A Practical Micro Mechanical Model Based Local Approach Methodology for the Analysis of Ductile Fracture of Welded T-Joints

This thesis concentrates on developing a practical local approach methodology based on micro mechanical models for the analysis of ductile fracture of welded joints. Two major problems involved in the local approach, namely the dilational constitutive relation reflecting the softening behaviour of material, and the failure criterion associated with the constitutive equation, have been studied in detail. Firstly, considerable efforts were made on the numerical integration and computer implementation for the non trivial dilational Gurson Tvergaard model. Considering the weaknesses of the widely used Euler forward integration algorithms, a family of generalized mid point algorithms is proposed for the Gurson Tvergaard model. Correspondingly, based on the decomposition of stresses into hydrostatic and deviatoric parts, an explicit seven parameter expression for the consistent tangent moduli of the algorithms is presented. This explicit formula avoids any matrix inversion during numerical iteration and thus greatly facilitates the computer implementation of the algorithms and increase the efficiency of the code. The accuracy of the proposed algorithms and other conventional algorithms has been assessed in a systematic manner in order to highlight the best algorithm for this study. The accurate and efficient performance of present finite element implementation of the proposed algorithms has been demonstrated by various numerical examples. It has been found that the true mid point algorithm (a = 0.5) is the most accurate one when the deviatoric strain increment is radial to the yield surface and it is very important to use the consistent tangent moduli in the Newton iteration procedure. Secondly, an assessment of the consistency of current local failure criteria for ductile fracture, the critical void growth criterion, the constant critical void volume fraction criterion and Thomason's plastic limit load failure criterion, has been made. Significant differences in the predictions of ductility by the three criteria were found. By assuming the void grows spherically and using the void volume fraction from the Gurson Tvergaard model to calculate the current void matrix geometry, Thomason's failure criterion has been modified and a new failure criterion for the Gurson Tvergaard model is presented. Comparison with Koplik and Needleman's finite element results shows that the new failure criterion is fairly accurate indeed. A novel feature of the new failure criterion is that a mechanism for void coalescence is incorporated into the constitutive model. Hence the material failure is a natural result of the development of macroscopic plastic flow and the microscopic internal necking mechanism. By the new failure criterion, the critical void volume fraction is not a material constant and the initial void volume fraction and/or void nucleation parameters essentially control the material failure. This feature is very desirable and makes the numerical calibration of void nucleation parameters(s) possible and physically sound. Thirdly, a local approach methodology based on the above two major contributions has been built up in ABAQUS via the user material subroutine UMAT and applied to welded T joints. By using the void nucleation parameters calibrated from simple smooth and notched specimens, it was found that the fracture behaviour of the welded T joints can be well predicted using present methodology. This application has shown how the damage parameters of both base material and heat affected zone (HAZ) material can be obtained in a step by step manner and how useful and capable the local approach methodology is in the analysis of fracture behaviour and crack development as well as structural integrity assessment of practical problems where non homogeneous materials are involved. Finally, a procedure for the possible engineering application of the present methodology is suggested and discussed.

ContinuousMultimodal Global Optimization with Differential Evolution-Based Methods

Metaheuristic methods have become increasingly popular approaches in solving global optimization problems. From a practical viewpoint, it is often desirable to perform multimodal optimization which, enables the search of more than one optimal solution to the task at hand. Population-based metaheuristic methods offer a natural basis for multimodal optimization. The topic has received increasing interest especially in the evolutionary computation community. Several niching approaches have been suggested to allow multimodal optimization using evolutionary algorithms. Most global optimization approaches, including metaheuristics, contain global and local search phases. The requirement to locate several optima sets additional requirements for the design of algorithms to be effective in both respects in the context of multimodal optimization. In this thesis, several different multimodal optimization algorithms are studied in regard to how their implementation in the global and local search phases affect their performance in different problems. The study concentrates especially on variations of the Differential Evolution algorithm and their capabilities in multimodal optimization. To separate the global and local search search phases, three multimodal optimization algorithms are proposed, two of which hybridize the Differential Evolution with a local search method. As the theoretical background behind the operation of metaheuristics is not generally thoroughly understood, the research relies heavily on experimental studies in finding out the properties of different approaches. To achieve reliable experimental information, the experimental environment must be carefully chosen to contain appropriate and adequately varying problems. The available selection of multimodal test problems is, however, rather limited, and no general framework exists. As a part of this thesis, such a framework for generating tunable test functions for evaluating different methods of multimodal optimization experimentally is provided and used for testing the algorithms. The results demonstrate that an efficient local phase is essential for creating efficient multimodal optimization algorithms. Adding a suitable global phase has the potential to boost the performance significantly, but the weak local phase may invalidate the advantages gained from the global phase.

Physical Realization of an Optical Automatic Target Recognition System

In the modern warfare there is an active development of a new trend connected with a robotic warfare. One of the critical elements of robotics warfare systems is an automatic target recognition system, allowing to recognize objects, based on the data received from sensors. This work considers aspects of optical realization of such a system by means of NIR target scanning at fixed wavelengths. An algorithm was designed, an experimental setup was built and samples of various modern gear and apparel materials were tested. For pattern testing the samples of actively arm engaged armies camouflages were chosen. Tests were performed both in clear atmosphere and in the artificial extremely humid and hot atmosphere to simulate field conditions.

Eye Fundus Image Analysis for Automatic Detection of Diabetic Retinopathy

Diabetes is a rapidly increasing worldwide problem which is characterised by defective metabolism of glucose that causes long-term dysfunction and failure of various organs. The most common complication of diabetes is diabetic retinopathy (DR), which is one of the primary causes of blindness and visual impairment in adults. The rapid increase of diabetes pushes the limits of the current DR screening capabilities for which the digital imaging of the eye fundus (retinal imaging), and automatic or semi-automatic image analysis algorithms provide a potential solution. In this work, the use of colour in the detection of diabetic retinopathy is statistically studied using a supervised algorithm based on one-class classification and Gaussian mixture model estimation. The presented algorithm distinguishes a certain diabetic lesion type from all other possible objects in eye fundus images by only estimating the probability density function of that certain lesion type. For the training and ground truth estimation, the algorithm combines manual annotations of several experts for which the best practices were experimentally selected. By assessing the algorithm’s performance while conducting experiments with the colour space selection, both illuminance and colour correction, and background class information, the use of colour in the detection of diabetic retinopathy was quantitatively evaluated. Another contribution of this work is the benchmarking framework for eye fundus image analysis algorithms needed for the development of the automatic DR detection algorithms. The benchmarking framework provides guidelines on how to construct a benchmarking database that comprises true patient images, ground truth, and an evaluation protocol. The evaluation is based on the standard receiver operating characteristics analysis and it follows the medical practice in the decision making providing protocols for image- and pixel-based evaluations. During the work, two public medical image databases with ground truth were published: DIARETDB0 and DIARETDB1. The framework, DR databases and the final algorithm, are made public in the web to set the baseline results for automatic detection of diabetic retinopathy. Although deviating from the general context of the thesis, a simple and effective optic disc localisation method is presented. The optic disc localisation is discussed, since normal eye fundus structures are fundamental in the characterisation of DR.

Tool-supported invariant-based programming

The development of correct programs is a core problem in computer science. Although formal verification methods for establishing correctness with mathematical rigor are available, programmers often find these difficult to put into practice. One hurdle is deriving the loop invariants and proving that the code maintains them. So called correct-by-construction methods aim to alleviate this issue by integrating verification into the programming workflow. Invariant-based programming is a practical correct-by-construction method in which the programmer first establishes the invariant structure, and then incrementally extends the program in steps of adding code and proving after each addition that the code is consistent with the invariants. In this way, the program is kept internally consistent throughout its development, and the construction of the correctness arguments (proofs) becomes an integral part of the programming workflow. A characteristic of the approach is that programs are described as invariant diagrams, a graphical notation similar to the state charts familiar to programmers. Invariant-based programming is a new method that has not been evaluated in large scale studies yet. The most important prerequisite for feasibility on a larger scale is a high degree of automation. The goal of the Socos project has been to build tools to assist the construction and verification of programs using the method. This thesis describes the implementation and evaluation of a prototype tool in the context of the Socos project. The tool supports the drawing of the diagrams, automatic derivation and discharging of verification conditions, and interactive proofs. It is used to develop programs that are correct by construction. The tool consists of a diagrammatic environment connected to a verification condition generator and an existing state-of-the-art theorem prover. Its core is a semantics for translating diagrams into verification conditions, which are sent to the underlying theorem prover. We describe a concrete method for 1) deriving sufficient conditions for total correctness of an invariant diagram; 2) sending the conditions to the theorem prover for simplification; and 3) reporting the results of the simplification to the programmer in a way that is consistent with the invariantbased programming workflow and that allows errors in the program specification to be efficiently detected. The tool uses an efficient automatic proof strategy to prove as many conditions as possible automatically and lets the remaining conditions be proved interactively. The tool is based on the verification system PVS and i uses the SMT (Satisfiability Modulo Theories) solver Yices as a catch-all decision procedure. Conditions that were not discharged automatically may be proved interactively using the PVS proof assistant. The programming workflow is very similar to the process by which a mathematical theory is developed inside a computer supported theorem prover environment such as PVS. The programmer reduces a large verification problem with the aid of the tool into a set of smaller problems (lemmas), and he can substantially improve the degree of proof automation by developing specialized background theories and proof strategies to support the specification and verification of a specific class of programs. We demonstrate this workflow by describing in detail the construction of a verified sorting algorithm. Tool-supported verification often has little to no presence in computer science (CS) curricula. Furthermore, program verification is frequently introduced as an advanced and purely theoretical topic that is not connected to the workflow taught in the early and practically oriented programming courses. Our hypothesis is that verification could be introduced early in the CS education, and that verification tools could be used in the classroom to support the teaching of formal methods. A prototype of Socos has been used in a course at Åbo Akademi University targeted at first and second year undergraduate students. We evaluate the use of Socos in the course as part of a case study carried out in 2007.

Exploring Adaptive Implementation of On-Chip Networks

As technology geometries have shrunk to the deep submicron regime, the communication delay and power consumption of global interconnections in high performance Multi- Processor Systems-on-Chip (MPSoCs) are becoming a major bottleneck. The Network-on- Chip (NoC) architecture paradigm, based on a modular packet-switched mechanism, can address many of the on-chip communication issues such as performance limitations of long interconnects and integration of large number of Processing Elements (PEs) on a chip. The choice of routing protocol and NoC structure can have a significant impact on performance and power consumption in on-chip networks. In addition, building a high performance, area and energy efficient on-chip network for multicore architectures requires a novel on-chip router allowing a larger network to be integrated on a single die with reduced power consumption. On top of that, network interfaces are employed to decouple computation resources from communication resources, to provide the synchronization between them, and to achieve backward compatibility with existing IP cores. Three adaptive routing algorithms are presented as a part of this thesis. The first presented routing protocol is a congestion-aware adaptive routing algorithm for 2D mesh NoCs which does not support multicast (one-to-many) traffic while the other two protocols are adaptive routing models supporting both unicast (one-to-one) and multicast traffic. A streamlined on-chip router architecture is also presented for avoiding congested areas in 2D mesh NoCs via employing efficient input and output selection. The output selection utilizes an adaptive routing algorithm based on the congestion condition of neighboring routers while the input selection allows packets to be serviced from each input port according to its congestion level. Moreover, in order to increase memory parallelism and bring compatibility with existing IP cores in network-based multiprocessor architectures, adaptive network interface architectures are presented to use multiple SDRAMs which can be accessed simultaneously. In addition, a smart memory controller is integrated in the adaptive network interface to improve the memory utilization and reduce both memory and network latencies. Three Dimensional Integrated Circuits (3D ICs) have been emerging as a viable candidate to achieve better performance and package density as compared to traditional 2D ICs. In addition, combining the benefits of 3D IC and NoC schemes provides a significant performance gain for 3D architectures. In recent years, inter-layer communication across multiple stacked layers (vertical channel) has attracted a lot of interest. In this thesis, a novel adaptive pipeline bus structure is proposed for inter-layer communication to improve the performance by reducing the delay and complexity of traditional bus arbitration. In addition, two mesh-based topologies for 3D architectures are also introduced to mitigate the inter-layer footprint and power dissipation on each layer with a small performance penalty.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Aging based maintenance and reinvestment scheduling of electric distribution

The maintenance of electric distribution network is a topical question for distribution system operators because of increasing significance of failure costs. In this dissertation the maintenance practices of the distribution system operators are analyzed and a theory for scheduling maintenance activities and reinvestment of distribution components is created. The scheduling is based on the deterioration of components and the increasing failure rates due to aging. The dynamic programming algorithm is used as a solving method to maintenance problem which is caused by the increasing failure rates of the network. The other impacts of network maintenance like environmental and regulation reasons are not included to the scope of this thesis. Further the tree trimming of the corridors and the major disturbance of the network are not included to the problem optimized in this thesis. For optimizing, four dynamic programming models are presented and the models are tested. Programming is made in VBA-language to the computer. For testing two different kinds of test networks are used. Because electric distribution system operators want to operate with bigger component groups, optimal timing for component groups is also analyzed. A maintenance software package is created to apply the presented theories in practice. An overview of the program is presented.

Electroactive ion exchange membranes based on conducting polymers

Ion exchange membranes are indispensable for the separation of ionic species. They can discriminate between anions and cations depending on the type of fixed ionic group present in the membrane. These conventional ion exchange membranes (CIX) have exceptional ionic conductivity, which is advantageous in various electromembrane separation processes such as electrodialysis, electrodeionisation and electrochemical ion exchange. The main disadvantage of CIX membranes is their high electrical resistance owing to the fact that the membranes are electronically non conductive. An alternative can be electroactive ion exchange membranes, which are ionically and electronically conducting. Polypyrrole (PPy) is a type of electroactive ion exchange material as well as a commonly known conducting polymer. When PPy membranes are repeatedly reduced and oxidised, ions are pumped through the membrane. The main aim of this thesis was to develop electroactive cation transport membranes based on PPy for the selective transport of divalent cations. Membranes developed composed of PPy films deposited on commercially available support materials. To carry out this study, cation exchange membranes based on PPy doped with immobile anions were prepared. Two types of dopant anions known to interact with divalent metal ions were considered, namely 4-sulphonic calix[6]arene (C6S) and carboxylated multiwalled carbon nanotubes (CNT). The transport of ions across membranes containing PPy doped with polystyrene sulphonate (PSS) and PPy doped with para-toluene sulphonate (pTS) was also studied in order to understand the nature of ion transport and permeability across PPy(CNT) and PPy(C6S) membranes. In the course of these studies, membrane characterisation was performed using electrochemical quartz crystal microbalance (EQCM) and scanning electron microscopy (SEM). Permeability of the membranes towards divalent cations was explored using a two compartment transport cell. EQCM results demonstrated that the ion exchange behaviour of polypyrrole is dependent on a number of factors including the type of dopant anion present, the type of ions present in the surrounding medium, the scan rate used during the experiment and the previous history of the polymer film. The morphology of PPy films was found to change when the dopant anion was varied and even when the thickness of the film was altered in some cases. In nearly all cases the permeability of the membranes towards metal ions followed the order K+ > Ca2+ > Mn2+. The one exception was PPy(C6S), for which the permeability followed the order Ca2+ ≥ K+ > Mn2+ > Co2+ > Cr3+. The above permeability sequences show a strong dependence on the size of the metal ions with metal ions having the smallest hydrated radii exhibiting the highest flux. Another factor that affected the permeability towards metal ions was the thickness of the PPy films. Films with the least thickness showed higher metal ion fluxes. Electrochemical control over ion transport across PPy(CNT) membrane was obtained when films composed of the latter were deposited on track-etched Nucleopore® membranes as support material. In contrast, the flux of ions across the same film was concentration gradient dependent when the polymer was deposited on polyvinylidene difluoride membranes as support material. However, electrochemical control over metal ion transport was achieved with a bilayer type of PPy film consisting of PPy(pTS)/PPy(CNT), irrespective of the type of support material. In the course of studying macroscopic charge balance during transport experiments performed using a two compartment transport cell, it was observed that PPy films were non-permselective. A clear correlation between the change in pH in the receiving solution and the ions transported across the membrane was observed. A decrease in solution pH was detected when the polymer membrane acted primarily as an anion exchanger, while an increase in pH occurred when it functioned as a cation exchanger. When there was an approximately equal flux of anions and cations across the polymer membrane, the pH in the receiving solution was in the range 6 - 8. These observations suggest that macroscopic charge balance during the transport of cations and anions across polypyrrole membranes was maintained by introduction of anions (OH-) and cations (H+) produced via electrolysis of water.

Power cycling lifetime estimation of IGBT power modules based on chip temperature modeling

In this doctoral thesis, methods to estimate the expected power cycling life of power semiconductor modules based on chip temperature modeling are developed. Frequency converters operate under dynamic loads in most electric drives. The varying loads cause thermal expansion and contraction, which stresses the internal boundaries between the material layers in the power module. Eventually, the stress wears out the semiconductor modules. The wear-out cannot be detected by traditional temperature or current measurements inside the frequency converter. Therefore, it is important to develop a method to predict the end of the converter lifetime. The thesis concentrates on power-cycling-related failures of insulated gate bipolar transistors. Two types of power modules are discussed: a direct bonded copper (DBC) sandwich structure with and without a baseplate. Most common failure mechanisms are reviewed, and methods to improve the power cycling lifetime of the power modules are presented. Power cycling curves are determined for a module with a lead-free solder by accelerated power cycling tests. A lifetime model is selected and the parameters are updated based on the power cycling test results. According to the measurements, the factor of improvement in the power cycling lifetime of modern IGBT power modules is greater than 10 during the last decade. Also, it is noticed that a 10 C increase in the chip temperature cycle amplitude decreases the lifetime by 40%. A thermal model for the chip temperature estimation is developed. The model is based on power loss estimation of the chip from the output current of the frequency converter. The model is verified with a purpose-built test equipment, which allows simultaneous measurement and simulation of the chip temperature with an arbitrary load waveform. The measurement system is shown to be convenient for studying the thermal behavior of the chip. It is found that the thermal model has a 5 C accuracy in the temperature estimation. The temperature cycles that the power semiconductor chip has experienced are counted by the rainflow algorithm. The counted cycles are compared with the experimentally verified power cycling curves to estimate the life consumption based on the mission profile of the drive. The methods are validated by the lifetime estimation of a power module in a direct-driven wind turbine. The estimated lifetime of the IGBT power module in a direct-driven wind turbine is 15 000 years, if the turbine is located in south-eastern Finland.

The nature of communication structures of university students in an international web-based computer-supported collaborative learning (CSCL) course

Communication, the flow of ideas and information between individuals in a social context, is the heart of educational experience. Constructivism and constructivist theories form the foundation for the collaborative learning processes of creating and sharing meaning in online educational contexts. The Learning and Collaboration in Technology-enhanced Contexts (LeCoTec) course comprised of 66 participants drawn from four European universities (Oulu, Turku, Ghent and Ramon Llull). These participants were split into 15 groups with the express aim of learning about computer-supported collaborative learning (CSCL). The Community of Inquiry model (social, cognitive and teaching presences) provided the content and tools for learning and researching the collaborative interactions in this environment. The sampled comments from the collaborative phase were collected and analyzed at chain-level and group-level, with the aim of identifying the various message types that sustained high learning outcomes. Furthermore, the Social Network Analysis helped to view the density of whole group interactions, as well as the popular and active members within the highly collaborating groups. It was observed that long chains occur in groups having high quality outcomes. These chains were also characterized by Social, Interactivity, Administrative and Content comment-types. In addition, high outcomes were realized from the high interactive cases and high-density groups. In low interactive groups, commenting patterned around the one or two central group members. In conclusion, future online environments should support high-order learning and develop greater metacognition and self-regulation. Moreover, such an environment, with a wide variety of problem solving tools, would enhance interactivity.

Research and development of III-V semiconductor surfaces for improved device interfaces

This thesis is devoted to understanding and improving technologically important III-V compound semiconductor (e.g. GaAs, InAs, and InSb) surfaces and interfaces for devices. The surfaces and interfaces of crystalline III-V materials have a crucial role in the operation of field-effect-transistors (FET) and highefficiency solar-cells, for instance. However, the surfaces are also the most defective part of the semiconductor material and it is essential to decrease the amount of harmful surface or interface defects for the next-generation III-V semiconductor device applications. Any improvement in the crystal ordering at the semiconductor surface reduces the amount of defects and increases the material homogeneity. This is becoming more and more important when the semiconductor device structures decrease to atomic-scale dimensions. Toward that target, the effects of different adsorbates (i.e., Sn, In, and O) on the III-V surface structures and properties have been investigated in this work. Furthermore, novel thin-films have been synthesized, which show beneficial properties regarding the passivation of the reactive III-V surfaces. The work comprises ultra-high-vacuum (UHV) environment for the controlled fabrication of atomically ordered III-V(100) surfaces. The surface sensitive experimental methods [low energy electron diffraction (LEED), scanning tunneling microscopy/spectroscopy (STM/STS), and synchrotron radiation photoelectron spectroscopy (SRPES)] and computational density-functionaltheory (DFT) calculations are utilized for elucidating the atomic and electronic properties of the crucial III-V surfaces. The basic research results are also transferred to actual device tests by fabricating metal-oxide-semiconductor capacitors and utilizing the interface sensitive measurement techniques [capacitance voltage (CV) profiling, and photoluminescence (PL) spectroscopy] for the characterization. This part of the thesis includes the instrumentation of home-made UHV-compatible atomic-layer-deposition (ALD) reactor for growing good quality insulator layers. The results of this thesis elucidate the atomic structures of technologically promising Sn- and In-stabilized III-V compound semiconductor surfaces. It is shown that the Sn adsorbate induces an atomic structure with (1×2)/(1×4) surface symmetry which is characterized by Sn-group III dimers. Furthermore, the stability of peculiar ζa structure is demonstrated for the GaAs(100)-In surface. The beneficial effects of these surface structures regarding the crucial III-V oxide interface are demonstrated. Namely, it is found that it is possible to passivate the III-V surface by a careful atomic-scale engineering of the III-V surface prior to the gate-dielectric deposition. The thin (1×2)/(1×4)-Sn layer is found to catalyze the removal of harmful amorphous III-V oxides. Also, novel crystalline III-V-oxide structures are synthesized and it is shown that these structures improve the device characteristics. The finding of crystalline oxide structures is exploited by solving the atomic structure of InSb(100)(1×2) and elucidating the electronic structure of oxidized InSb(100) for the first time.

Unidirectional fiber-reinforced composite as an oral implant abutment material: Experimental studies of E-glass fiber/BisGMA-TEGDMA polymer in vitro

Fiber-reinforced composites (FRCs) are a new group of non-metallic biomaterials showing a growing popularity in many dental and medical applications. As an oral implant material, FRC is biocompatible in bone tissue environment. Soft tissue integration to FRC polymer material is unclear. This series of in vitro studies aimed at evaluating unidirectional E-glass FRC polymer in terms of mechanical, chemical, and biological properties in an attempt to develop a new non-metallic oral implant abutment alternative. Two different types of substrates were investigated: (a) Plain polymer (BisGMA 50%–TEGDMA 50%) and (b) Unidirectional FRC. The mechanical behavior of high fiber-density FRCs was assessed using a three-point bending test. Surface characterization was performed using scanning electron and spinning disk confocal microscopes. The surface wettability/energy was determined using sessile drop method. The blood response, including blood-clotting ability and platelet morphology was evaluated. Human gingival fibroblast cell responses - adhesion kinetics, adhesion strength, and proliferation activity - were studied in cell culture environment using routine test conditions. A novel tissue culture method was developed and used to evaluate porcine gingival tissue graft attachment and growth on the experimental composite implants. The analysis of the mechanical properties showed that there is a direct proportionality in the relationship between E-glass fiber volume fraction and toughness, modulus of elasticity, and load bearing capacity; however, flexural strength did not show significant improvement when high fiber-density FRC is used. FRCs showed moderate hydrophilic properties owing to the presence of exposed glass fibers on the polymer surface. Blood-clotting time was shorter on FRC substrates than on plain polymer. The FRC substrates also showed higher platelet activation state than plain polymer substrates. Fibroblast cell adhesion strength and proliferation rate were highly pronounced on FRCs. A tissue culture study revealed that gingival epithelium and connective tissue established an immediate close contact with both plain polymer and FRC implants. However, FRC seemed to guide epithelial migration outwards from the tissue/implant interface. Due to the anisotropic and hydrophilic nature of FRC, it can be concluded that this material enhances biological events related with soft tissue integration on oral implant surface.

Manifestation of the pairing symmetry in the vortex core structure in iron-based superconductors

The superconducting gap is a basic character of a superconductor. While the cuprates and conventional phonon-mediated superconductors are characterized by distinct d- and s-wave pairing symmetries with nodal and nodeless gap distributions respectively, the superconducting gap distributions in iron-based superconductors are rather diversified. While nodeless gap distributions have been directly observed in Ba1–xKxFe2As2, BaFe2–xCoxAs2, LiFeAs, KxFe2–ySe2, and FeTe1–xSex, the signatures of a nodal superconducting gap have been reported in LaOFeP, LiFeP, FeSe, KFe2As2, BaFe2–xRuxAs2, and BaFe2(As1–xPx)2. Due to the multiplicity of the Fermi surface in these compounds s± and d pairing states can be both nodeless and nodal. A nontrivial orbital structure of the order parameter, in particular the presence of the gap nodes, leads to effects in which the disorder is much richer in dx2–y2-wave superconductors than in conventional materials. In contrast to the s-wave case, the Anderson theorem does not work, and nonmagnetic impurities exhibit a strong pair-breaking influence. In addition, a finite concentration of disorder produces a nonzero density of quasiparticle states at zero energy, which results in a considerable modification of the thermodynamic and transport properties at low temperatures. The influence of order parameter symmetry on the vortex core structure in iron-based pnictide and chalcogenide superconductors has been investigated in the framework of quasiclassical Eilenberger equations. The main results of the thesis are as follows. The vortex core characteristics, such as, cutoff parameter, ξh, and core size, ξ2, determined as the distance at which density of the vortex supercurrent reaches its maximum, are calculated in wide temperature, impurity scattering rate, and magnetic field ranges. The cutoff parameter, ξh(B; T; Г), determines the form factor of the flux-line lattice, which can be obtained in _SR, NMR, and SANS experiments. A comparison among the applied pairing symmetries is done. In contrast to s-wave systems, in dx2–y2-wave superconductors, ξh/ξc2 always increases with the scattering rate Г. Field dependence of the cutoff parameter affects strongly on the second moment of the magnetic field distributions, resulting in a significant difference with nonlocal London theory. It is found that normalized ξ2/ξc2(B/Bc2) dependence is increasing with pair-breaking impurity scattering (interband scattering for s±-wave and intraband impurity scattering for d-wave superconductors). Here, ξc2 is the Ginzburg-Landau coherence length determined from the upper critical field Bc2 = Φ0/2πξ2 c2, where Φ0 is a flux quantum. Two types of ξ2/ξc2 magnetic field dependences are obtained for s± superconductors. It has a minimum at low temperatures and small impurity scattering transforming in monotonously decreasing function at strong scattering and high temperatures. The second kind of this dependence has been also found for d-wave superconductors at intermediate and high temperatures. In contrast, impurity scattering results in decreasing of ξ2/ξc2(B/Bc2) dependence in s++ superconductors. A reasonable agreement between calculated ξh/ξc2 values and those obtained experimentally in nonstoichiometric BaFe2–xCoxAs2 (μSR) and stoichiometric LiFeAs (SANS) was found. The values of ξh/ξc2 are much less than one in case of the first compound and much more than one for the other compound. This is explained by different influence of two factors: the value of impurity scattering rate and pairing symmetry.