusted potential could be controlled by choosing a suitable concentration for the short-circuiting electrolyte. The piece-to-piece reproducibility of the adjusted potential was promising, and the day-today reproducibility for a specific sensor was excellent. The instrumentfree approach to control the E° is very attractive considering practical applications.

Maakaasupolttimen säätöjärjestelmän kehittäminen

Jatkuvasti kiristyvät päästörajoitukset pakottavat teollisuuden kehittämään uusia ratkaisuja päästöjen vähentämiseksi. Hiilimonoksidin ja typen oksidien päästörajoitukset ovat erityi-sen tiukat esimerkiksi Kiinassa ja Yhdysvalloissa. Maakaasun ja ilman epätäydellisessä pa-lamisessa muodostuu hiilimonoksidia ja typen oksideja. Käytännön sovelluksissa palaminen on lähes aina epätäydellistä polttoaineen ja ilman epätäydellisen sekoittumisen takia, joten palamisreaktiossa muodostuva savukaasu sisältää edellä mainittuja haitallisia komponentteja lähes poikkeuksetta. Savukaasua voidaan puhdistaa erilaisilla menetelmillä ennen sen pää-tymistä ympäristöön. Tässä diplomityössä esitellään maakaasupoltinjärjestelmän keskeiset komponentit ja aihee-seen liittyvät tarpeelliset käsitteet sekä suunnitellaan polttoaine-ilma-seossuhdesäätö eräälle maakaasupoltinjärjestelmälle. Säädön ensisijaisena tavoitteena on pitää seossuhde mahdolli-simman tarkasti halutussa arvossa savukaasun puhdistuksen kannalta. Lisäksi säädön on tarkoitus taata mahdollisimman hyvä suorituskyky transienttitilanteissa. Järjestelmän eri osien toiminta mallinnetaan ja analysoidaan. Mallinnuksen perusteella suunnitellaan ja simu-loidaan säätöjärjestelmä. Suunniteltu säätöjärjestelmä toteutetaan osaksi polttolaitoksen automaatiojärjestelmää. Mittaustulokset osoittavat, että päästöjen kannalta säätö pitää seossuhteen riittävän tarkasti halutussa arvossa: hiilimonoksidin ja typen oksidien päästöt ovat asetettujen rajojen sisällä. Testiajojen perusteella prosessi on kuitenkin erittäin häiriöinen ja transienttitilanteissa ei saavuteta simulointien mukaista suorituskykyä.

Fuzzy real option analysis in patent related decision making and patent valuation

The shift towards a knowledge-based economy has inevitably prompted the evolution of patent exploitation. Nowadays, patent is more than just a prevention tool for a company to block its competitors from developing rival technologies, but lies at the very heart of its strategy for value creation and is therefore strategically exploited for economic pro t and competitive advantage. Along with the evolution of patent exploitation, the demand for reliable and systematic patent valuation has also reached an unprecedented level. However, most of the quantitative approaches in use to assess patent could arguably fall into four categories and they are based solely on the conventional discounted cash flow analysis, whose usability and reliability in the context of patent valuation are greatly limited by five practical issues: the market illiquidity, the poor data availability, discriminatory cash-flow estimations, and its incapability to account for changing risk and managerial flexibility. This dissertation attempts to overcome these impeding barriers by rationalizing the use of two techniques, namely fuzzy set theory (aiming at the first three issues) and real option analysis (aiming at the last two). It commences with an investigation into the nature of the uncertainties inherent in patent cash flow estimation and claims that two levels of uncertainties must be properly accounted for. Further investigation reveals that both levels of uncertainties fall under the categorization of subjective uncertainty, which differs from objective uncertainty originating from inherent randomness in that uncertainties labelled as subjective are highly related to the behavioural aspects of decision making and are usually witnessed whenever human judgement, evaluation or reasoning is crucial to the system under consideration and there exists a lack of complete knowledge on its variables. Having clarified their nature, the application of fuzzy set theory in modelling patent-related uncertain quantities is effortlessly justified. The application of real option analysis to patent valuation is prompted by the fact that both patent application process and the subsequent patent exploitation (or commercialization) are subject to a wide range of decisions at multiple successive stages. In other words, both patent applicants and patentees are faced with a large variety of courses of action as to how their patent applications and granted patents can be managed. Since they have the right to run their projects actively, this flexibility has value and thus must be properly accounted for. Accordingly, an explicit identification of the types of managerial flexibility inherent in patent-related decision making problems and in patent valuation, and a discussion on how they could be interpreted in terms of real options are provided in this dissertation. Additionally, the use of the proposed techniques in practical applications is demonstrated by three fuzzy real option analysis based models. In particular, the pay-of method and the extended fuzzy Black-Scholes model are employed to investigate the profitability of a patent application project for a new process for the preparation of a gypsum-fibre composite and to justify the subsequent patent commercialization decision, respectively; a fuzzy binomial model is designed to reveal the economic potential of a patent licensing opportunity.

The Forecast Performance of Model-Free Implied Volatility: Evidence from DAX Index Options

Volatility has a central role in various theoretical and practical applications in financial markets. These include the applications related to portfolio theory, derivatives pricing and financial risk management. Both theoretical and practical applications require good estimates and forecasts for the asset return volatility. The goal of this study is to examine the forecast performance of one of the more recent volatility measures, model-free implied volatility. Model-free implied volatility is extracted from the prices in the option markets, and it aims to provide an unbiased estimate for the market’s expectation on the future level of volatility. Since it is extracted from the option prices, model-free implied volatility should contain all the relevant information that the market participants have. Moreover, model-free implied volatility requires less restrictive assumptions than the commonly used Black-Scholes implied volatility, which means that it should be less biased estimate for the market’s expectations. Therefore, it should also be a better forecast for the future volatility. The forecast performance of model-free implied volatility is evaluated by comparing it to the forecast performance of Black-Scholes implied volatility and GARCH(1,1) forecast. Weekly forecasts for six years period were calculated for the forecasted variable, German stock market index DAX. The data consisted of price observations for DAX index options. The forecast performance was measured using econometric methods, which aimed to capture the biasedness, accuracy and the information content of the forecasts. The results of the study suggest that the forecast performance of model-free implied volatility is superior to forecast performance of GARCH(1,1) forecast. However, the results also suggest that the forecast performance of model-free implied volatility is not as good as the forecast performance of Black-Scholes implied volatility, which is against the hypotheses based on theory. The results of this study are consistent with the majority of prior research on the subject.

Rigid body dynamics and Kalman filtering

X-ray computed log tomography has always been applied for qualitative reconstructions. In most cases, a series of consecutive slices of the timber are scanned to estimate the 3D image reconstruction of the entire log. However, the unexpected movement of the timber under study influences the quality of image reconstruction since the position and orientation of some scanned slices can be incorrectly estimated. In addition, the reconstruction time remains a significant challenge for practical applications. The present study investigates the possibility to employ modern physics engines for the problem of estimating the position of a moving rigid body and its scanned slices which are subject to X-ray computed tomography. The current work includes implementations of the extended Kalman filter and an algebraic reconstruction method for fan-bean computer tomography. In addition, modern techniques such as NVidia PhysX and CUDA are used in current study. As the result, it is numerically shown that it is possible to apply the extended Kalman filter together with a real-time physics engine, known as PhysX, in order to determine the position of a moving object. It is shown that the position of the rigid body can be determined based only on reconstructions of its slices. However, the simulation of the body movement sometimes is subject to an error during Kalman filter employment as PhysX is not always able to continue simulating the movement properly because of incorrect state estimation.

Pretraining Convolutional Neural Networks for Visual Recognition

Convolutional Neural Networks (CNN) have become the state-of-the-art methods on many large scale visual recognition tasks. For a lot of practical applications, CNN architectures have a restrictive requirement: A huge amount of labeled data are needed for training. The idea of generative pretraining is to obtain initial weights of the network by training the network in a completely unsupervised way and then fine-tune the weights for the task at hand using supervised learning. In this thesis, a general introduction to Deep Neural Networks and algorithms are given and these methods are applied to classification tasks of handwritten digits and natural images for developing unsupervised feature learning. The goal of this thesis is to find out if the effect of pretraining is damped by recent practical advances in optimization and regularization of CNN. The experimental results show that pretraining is still a substantial regularizer, however, not a necessary step in training Convolutional Neural Networks with rectified activations. On handwritten digits, the proposed pretraining model achieved a classification accuracy comparable to the state-of-the-art methods.

Calculation of the carbon footprint of Finnish barley products - methodology and possible applications

The purpose of this thesis was to define how product carbon footprint analysis and its results can be used in company's internal development as well as in customer and interest group guidance, and how these factors are related to corporate social responsibility. From-cradle-to-gate carbon footprint was calculated for three products; Torino Whole grain barley, Torino Pearl barley, and Elovena Barley grit & oat bran, all of them made of Finnish barley. The carbon footprint of the Elovena product was used to determine carbon footprints for industrial kitchen cooked porridge portions. The basic calculation data was collected from several sources. Most of the data originated from Raisio Group's contractual farmers and Raisio Group's cultivation, processing and packaging specialists. Data from national and European literature and database sources was also used. The electricity consumption for porridge portions' carbon footprint calculations was determined with practical measurements. The carbon footprint calculations were conducted according to the ISO 14044 standard, and the PAS 2050 guide was also applied. A consequential functional unit was applied in porridge portions' carbon footprint calculations. Most of the emissions from barley products' life cycle originate from primary production. The nitrous oxide emissions from cultivated soil and the use and production of nitrogenous fertilisers contribute over 50% of products' carbon footprint. Torino Pearl barley has the highest carbon footprint due to the lowest processing output. The reductions in products' carbon footprint can be achieved with developments in cultivation and grain processing. The carbon footprint of porridge portion can be reduced by using domestically produced plant-based ingredients and by making the best possible use of the kettle. Carbon footprint calculation can be used to determine possible improvement points related to corporate environmental responsibility. Several improvement actions are related to economical and social responsibility through better raw material utilization and expense reductions.

Applications and Markets of Linear Motors

A steady increase in practical industrial applications has secured a place for linear motors. They provide high dynamics and high positioning accuracy of the motor, high reliability and durability of all components of the system. Machines with linear motors have very big perspectives in modern industry. This thesis enables to understand what a linear motor is, where they are used and what situation there is on their market nowadays. It can help to understand reasonability of applying linear motors on manufacture and benefits of its application.

Performance and scalability of isolated DC-DC converter topologies in low voltage, high current applications

Fuel cells are a promising alternative for clean and efficient energy production. A fuel cell is probably the most demanding of all distributed generation power sources. It resembles a solar cell in many ways, but sets strict limits to current ripple, common mode voltages and load variations. The typically low output voltage from the fuel cell stack needs to be boosted to a higher voltage level for grid interfacing. Due to the high electrical efficiency of the fuel cell, there is a need for high efficiency power converters, and in the case of low voltage, high current and galvanic isolation, the implementation of such converters is not a trivial task. This thesis presents galvanically isolated DC-DC converter topologies that have favorable characteristics for fuel cell usage and reviews the topologies from the viewpoint of electrical efficiency and cost efficiency. The focus is on evaluating the design issues when considering a single converter module having large current stresses. The dominating loss mechanism in low voltage, high current applications is conduction losses. In the case of MOSFETs, the conduction losses can be efficiently reduced by paralleling, but in the case of diodes, the effectiveness of paralleling depends strongly on the semiconductor material, diode parameters and output configuration. The transformer winding losses can be a major source of losses if the windings are not optimized according to the topology and the operating conditions. Transformer prototyping can be expensive and time consuming, and thus it is preferable to utilize various calculation methods during the design process in order to evaluate the performance of the transformer. This thesis reviews calculation methods for solid wire, litz wire and copper foil winding losses, and in order to evaluate the applicability of the methods, the calculations are compared against measurements and FEM simulations. By selecting a proper calculation method for each winding type, the winding losses can be predicted quite accurately before actually constructing the transformer. The transformer leakage inductance, the amount of which can also be calculated with reasonable accuracy, has a significant impact on the semiconductor switching losses. Therefore, the leakage inductance effects should also be taken into account when considering the overall efficiency of the converter. It is demonstrated in this thesis that although there are some distinctive differences in the loss distributions between the converter topologies, the differences in the overall efficiency can remain within a range of a few percentage points. However, the optimization effort required in order to achieve the high efficiencies is quite different in each topology. In the presence of practical constraints such as manufacturing complexity or cost, the question of topology selection can become crucial.

Large-eddy simulation of wind flows over complex terrains for wind energy applications

Wind energy has obtained outstanding expectations due to risks of global warming and nuclear energy production plant accidents. Nowadays, wind farms are often constructed in areas of complex terrain. A potential wind farm location must have the site thoroughly surveyed and the wind climatology analyzed before installing any hardware. Therefore, modeling of Atmospheric Boundary Layer (ABL) flows over complex terrains containing, e.g. hills, forest, and lakes is of great interest in wind energy applications, as it can help in locating and optimizing the wind farms. Numerical modeling of wind flows using Computational Fluid Dynamics (CFD) has become a popular technique during the last few decades. Due to the inherent flow variability and large-scale unsteadiness typical in ABL flows in general and especially over complex terrains, the flow can be difficult to be predicted accurately enough by using the Reynolds-Averaged Navier-Stokes equations (RANS). Large- Eddy Simulation (LES) resolves the largest and thus most important turbulent eddies and models only the small-scale motions which are more universal than the large eddies and thus easier to model. Therefore, LES is expected to be more suitable for this kind of simulations although it is computationally more expensive than the RANS approach. With the fast development of computers and open-source CFD software during the recent years, the application of LES toward atmospheric flow is becoming increasingly common nowadays. The aim of the work is to simulate atmospheric flows over realistic and complex terrains by means of LES. Evaluation of potential in-land wind park locations will be the main application for these simulations. Development of the LES methodology to simulate the atmospheric flows over realistic terrains is reported in the thesis. The work also aims at validating the LES methodology at a real scale. In the thesis, LES are carried out for flow problems ranging from basic channel flows to real atmospheric flows over one of the most recent real-life complex terrain problems, the Bolund hill. All the simulations reported in the thesis are carried out using a new OpenFOAM® -based LES solver. The solver uses the 4th order time-accurate Runge-Kutta scheme and a fractional step method. Moreover, development of the LES methodology includes special attention to two boundary conditions: the upstream (inflow) and wall boundary conditions. The upstream boundary condition is generated by using the so-called recycling technique, in which the instantaneous flow properties are sampled on aplane downstream of the inlet and mapped back to the inlet at each time step. This technique develops the upstream boundary-layer flow together with the inflow turbulence without using any precursor simulation and thus within a single computational domain. The roughness of the terrain surface is modeled by implementing a new wall function into OpenFOAM® during the thesis work. Both, the recycling method and the newly implemented wall function, are validated for the channel flows at relatively high Reynolds number before applying them to the atmospheric flow applications. After validating the LES model over simple flows, the simulations are carried out for atmospheric boundary-layer flows over two types of hills: first, two-dimensional wind-tunnel hill profiles and second, the Bolund hill located in Roskilde Fjord, Denmark. For the twodimensional wind-tunnel hills, the study focuses on the overall flow behavior as a function of the hill slope. Moreover, the simulations are repeated using another wall function suitable for smooth surfaces, which already existed in OpenFOAM® , in order to study the sensitivity of the flow to the surface roughness in ABL flows. The simulated results obtained using the two wall functions are compared against the wind-tunnel measurements. It is shown that LES using the implemented wall function produces overall satisfactory results on the turbulent flow over the two-dimensional hills. The prediction of the flow separation and reattachment-length for the steeper hill is closer to the measurements than the other numerical studies reported in the past for the same hill geometry. The field measurement campaign performed over the Bolund hill provides the most recent field-experiment dataset for the mean flow and the turbulence properties. A number of research groups have simulated the wind flows over the Bolund hill. Due to the challenging features of the hill such as the almost vertical hill slope, it is considered as an ideal experimental test case for validating micro-scale CFD models for wind energy applications. In this work, the simulated results obtained for two wind directions are compared against the field measurements. It is shown that the present LES can reproduce the complex turbulent wind flow structures over a complicated terrain such as the Bolund hill. Especially, the present LES results show the best prediction of the turbulent kinetic energy with an average error of 24.1%, which is a 43% smaller than any other model results reported in the past for the Bolund case. Finally, the validated LES methodology is demonstrated to simulate the wind flow over the existing Muukko wind farm located in South-Eastern Finland. The simulation is carried out only for one wind direction and the results on the instantaneous and time-averaged wind speeds are briefly reported. The demonstration case is followed by discussions on the practical aspects of LES for the wind resource assessment over a realistic inland wind farm.

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.