Structural and optical properties of InAs/GaAs quantum structures

The goal of the thesis was to study fundamental structural and optical properties of InAs islands and In(Ga)As quantum rings. The research was carried out at the Department of Micro and Nanosciences of Helsinki University of Technology. A good surface quality can be essential for the potential applications in optoelectronic devices. For such device applications it is usually necessary to control size, density and arrangement of the islands. In order to study the dependence of the structural properties of the islands and the quantum rings on growth conditions, atomic force microscope was used. Obtained results reveal that the size and the density of the In(Ga)As quantum rings strongly depend on the growth temperature, the annealing time and the thickness of the partial capping layer. From obtained results it is possible to conclude that to get round shape islands and high density one has to use growth temperature of 500 ̊C. In the case of formation of In(Ga)As quantum rings the effect of mobility anisotropy is observed that so the shape of the rings is not symmetric. To exclude this effect it is preferable to use a higher annealing temperature of 570 ̊C. Optical properties were characterized by PL spectroscopy. PL emission was observed from buried InAs quantum dots and In(Ga)As quantum rings grown with different annealing time and temperature and covered with a various thickness of the partial capping layer.

Non-Linear Journal Bearing Model for Analysis of Superharmonic Vibrations of Rotor Systems

A rotating machine usually consists of a rotor and bearings that supports it. The nonidealities in these components may excite vibration of the rotating system. The uncontrolled vibrations may lead to excessive wearing of the components of the rotating machine or reduce the process quality. Vibrations may be harmful even when amplitudes are seemingly low, as is usually the case in superharmonic vibration that takes place below the first critical speed of the rotating machine. Superharmonic vibration is excited when the rotational velocity of the machine is a fraction of the natural frequency of the system. In such a situation, a part of the machine’s rotational energy is transformed into vibration energy. The amount of vibration energy should be minimised in the design of rotating machines. The superharmonic vibration phenomena can be studied by analysing the coupled rotor-bearing system employing a multibody simulation approach. This research is focused on the modelling of hydrodynamic journal bearings and rotorbearing systems supported by journal bearings. In particular, the non-idealities affecting the rotor-bearing system and their effect on the superharmonic vibration of the rotating system are analysed. A comparison of computationally efficient journal bearing models is carried out in order to validate one model for further development. The selected bearing model is improved in order to take the waviness of the shaft journal into account. The improved model is implemented and analyzed in a multibody simulation code. A rotor-bearing system that consists of a flexible tube roll, two journal bearings and a supporting structure is analysed employing the multibody simulation technique. The modelled non-idealities are the shell thickness variation in the tube roll and the waviness of the shaft journal in the bearing assembly. Both modelled non-idealities may cause subharmonic resonance in the system. In multibody simulation, the coupled effect of the non-idealities can be captured in the analysis. Additionally one non-ideality is presented that does not excite the vibrations itself but affects the response of the rotorbearing system, namely the waviness of the bearing bushing which is the non-rotating part of the bearing system. The modelled system is verified with measurements performed on a test rig. In the measurements the waviness of bearing bushing was not measured and therefore it’s affect on the response was not verified. In conclusion, the selected modelling approach is an appropriate method when analysing the response of the rotor-bearing system. When comparing the simulated results to the measured ones, the overall agreement between the results is concluded to be good.

Influence of stationary phase and eluent properties on chromatographic separation of carbohydrates

In this thesis, the sorption and elastic properties of the cation-exchange resins were studied to explain the liquid chromatographic separation of carbohydrates. Na+, Ca2+ and La3+ form strong poly(styrene-co-divinylbenzene) (SCE) as well as Na+ and Ca2+ form weak acrylic (WCE) cation-exchange resins at different cross-link densities were treated within this work. The focus was on the effects of water-alcohol mixtures, mostly aqueous ethanol, and that of the carbohydrates. The carbohydrates examined were rhamnose, xylose, glucose, fructose, arabinose, sucrose, xylitol and sorbitol. In addition to linear chromatographic conditions, non-linear conditions more typical for industrial applications were studied. Both experimental and modeling aspectswere covered. The aqueous alcohol sorption on the cation-exchangers were experimentally determined and theoretically calculated. The sorption model includes elastic parameters, which were obtained from sorption data combined with elasticity measurements. As hydrophilic materials cation-exchangers are water selective and shrink when an organic solvent is added. At a certain deswelling degree the elastic resins go through glass transition and become as glass-like material. Theincreasing cross-link level and the valence of the counterion decrease the sorption of solvent components in the water-rich solutions. The cross-linkage or thecounterions have less effect on the water selectivity than the resin type or the used alcohol. The amount of water sorbed is higher in the WCE resin and, moreover, the WCE resin is more water selective than the corresponding SCE resin. Theincreased aliphatic part of lower alcohols tend to increase the water selectivity, i.e. the resins are more water selective in 2-propanol than in ethanol solutions. Both the sorption behavior of carbohydrates and the sorption differences between carbohydrates are considerably affected by the eluent composition and theresin characteristics. The carbohydrate sorption was experimentally examined and modeled. In all cases, sorption and moreover the separation of carbohydrates are dominated by three phenomena: partition, ligand exchange and size exclusion. The sorption of hydrophilic carbohydrates increases when alcohol is added into the eluent or when carbohydrate is able to form coordination complexes with the counterions, especially with multivalent counterions. Decreasing polarity of the eluent enhances the complex stability. Size exclusion effect is more prominent when the resin becomes tighter or carbohydrate size increases. On the other hand,the elution volumes between different sized carbohydrates decreases with the decreasing polarity of the eluent. The chromatographic separation of carbohydrateswas modeled, using rhamnose and xylose as target molecules. The thermodynamic sorption model was successfully implemented in the rate-based column model. The experimental chromatographic data were fitted by using only one adjustable parameter. In addition to the fitted data also simulated data were generated and utilized in explaining the effect of the eluent composition and of the resin characteristics on the carbohydrate separation.

Development of phase retrieval algorithm and techniques for optical spectrum analysis

Coherent anti-Stokes Raman scattering is the powerful method of laser spectroscopy in which significant successes are achieved. However, the non-linear nature of CARS complicates the analysis of the received spectra. The objective of this Thesis is to develop a new phase retrieval algorithm for CARS. It utilizes the maximum entropy method and the new wavelet approach for spectroscopic background correction of a phase function. The method was developed to be easily automated and used on a large number of spectra of different substances.. The algorithm was successfully tested on experimental data.

Monolithic zirconium dioxide as a full contour restorative material: With special emphasis on the optical and mechanical properties

Full contour monolithic zirconia restorations have shown an increased popularity in the dental field over the recent years, owing to its mechanical and acceptable optical properties. However, many features of the restoration are yet to be researched and supported by clinical studies to confirm its place among the other indirect restorative materials This series of in vitro studies aimed at evaluating and comparing the optical and mechanical properties, light cure irradiance, and cement polymerization of multiple monolithic zirconia material at variable thicknesses, environments, treatments, and stabilization. Five different monolithic zirconia materials, four of which were partially stabilized and one fully stabilized were investigated. The optical properties in terms of surface gloss, translucency parameter, and contrast ratio were determined via a reflection spectrophotometer at variable thicknesses, coloring, sintering method, and after immersion in an acidic environment. Light cure irradiance and radiant exposure were quantified through the specimens at variable thicknesses and the degree of conversion of two dual-cure cements was determined via Fourier Transform Infrared spectroscopy. Bi-axial flexural strength was evaluated to compare between the partially and fully stabilized zirconia prepared using different coloring and sintering methods. Surface characterization was performed using a scanning electron microscope and a spinning disk confocal microscope. The surface gloss and translucency of the zirconia investigated were brand and thickness dependent with the translucency values decreasing as the thickness increased. Staining decreased the translucency of the zirconia and enhanced surface gloss as well as the flexural strength of the fully stabilized zirconia but had no effect on partially stabilized zirconia. Immersion in a corrosive acid increased surface gloss and decreased the translucency of some zirconia brands. Zirconia thickness was inversely related to the amount of light irradiance, radiant exposure, and degree of monomer conversion. Type of sintering furnace had no effect on the optical and mechanical properties of zirconia. Monolithic zirconia maybe classified as a semi-translucent material that is well influenced by the thickness, limiting its use in the esthetic zones. Conventional acid-base reaction, autopolymerizing and dual-cure cements are recommended for its cementation. Its desirable mechanical properties give it a high potential as a restoration for posterior teeth. However, close monitoring with controlled clinical studies must be determined before any definite clinical recommendations can be drawn.

Optical and photoelectric properties of dry bacteriorhodopsin sensors

In this thesis, bacteriorhodopsin (BR) photosensor’s optical and electrical properties were studied. The BR sensor consisted of a dry film with BR in polyvinyl alcohol and covered with transparent conductors. In the experiments the BR photocycle was started with two lasers. The characteristics of the BR sensor were measured in two ways. The first approach was theoretical and it required knowing the laser parameters. The second way required assembling a measurement setup for the optical response measurements. However, no measurable results were obtained due to low laser power. The photoelectric response was measured in the experiments with two laser systems and the amplifier was tested. In the experiment with a Cavitar laser, the photoelectric response was obtained. In the experiment with FemtoFiber Pro laser, the photoelectric response was not measured. The expected amplitude of the response was obtained. The experimental data was analyzed and possible solutions for reducing the interference were given.

Korkeakappa-massan suotatuvuus

Työn tarkoituksena oli tutkia korkeakappa-massan suotautuvuutta sekä etsiä uusia analyysimenetelmiä korkeakappa-massan karakterisoimiseksi. Työssä pyrittiin määrittämään tekijöitä, jotka vaikuttavat korkeakappa-massan suotautumiseen. Työn kirjallisessa osassa tarkasteltiin aluksi yleisesti keiton teoriaa, minkä jälkeen käsiteltiin jauhatusta ja tarkemmin korkeakappa-massan hienovaraisempaa jauhatusta eli kuidutusta. Seuraavaksi käsiteltiin suodatusta ja sen teoriaa sekä suodatukseen vaikuttavia tekijöitä. Massan pesusta esitettiin perusteet ja teoriaa. Lopuksi tarkasteltiin massan karakterisointia eri lähestymistavoilla sekä kuitujen perusominaisuuksia. Kokeellisessa osassa verrattiin LTY:n koesuodatuslaitteistolla tehdyillä suodatuskokeilla korkeakappa-massaisen sellukakun suotautuvuutta eri paine-eroilla, suodoksen eri hienoainepitoisuuksilla sekä ennen ja jälkeen sellutehtaallatapahtuneen kuidutuksen. Savonlinnassa sijaitsevalla laitteistolla tehtiin syrjäytystestejä ennen ja jälkeen kuidutusta otetuilla sellumassoilla. Lisäksi ennenja jälkeen kuidutusta otettuja sellumassanäytteitä karakterisoitiin mm. kuituanalysaattorilla, huokoskoko- ja ominaispinta-ala-analyyseillä sekä SEM-kuvilla. Suodatuskokeissa hienoainepitoisuudella ei ollut merkitystä permeabiliteettiin mitattujen suodosvirtausten perusteella. Kuten Darcyn lain perusteella voitiin olettaa, kakun paine-eron kasvaessa permeabiliteetti kasvoi. Vaikutus ei ollut kuitenkaan lineaarinen paine-eroon verrattuna vaan kakun permeabiliteetti kasvoi enemmän tietyllä paine-erovälillä. Tämä paine-eroväli vaihteli hieman riippuen oliko sellumassa otettu ennen vai jälkeen kuidutusta. Lappeenrannassa tehdyissä suodatuskokeissa ei ennen ja jälkeen kuidutusta otetuilla näytteillä ollut selvää eroa permeabiliteeteissa, mutta Savonlinnan syrjäytystesteissä ero syrjäytymisnopeudessa oli selvä. Ennen ja jälkeen kuidutusta otettujen sellumassojen kuituanalysaattorituloksissa ja SEM-kuvissa ei havaittu eroa näytteiden välillä, mutta massojen huokoskoko muuttui kuidutuksen vaikutuksesta.

THE IMPACT OF ARCHITECTURAL DESIGN ON SOFTWARE DEVELOPMENT

Tässä työssä tutkitaan ohjelmistoarkkitehtuurisuunnitteluominaisuuksien vaikutusta erään client-server –arkkitehtuuriin perustuvan mobiilipalvelusovelluksen suunnittelu- ja toteutusaikaan. Kyseinen tutkimus perustuu reaalielämän projektiin, jonka kvalitatiivinen analyysi paljasti arkkitehtuurikompponenttien välisten kytkentöjen merkittävästi vaikuttavan projektin työmäärään. Työn päätavoite oli kvantitatiivisesti tutkia yllä mainitun havainnon oikeellisuus. Tavoitteen saavuttamiseksi suunniteltiin ohjelmistoarkkitehtuurisuunnittelun mittaristo kuvaamaan kyseisen järjestelmän alijärjestelmien arkkitehtuuria ja luotiin kaksi suunniteltua mittaristoa käyttävää, työmäärää (komponentin suunnittelu-, toteutus- ja testausaikojen summa) arvioivaa mallia, joista toinen on lineaarinen ja toinen epälineaarinen. Näiden mallien kertoimet sovitettiin optimoimalla niiden arvot epälineaarista gloobaalioptimointimenetelmää, differentiaalievoluutioalgoritmia, käyttäen, niin että mallien antamat arvot vastasivat parhaiten mitattua työmäärää sekä kaikilla ominaisuuksilla eli attribuuteilla että vain osalla niistä (yksi jätettiin vuorotellen pois). Kun arkkitehtuurikompenttien väliset kytkennät jätettiin malleista pois, mitattujen ja arvoitujen työmäärien välinen ero (ilmaistuna virheenä) kasvoi eräässä tapauksessa 367 % entisestä tarkoittaen sitä, että näin muodostettu malli vastasi toteutusaikoja huonosti annetulla ainestolla. Tämä oli suurin havaitu virhe kaikkien poisjätettyjen ominaisuuksien kesken. Saadun tuloksen perusteella päätettiin, että kyseisen järjestelmän toteutusajat ovat vahvasti riippuvaisia kytkentöjen määrästä, ja näin ollen kytkentöjen määrä oli mitä todennäköisemmin kaikista tärkein työmäärään vaikuttava tekijä tutkitun järjestelmän arkkitehtuurisuunnittelussa.

Predicting diffusion of innovations with self-organisation and machine learning

The main subject of this master's thesis was predicting diffusion of innovations. The prediction was done in a special case: product has been available in some countries, and based on its diffusion in those countries the prediction is done for other countries. The prediction was based on finding similar countries with Self-Organizing Map~(SOM), using parameters of countries. Parameters included various economical and social key figures. SOM was optimised for different products using two different methods: (a) by adding diffusion information of products to the country parameters, and (b) by weighting the country parameters based on their importance for the diffusion of different products. A novel method using Differential Evolution (DE) was developed to solve the latter, highly non-linear optimisation problem. Results were fairly good. The prediction method seems to be on a solid theoretical foundation. The results based on country data were good. Instead, optimisation for different products did not generally offer clear benefit, but in some cases the improvement was clearly noticeable. The weights found for the parameters of the countries with the developed SOM optimisation method were interesting, and most of them could be explained by properties of the products.

Kylmämuovattujen putkipalkkien X-liitosten äärikestävyyden ja jäykkyyden määrittäminen sekä materiaalimallin kehittäminen

Työssä on tutkittu elementtimenetelmän avulla kylmämuovattujen nelikulmaisten putkipalkkien materiaalimallin kehittämistä ja putkipalkkien X-liitosten jäykkyyden ja äärikestävyyden määrittämistä. Työn tavoitteena on tutkia kylmämuovauksen vaikutuksia putkipalkkiprofiilin materiaaliominaisuuksiin materiaalikokeiden ja elementtianalyysien avulla sekä kehittää putkipalkille anisotrooppista materiaalimallia. Työssä määritettyjä materiaalimalleja on sovellettu X-liitosten elementtimalleihin, joiden käyttäytymistä on verrattu äärikestävyyskokeiden tuloksiin. Tutkimuksen perusteella Eurocode 3:n mitoitusohjeita voidaan turvallisesti soveltaa kylmämuovattujen putkipalkkien X-liitosten laskennassa. Työssä tehtyjen materiaalikokeiden ja elementtianalyysien perusteella materiaalin anisotrooppisuuden vaikutus liitoksen kestävyyteen on vähäistä, ja putkipalkin pituussuuntaista materiaalimallia voidaan soveltaa myös kehäsuuntaisille materiaaliominaisuuksille. Materiaalikokeiden simulointi osoittaa, että elementtimenetelmää voidaan käyttää materiaalimallin määrittämisen apuvälineenä.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.