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  • Vehkamäki, Marko (Helsingin yliopisto, 2007)
    Atomic layer deposition (ALD) is a method for thin film deposition which has been extensively studied for binary oxide thin film growth. Studies on multicomponent oxide growth by ALD remain relatively few owing to the increased number of factors that come into play when more than one metal is employed. More metal precursors are required, and the surface may change significantly during successive stages of the growth. Multicomponent oxide thin films can be prepared in a well-controlled way as long as the same principle that makes binary oxide ALD work so well is followed for each constituent element: in short, the film growth has to be self-limiting. ALD of various multicomponent oxides was studied. SrTiO3, BaTiO3, Ba(1-x)SrxTiO3 (BST), SrTa2O6, Bi4Ti3O12, BiTaO4 and SrBi2Ta2O9 (SBT) thin films were prepared, many of them for the first time by ALD. Chemistries of the binary oxides are shown to influence the processing of their multicomponent counterparts. The compatibility of precursor volatilities, thermal stabilities and reactivities is essential for multicomponent oxide ALD, but it should be noted that the main reactive species, the growing film itself, must also be compatible with self-limiting growth chemistry. In the cases of BaO and Bi2O3 the growth of the binary oxide was very difficult, but the presence of Ti or Ta in the growing film made self-limiting growth possible. The application of the deposited films as dielectric and ferroelectric materials was studied. Post-deposition annealing treatments in different atmospheres were used to achieve the desired crystalline phase or, more generally, to improve electrical properties. Electrode materials strongly influenced the leakage current densities in the prepared metal insulator metal (MIM) capacitors. Film permittivities above 100 and leakage current densities below 110-7 A/cm2 were achieved with several of the materials.
  • Hämäläinen, Jani (Helsingin yliopisto, 2013)
    Atomic layer deposition (ALD) is a chemical gas phase deposition method to grow thin films which are highly uniform and conformal over large and complex substrate areas. Film growth in ALD is precise, remarkably repeatable, and combined with unparalleled control of the film thickness. These inherent properties make ALD an attractive method to deposit thin films for advanced technological applications such as microelectronics and nanotechnology. One material group in ALD which has matured in ten years and proven to be of wide technological importance is noble metals. The purpose of this study was to investigate noble metal oxide film growth by ALD. The ALD of noble metal oxides has been very limited compared to the noble metal growth. Another aim was to examine noble metal film deposition at temperatures lower than required in the earlier ALD noble metal processes. In addition, the selection of noble metals that can be grown by ALD was expanded with osmium. The results of the study showed that oxides of iridium, rhodium, platinum, and palladium can be deposited from the common noble metal precursors using ozone as the reactant at temperatures below 200 °C. The development of ozone-based ALD noble metal oxide processes led further on to the low temperature deposition of noble metals by adding a reductive molecular hydrogen step after every oxidative ozone step. The noble metal deposition via noble metal oxide growth was achieved at lower temperatures than required with the common oxygen-based ALD noble metal processes. Film growth rates, resistivities, purities, and surface roughnesses resulting from the studied noble metal oxide and noble metal processes were reasonable. The processes showed some shortcomings but offer an alternative thermal ALD pathway to deposit noble metals and noble metal oxides compared to the oxygen-based ALD processes. Keywords: atomic layer deposition, ALD, noble metal oxide, noble metal, thin film, ozone
  • Aaltonen, Titta (Helsingin yliopisto, 2005)
  • Tolvanen, Antti (Helsingin yliopisto, 2010)
    Carbon nanotubes, seamless cylinders made from carbon atoms, have outstanding characteristics: inherent nano-size, record-high Young’s modulus, high thermal stability and chemical inertness. They also have extraordinary electronic properties: in addition to extremely high conductance, they can be both metals and semiconductors without any external doping, just due to minute changes in the arrangements of atoms. As traditional silicon-based devices are reaching the level of miniaturisation where leakage currents become a problem, these properties make nanotubes a promising material for applications in nanoelectronics. However, several obstacles must be overcome for the development of nanotube-based nanoelectronics. One of them is the ability to modify locally the electronic structure of carbon nanotubes and create reliable interconnects between nanotubes and metal contacts which likely can be used for integration of the nanotubes in macroscopic electronic devices. In this thesis, the possibility of using ion and electron irradiation as a tool to introduce defects in nanotubes in a controllable manner and to achieve these goals is explored. Defects are known to modify the electronic properties of carbon nanotubes. Some defects are always present in pristine nanotubes, and naturally are introduced during irradiation. Obviously, their density can be controlled by irradiation dose. Since different types of defects have very different effects on the conductivity, knowledge of their abundance as induced by ion irradiation is central for controlling the conductivity. In this thesis, the response of single walled carbon nanotubes to ion irradiation is studied. It is shown that, indeed, by energy selective irradiation the conductance can be controlled. Not only the conductivity, but the local electronic structure of single walled carbon nanotubes can be changed by the defects. The presented studies show a variety of changes in the electronic structures of semiconducting single walled nanotubes, varying from individual new states in the band gap to changes in the band gap width. The extensive simulation results for various types of defect make it possible to unequivocally identify defects in single walled carbon nanotubes by combining electronic structure calculations and scanning tunneling spectroscopy, offering a reference data for a wide scientific community of researchers studying nanotubes with surface probe microscopy methods. In electronics applications, carbon nanotubes have to be interconnected to the macroscopic world via metal contacts. Interactions between the nanotubes and metal particles are also essential for nanotube synthesis, as single walled nanotubes are always grown from metal catalyst particles. In this thesis, both growth and creation of nanotube-metal nanoparticle interconnects driven by electron irradiation is studied. Surface curvature and the size of metal nanoparticles is demonstrated to determine the local carbon solubility in these particles. As for nanotube-metal contacts, previous experiments have proved the possibility to create junctions between carbon nanotubes and metal nanoparticles under irradiation in a transmission electron microscope. In this thesis, the microscopic mechanism of junction formation is studied by atomistic simulations carried out at various levels of sophistication. It is shown that structural defects created by the electron beam and efficient reconstruction of the nanotube atomic network, inherently related to the nanometer size and quasi-one dimensional structure of nanotubes, are the driving force for junction formation. Thus, the results of this thesis not only address practical aspects of irradiation-mediated engineering of nanosystems, but also contribute to our understanding of the behaviour of point defects in low-dimensional nanoscale materials.
  • Ullah, Mohammad Wali (Helsingin yliopisto, 2014)
    Gallium nitride (GaN) has emerged as one of the most important semiconductors in modern technology. GaN-based device technology was mainly pushed forward by invention of p-type doping and the successful fabrication of light emitting diodes (LEDs) and laser diodes (LDs). Intensive studies in the last 20 years on GaN have significantly advanced the understanding of the properties and have expanded the range of practical applications. Beside basic lighting, current applications of GaN include high-power and high temperature electronics, microwave, optoelectronic devices, and so on. The successful production of optical devices demands efficient tuning of charge carrier lifetime where defect engineering plays a vital role. During growth, varying the level of recombination centers is difficult, whereas ion irradiation can do this job efficiently on a final product. On the other hand, during doping, undesirable defects can also be produced and epitaxial GaN is known to have a highly defective structure. Thus, having both positive and negative aspects, it is very important to have a detailed understanding of irradiation-induced defects. To explain experimental findings, atomic level understanding is necessary, but it is not always possible to have an atomistic view of defect dynamics in experiments. Some damage build-up studies by single ions have been reported in the literature, but not many by molecular ions. In this thesis, the irradiation of GaN by single and molecular ions by the means of atomistic simulations was studied. Detailed analysis mainly of what kind of defects, their distribution, reason of defect formation and time evolution have been studied and compared with experiments. The irradiation response of both bulk and nano-structured GaN system were studied. For bulk studies, all projectiles were irradiated having the same energy per mass. The damage by molecular ions showed strong dynamic annealing. No non-linearity had been observed in the total number of point defects between single and molecular ions. On the other hand, molecular ions produce larger clusters of point defects than single ions. These large defect clusters can be one of the mechanisms of the experimentally observed faster carrier decay time for molecular projectiles. Defects were mostly concentrated at the surface and near surface regions, which is also evident from experiments. Comparison between a similar mass single ion and a molecular ion show that a single ion produced more defect clusters than molecular ions. This suggests that heavy ions are even more efficient than similar mass cluster ions to quench the carrier lifetime. Irradiation of a GaN nanowire (NW) reveals that a large surface to volume ratio promotes high density of surface defects. The experimentally observed yellow luminescence band is correlated with these defect induced surface states. Irradiation induced defects also expand the lattice parameters of the NW.
  • Lasa Esquisabel, Ane (Helsingin yliopisto, 2014)
    The world's energy demand and harmful green-house gas emissions are continuously increasing, while the fossil fuel reservoir may soon end. Currently, there is no clear alternative to the traditional energy production methods for a safe and clean future. Fusion could be part of the solution offering a green-house gas free, virtually endless, safe and large scale energy production. A major challenge for fusion is, however, to produce more energy than needed to achieve and maintain the fusion reaction. The most feasible fusion reaction is based on two hydrogen isotopes: deuterium and tritium, which fuse to produce a helium atom and a neutron. For these atoms to fuse, they must overcome the repulsive interaction between them, requiring extreme temperatures. Thus, the particles ionize forming gas plasma. On Earth, this condition can only be met by isolating the plasma from its environment, for instance, by using closed magnetic fields to form a torus-like shaped plasma, also known as tokamak. However, the plasma particles will interact with the reactor walls as their confinement is never perfect, the exhausted plasma must leave the reactor and impurities are introduced in the plasma boundary to control its characteristics. The plasma-wall interactions are especially intense at the divertor, where the plasma is designed to touch the wall. Understanding these processes is essential to develop safe, long-lasting materials and to avoid contaminating the plasma fuel. The main candidates as first wall materials in future fusion reactors are beryllium for the main wall, and tungsten and carbon for the divertor. Also, the materials may mix due to wall erosion, transport of the eroded particles and their deposition in a new location. Plasma-wall interactions can be studied in current experimental reactors or in linear plasma devices. However, this work is often insufficient to understand the underlying mechanisms. Further, the effects of plasma-wall interactions in materials develop in a wide range of time and length scales. Multi scale modelling is a tool that allows to overcome these challenges, improving the predictions for future fusion reactors. In this thesis, the plasma wall interactions taking place in a fusion reactors divertor have been studied by computational means. The interaction of pure and mixed divertor materials, with plasma and impurity particles were modelled. The work was mainly based on atomistic scale calculations, and a Kinetic Monte Carlo algorithm has also been developed to extend the results to macroscopic scales, enabling a direct comparison with experiments. First, deuterium irradiation of various W-C composites has been modelled, focusing on deuterium implantation, variations of the substrate composition and C erosion mechanisms. Carbon was preferentially eroded, varying the substrate's composition throughout the irradiation. The presence of carbon also affected the D implantation characteristics. As carbon became less likely to be an ITER first wall material, the present work focused on the tungsten-beryllium-deuterium system. The tungsten-beryllium mixing showed a strong dependence on irradiation energy and angle. Further, the presence of Be led to higher fuel implantation and W erosion was suppressed by mixed layer formation. The obtained yields were compared to Binary Collision Approximation results, in order to improve the description of the latter method. Furthermore, an unexpected and possibly harmful phenomenon has been addressed in this thesis: porous nano-morphology formation in tungsten by helium plasma exposure. First, the main characteristics and active mechanisms in the system were identified by atomistic simulations. Then, the porous morphology growth was modelled by implementing these processes in a Kinetic Monte Carlo code, resulting in rates that agreed with experimental findings. A morphology growth model was derived where the time dependence is driven by the evolution of the surface roughness, which is a stochastic process and thus evolves as the square root of time.
  • Parviainen, Stefan (Helsingin yliopisto, 2014)
    Modern society runs largely on electricity, and where there is electricity there are electric fields. As the boundaries of technology are pushed forward, stronger and stronger electric fields are either required, or appear due to unwanted effects. Examples of such applications, where very high electric fields are utilised include particle accelerators and atom probes. To further be able to improve on such techniques, it is necessary to gain a good understanding of the processes that are involved. Because it is often difficult, if not impossible, to observe these processes with high resolution in experiments, one needs to consider the use of atomistic simulations instead. This thesis provides an extension to classical molecular dynamics by describing an implementation where several electronic effects are considered when dealing with metal surfaces under high electric fields. These effects include the charging of surface atoms, field electron emission and the resulting resistive heating, as well as field evaporation of both neutral and charged atoms. In addition to the implementation details, the thesis also contains a brief background of the physics involved in these processes. Using the implementation, it is observed that a surface protrusion may grow on an initially flat surface in the presence of a near-surface void when a strong external electric field is applied. The growth is very rapid, resulting finally catastrophic breakage. This mechanism may explain the appearance of field emitters on otherwise pristine samples, and the instability of measured field emission currents. Simulations also reveal that high aspect ratio protrusions are subject to Rayleigh instability due to the temperature rise caused by field electron emission currents. As a result a large fraction of the protrusion can break off. The model also allows for the study of the trajectories of field evaporated ions from a surface, as they are accelerated in the electric field. From the simulations we see that even changes in the surface morphology on the atomic scale may result in aberrations in atom probe tomography experiments.
  • Pajunen, Taina (Helsingin yliopisto, 2009)
    The autoxidation of conjugated linoleic acid (CLA) is poorly understood in spite of increasing interest in the beneficial biological properties of CLA and growing consumption of CLA-rich foods. In this thesis, the autoxidation reactions of the two major CLA isomers, 9-cis,11-trans-octadecadienoic acid and 10-trans,12-cis-octadecadienoic acid, are investigated. The results contribute to an understanding of the early stages of the autoxidation of CLA methyl ester, and provide for the first time a means of producing and separating intact CLA methyl ester hydroperoxides as well as basic knowledge on lipid hydroperoxides and their hydroxy derivatives. Conjugated diene allylic monohydroperoxides were discovered as primary autoxidation products formed during autoxidation of CLA methyl esters in the presence and absence of α-tocopherol. This established that one of the autoxidation pathways of CLA methyl ester is the hydroperoxide pathway. Hydroperoxides were produced from the two major CLA methyl esters by taking advantage of the effect of α-tocopherol to promote hydroperoxide formation. The hydroperoxides were analysed and separated first as methyl hydroxyoctadecadienoates and then as intact hydroperoxides by HPLC. The isolated products were characterized by UV, GC-MS, and NMR techniques. In the presence of a high amount of α-tocopherol, the autoxidation of CLA methyl ester yields six kinetically-controlled conjugated diene monohydroperoxides and is diastereoselective in favour of one particular geometric isomer as a pair of enantiomers. The primary autoxidation products produced from the two major CLA isomers include new positional isomers of conjugated diene monohydroperoxides, the 8-, 10-, 12-, and 14-hydroperoxyoctadecadienoates. Furthermore, two of these new positional isomers have an unusual structure for a cis,trans lipid hydroperoxide where the allylic methine carbon is adjacent to the cis instead of the usual trans double bond. The 1H and 13C NMR spectra of nine isomeric methyl hydroxyoctadecadienoates and of ten isomeric methyl hydroperoxyoctadecadienoates including the unusual cis,trans hydroperoxides, i.e. Me 8-OOH-9c,11t and Me 14-OOH-10t,12c, were fully assigned with the aid of 2D NMR spectroscopy. The assigned NMR data enabled determination of the effects of the hydroxyl and hydroperoxyl groups on the carbon chemical shifts of CLA isomers, identification of diagnostic signals, and determination of chemical shift differences of the olefinic resonances that may help with the assignment of structure to as yet unknown lipid hydroperoxides either as hydroxy derivatives or as intact hydroperoxides. A mechanism for the hydroperoxide pathway of CLA autoxidation in the presence of a high amount of α-tocopherol was proposed based on the characterized primary products, their relative distribution, and theoretical calculations. This is an important step forward in CLA research, where exact mechanisms for the autoxidation of CLA have not been presented before. Knowledge of these hydroperoxide formation steps is of crucial importance for understanding the subsequent steps and the different pathways of the autoxidation of CLA. Moreover, a deeper understanding of the autoxidation mechanisms is required for ensuring the safety of CLA-rich foods. Knowledge of CLA oxidation and how it differs from the oxidation of nonconjugated polyunsaturated fatty acids may also be the key to understanding the biological mechanisms of CLA activity.
  • Kaasalainen, Sanna (Helsingin yliopisto, 2002)
  • Mutshinda Mwanza, Crispin (Helsingin yliopisto, 2010)
    Elucidating the mechanisms responsible for the patterns of species abundance, diversity, and distribution within and across ecological systems is a fundamental research focus in ecology. Species abundance patterns are shaped in a convoluted way by interplays between inter-/intra-specific interactions, environmental forcing, demographic stochasticity, and dispersal. Comprehensive models and suitable inferential and computational tools for teasing out these different factors are quite limited, even though such tools are critically needed to guide the implementation of management and conservation strategies, the efficacy of which rests on a realistic evaluation of the underlying mechanisms. This is even more so in the prevailing context of concerns over climate change progress and its potential impacts on ecosystems. This thesis utilized the flexible hierarchical Bayesian modelling framework in combination with the computer intensive methods known as Markov chain Monte Carlo, to develop methodologies for identifying and evaluating the factors that control the structure and dynamics of ecological communities. These methodologies were used to analyze data from a range of taxa: macro-moths (Lepidoptera), fish, crustaceans, birds, and rodents. Environmental stochasticity emerged as the most important driver of community dynamics, followed by density dependent regulation; the influence of inter-specific interactions on community-level variances was broadly minor. This thesis contributes to the understanding of the mechanisms underlying the structure and dynamics of ecological communities, by showing directly that environmental fluctuations rather than inter-specific competition dominate the dynamics of several systems. This finding emphasizes the need to better understand how species are affected by the environment and acknowledge species differences in their responses to environmental heterogeneity, if we are to effectively model and predict their dynamics (e.g. for management and conservation purposes). The thesis also proposes a model-based approach to integrating the niche and neutral perspectives on community structure and dynamics, making it possible for the relative importance of each category of factors to be evaluated in light of field data.
  • Mäntyniemi, Samu (Helsingin yliopisto, 2006)
    In this thesis the use of the Bayesian approach to statistical inference in fisheries stock assessment is studied. The work was conducted in collaboration of the Finnish Game and Fisheries Research Institute by using the problem of monitoring and prediction of the juvenile salmon population in the River Tornionjoki as an example application. The River Tornionjoki is the largest salmon river flowing into the Baltic Sea. This thesis tackles the issues of model formulation and model checking as well as computational problems related to Bayesian modelling in the context of fisheries stock assessment. Each article of the thesis provides a novel method either for extracting information from data obtained via a particular type of sampling system or for integrating the information about the fish stock from multiple sources in terms of a population dynamics model. Mark-recapture and removal sampling schemes and a random catch sampling method are covered for the estimation of the population size. In addition, a method for estimating the stock composition of a salmon catch based on DNA samples is also presented. For most of the articles, Markov chain Monte Carlo (MCMC) simulation has been used as a tool to approximate the posterior distribution. Problems arising from the sampling method are also briefly discussed and potential solutions for these problems are proposed. Special emphasis in the discussion is given to the philosophical foundation of the Bayesian approach in the context of fisheries stock assessment. It is argued that the role of subjective prior knowledge needed in practically all parts of a Bayesian model should be recognized and consequently fully utilised in the process of model formulation.
  • Pirinen, Matti (Helsingin yliopisto, 2009)
    Genetics, the science of heredity and variation in living organisms, has a central role in medicine, in breeding crops and livestock, and in studying fundamental topics of biological sciences such as evolution and cell functioning. Currently the field of genetics is under a rapid development because of the recent advances in technologies by which molecular data can be obtained from living organisms. In order that most information from such data can be extracted, the analyses need to be carried out using statistical models that are tailored to take account of the particular genetic processes. In this thesis we formulate and analyze Bayesian models for genetic marker data of contemporary individuals. The major focus is on the modeling of the unobserved recent ancestry of the sampled individuals (say, for tens of generations or so), which is carried out by using explicit probabilistic reconstructions of the pedigree structures accompanied by the gene flows at the marker loci. For such a recent history, the recombination process is the major genetic force that shapes the genomes of the individuals, and it is included in the model by assuming that the recombination fractions between the adjacent markers are known. The posterior distribution of the unobserved history of the individuals is studied conditionally on the observed marker data by using a Markov chain Monte Carlo algorithm (MCMC). The example analyses consider estimation of the population structure, relatedness structure (both at the level of whole genomes as well as at each marker separately), and haplotype configurations. For situations where the pedigree structure is partially known, an algorithm to create an initial state for the MCMC algorithm is given. Furthermore, the thesis includes an extension of the model for the recent genetic history to situations where also a quantitative phenotype has been measured from the contemporary individuals. In that case the goal is to identify positions on the genome that affect the observed phenotypic values. This task is carried out within the Bayesian framework, where the number and the relative effects of the quantitative trait loci are treated as random variables whose posterior distribution is studied conditionally on the observed genetic and phenotypic data. In addition, the thesis contains an extension of a widely-used haplotyping method, the PHASE algorithm, to settings where genetic material from several individuals has been pooled together, and the allele frequencies of each pool are determined in a single genotyping.
  • Cheng, Lu (Helsingin yliopisto, 2013)
    Vast amounts of molecular data are being generated every day. However, how to properly harness the data remains often a challenge for many biologists. Firstly, due to the typical large dimension of the molecular data, analyses can either require exhaustive amounts of computer memory or be very time-consuming, or both. Secondly, biological problems often have their own special features, which put demand on specially designed software to obtain meaningful results from statistical analyses without imposing too much requirements on the available computing resources. Finally, the general complexity of many biological research questions necessitates joint use of many different methods, which requires a considerable expertise in properly understanding the possibilities and limitations of the analysis tools. In the first part of this thesis, we discuss three general Bayesian classification/clustering frameworks, which in the considered applications are targeted towards clustering of DNA sequence data, in particular in the context of bacterial population genomics and evolutionary epidemiology. Based on more generic Bayesian concepts, we have developed several statistical tools for analyzing DNA sequence data in bacterial metagenomics and population genomics. In the second part of this thesis, we focus on discussing how to reconstruct bacterial evolutionary history from a combination of whole genome sequences and a number of core genes for which a large set of samples are available. A major problem is that for many bacterial species horizontal gene transfer of DNA, which is often termed as recombination, is relatively frequent and the recombined fragments within genome sequences have a tendency to severely distort the phylogenetic inferences. To obtain computationally viable solutions in practice for a majority of currently emerging genome data sets, it is necessary to divide the problem into parts and use different approaches in combination to perform the whole analysis. We demonstrate this strategy by application to two challenging data sets in the context of evolutionary epidemiology and show that biologically significant conclusions can be drawn by shedding light into the complex patterns of relatedness among strains of bacteria. Both studied organisms (\textit{Escherichia coli} and \textit{Campylobacter jejuni}) are major pathogens of humans and understanding the mechanisms behind the evolution of their populations is of vital importance for human health.