Multiscale study on hydrogen mobility in metallic fusion divertor material

For achieving efficient fusion energy production, the plasma-facing wall materials of the fusion reactor should ensure long time operation. In the next step fusion device, ITER, the first wall region facing the highest heat and particle load, i.e. the divertor area, will mainly consist of tiles based on tungsten. During the reactor operation, the tungsten material is slowly but inevitably saturated with tritium. Tritium is the relatively short-lived hydrogen isotope used in the fusion reaction. The amount of tritium retained in the wall materials should be minimized and its recycling back to the plasma must be unrestrained, otherwise it cannot be used for fueling the plasma. A very expensive and thus economically not viable solution is to replace the first walls quite often. A better solution is to heat the walls to temperatures where tritium is released. Unfortunately, the exact mechanisms of hydrogen release in tungsten are not known. In this thesis both experimental and computational methods have been used for studying the release and retention of hydrogen in tungsten. The experimental work consists of hydrogen implantations into pure polycrystalline tungsten, the determination of the hydrogen concentrations using ion beam analyses (IBA) and monitoring the out-diffused hydrogen gas with thermodesorption spectrometry (TDS) as the tungsten samples are heated at elevated temperatures. Combining IBA methods with TDS, the retained amount of hydrogen is obtained as well as the temperatures needed for the hydrogen release. With computational methods the hydrogen-defect interactions and implantation-induced irradiation damage can be examined at the atomic level. The method of multiscale modelling combines the results obtained from computational methodologies applicable at different length and time scales. Electron density functional theory calculations were used for determining the energetics of the elementary processes of hydrogen in tungsten, such as diffusivity and trapping to vacancies and surfaces. Results from the energetics of pure tungsten defects were used in the development of an classical bond-order potential for describing the tungsten defects to be used in molecular dynamics simulations. The developed potential was utilized in determination of the defect clustering and annihilation properties. These results were further employed in binary collision and rate theory calculations to determine the evolution of large defect clusters that trap hydrogen in the course of implantation. The computational results for the defect and trapped hydrogen concentrations were successfully compared with the experimental results. With the aforedescribed multiscale analysis the experimental results within this thesis and found in the literature were explained both quantitatively and qualitatively.

Computer simulation of H and He effects in fusion reactor materials

Fusion power is an appealing source of clean and abundant energy. The radiation resistance of reactor materials is one of the greatest obstacles on the path towards commercial fusion power. These materials are subject to a harsh radiation environment, and cannot fail mechanically or contaminate the fusion plasma. Moreover, for a power plant to be economically viable, the reactor materials must withstand long operation times, with little maintenance. The fusion reactor materials will contain hydrogen and helium, due to deposition from the plasma and nuclear reactions because of energetic neutron irradiation. The first wall divertor materials, carbon and tungsten in existing and planned test reactors, will be subject to intense bombardment of low energy deuterium and helium, which erodes and modifies the surface. All reactor materials, including the structural steel, will suffer irradiation of high energy neutrons, causing displacement cascade damage. Molecular dynamics simulation is a valuable tool for studying irradiation phenomena, such as surface bombardment and the onset of primary damage due to displacement cascades. The governing mechanisms are on the atomic level, and hence not easily studied experimentally. In order to model materials, interatomic potentials are needed to describe the interaction between the atoms. In this thesis, new interatomic potentials were developed for the tungsten-carbon-hydrogen system and for iron-helium and chromium-helium. Thus, the study of previously inaccessible systems was made possible, in particular the effect of H and He on radiation damage. The potentials were based on experimental and ab initio data from the literature, as well as density-functional theory calculations performed in this work. As a model for ferritic steel, iron-chromium with 10% Cr was studied. The difference between Fe and FeCr was shown to be negligible for threshold displacement energies. The properties of small He and He-vacancy clusters in Fe and FeCr were also investigated. The clusters were found to be more mobile and dissociate more rapidly than previously assumed, and the effect of Cr was small. The primary damage formed by displacement cascades was found to be heavily influenced by the presence of He, both in FeCr and W. Many important issues with fusion reactor materials remain poorly understood, and will require a huge effort by the international community. The development of potential models for new materials and the simulations performed in this thesis reveal many interesting features, but also serve as a platform for further studies.

Microstructural evolution during laser resolidification of Fe-25 atom percent Ge alloy

The microstructural evolution of concentrated alloys is relatively less understood both in terms of experiments as well as theory. Laser resolidification represents a powerful technique to study the solidification behavior under controlled growth conditions. This technique has been utilized in the current study to probe experimentally microstructural selection during rapid solidification of concentrated Fe-25 atom pct Ge alloy. Under the equilibrium solidification condition, the alloy undergoes a peritectic reaction between ordered alpha(2) (B2) and its liquid, leading to the formation of ordered hexagonal intermetallic phase epsilon (DO19). In general, the as-cast microstructure consists of epsilon phase and e-p eutectic and alpha(2) that forms as a result of an incomplete peritectic reaction. With increasing laser scanning velocity, the solidification front undergoes a number of morphological transitions leading to the selection of the microstructure corresponding to metastable alpha(2)/beta eutectic to alpha(2) dendrite + alpha(2)/beta eutectic to alpha(2) dendrite. The transition velocities as obtained from the experiments are well characterized. The microstructural selection is discussed using competitive growth kinetics.

Efficient content-based image retrieval based on multi-feature fusion

The increased availability of image capturing devices has enabled collections of digital images to rapidly expand in both size and diversity. This has created a constantly growing need for efficient and effective image browsing, searching, and retrieval tools. Pseudo-relevance feedback (PRF) has proven to be an effective mechanism for improving retrieval accuracy. An original, simple yet effective rank-based PRF mechanism (RB-PRF) that takes into account the initial rank order of each image to improve retrieval accuracy is proposed. This RB-PRF mechanism innovates by making use of binary image signatures to improve retrieval precision by promoting images similar to highly ranked images and demoting images similar to lower ranked images. Empirical evaluations based on standard benchmarks, namely Wang, Oliva & Torralba, and Corel datasets demonstrate the effectiveness of the proposed RB-PRF mechanism in image retrieval.

Selection of intrusion detection system threshold bounds for effective sensor fusion

The motivation behind the fusion of Intrusion Detection Systems was the realization that with the increasing traffic and increasing complexity of attacks, none of the present day stand-alone Intrusion Detection Systems can meet the high demand for a very high detection rate and an extremely low false positive rate. Multi-sensor fusion can be used to meet these requirements by a refinement of the combined response of different Intrusion Detection Systems. In this paper, we show the design technique of sensor fusion to best utilize the useful response from multiple sensors by an appropriate adjustment of the fusion threshold. The threshold is generally chosen according to the past experiences or by an expert system. In this paper, we show that the choice of the threshold bounds according to the Chebyshev inequality principle performs better. This approach also helps to solve the problem of scalability and has the advantage of failsafe capability. This paper theoretically models the fusion of Intrusion Detection Systems for the purpose of proving the improvement in performance, supplemented with the empirical evaluation. The combination of complementary sensors is shown to detect more attacks than the individual components. Since the individual sensors chosen detect sufficiently different attacks, their result can be merged for improved performance. The combination is done in different ways like (i) taking all the alarms from each system and avoiding duplications, (ii) taking alarms from each system by fixing threshold bounds, and (iii) rule-based fusion with a priori knowledge of the individual sensor performance. A number of evaluation metrics are used, and the results indicate that there is an overall enhancement in the performance of the combined detector using sensor fusion incorporating the threshold bounds and significantly better performance using simple rule-based fusion.

Characterization of a continuous CO2 laser-welded Fe-Cu dissimilar couple

Continuous CO2 laser welding of an Fe-Cu dissimilar couple in a butt-weld geometry at different process conditions is studied. The process conditions are varied to identify and characterize the microstructural features that are independent of the welding mode. The study presents a characterization of the microstructure and mechanical properties of the welds. Detailed microstructural analysis of the weld/base-metal interface shows features that are different on the two sides of the weld. The iron side can grow into the weld with a local change in length scale, whereas the interface on the copper side indicates a barrier to growth. The interface is jagged, and a banded microstructure consisting of iron-rich layers could be observed next to the weld/Cu interface. The observations suggest that solidification initiates inside the melt, where iron and copper are mixed due to convective flow. The transmission electron microscopy (TEM) of the weld region also indicates the occasional presence of droplets of iron and copper. The microstructural observations are rationalized using arguments drawn from a thermodynamic analysis of the Fe-Cu system.

Functional role of the Mso1p-Sec1p complex in membrane fusion regulation

Sec1/Munc18 (SM) protein family members are evolutionary conserved proteins. They perform an essential, albeit poorly understood function in SNARE complex formation in membrane fusion. In addition to the SNARE complex components, only a few SM protein binding proteins are known. Typically, their binding modes to SM proteins and their contribution to the membrane fusion regulation is poorly characterised. We identified Mso1p as a novel Sec1p interacting partner. It was shown that Mso1p and Sec1p interact at sites of polarised secretion and that this localisation is dependent on the Rab GTPase Sec4p and its GEF Sec2p. Using targeted mutagenesis and N- and C-terminal deletants, it was discovered that the interaction between an N-terminal peptide of Mso1p and the putative Syntaxin N-peptide binding area in Sec1p domain 1 is important for membrane fusion regulation. The yeast Syntaxin homologues Sso1p and Sso2p lack the N-terminal peptide. Our results show that in addition to binding to the putative N-peptide binding area in Sec1p, Mso1p can interact with Sso1p and Sso2p. This result suggests that Mso1p can mimic the N-peptide binding to facilitate membrane fusion. In addition to Mso1p, a novel role in membrane fusion regulation was revealed for the Sec1p C-terminal tail, which is missing in its mammalian homologues. Deletion of the Sec1p-tail results in temperature sensitive growth and reduced sporulation. Using in vivo and in vitro experiments, it was shown that the Sec1p-tail mediates SNARE complex binding and assembly. These results propose a regulatory role for the Sec1p-tail in SNARE complex formation. Furthermore, two novel interaction partners for Mso1p, the Rab GTPase Sec4p and plasma membrane phospholipids, were identified. The Sec4p link was identified using Bimolecular Fluorescence Complementation assays with Mso1p and the non-SNARE binding Sec1p(1-657). The assay revealed that Mso1p can target Sec1p(1-657) to sites of secretion. This effect is mediated via the Mso1p C-terminus, which previously has been genetically linked to Sec4p. These results and in vitro binding experiments suggest that Mso1p acts in cooperation with the GTP-bound form of Sec4p on vesicle-like structures prior to membrane fusion. Mso1p shares homology with the PIP2 binding domain of the mammalian Munc18 binding Mint proteins. It was shown both in vivo and in vitro that Mso1p is a phospholipid inserting protein and that this insertion is mediated by the conserved Mso1p amino terminus. In vivo, the Mso1p phospholipid binding is needed for sporulation and Mso1p-Sec1p localisation at the sites of secretion at the plasma membrane. The results reveal a novel layer of membrane fusion regulation in exocytosis and propose a coordinating role for Mso1p in connection with membrane lipids, Sec1p, Sec4p and SNARE complexes in this process.

Data fusion and matching by maximizing statistical dependencies

The core aim of machine learning is to make a computer program learn from the experience. Learning from data is usually defined as a task of learning regularities or patterns in data in order to extract useful information, or to learn the underlying concept. An important sub-field of machine learning is called multi-view learning where the task is to learn from multiple data sets or views describing the same underlying concept. A typical example of such scenario would be to study a biological concept using several biological measurements like gene expression, protein expression and metabolic profiles, or to classify web pages based on their content and the contents of their hyperlinks. In this thesis, novel problem formulations and methods for multi-view learning are presented. The contributions include a linear data fusion approach during exploratory data analysis, a new measure to evaluate different kinds of representations for textual data, and an extension of multi-view learning for novel scenarios where the correspondence of samples in the different views or data sets is not known in advance. In order to infer the one-to-one correspondence of samples between two views, a novel concept of multi-view matching is proposed. The matching algorithm is completely data-driven and is demonstrated in several applications such as matching of metabolites between humans and mice, and matching of sentences between documents in two languages.

Microstructural Evolution during Laser Resolidification of Fe-18 At. Pct Ge Alloy

The technique of laser resolidification has been used to study the rapid solidification behavior of concentrated Fe-18 at. pct Ge alloy. The microstructural evolution has been studied as a function of scanning rate of laser beam. Scanning electron microscopy (SEM) reveals the formation of a two-layer (designated as "A" and "B") microstructure in the remelted pool. The A layer shows a band consisting of a network of interconnected channels and walls, quite similar to cell walls. The B layer shows dendritic growth. Transmission electron microscopic observations reveal the formation of bcc alpha-FeGe in the B layer. Laser melting has been found to play an important role in formation of the A layer. Microstructural evolution in B has been analyzed using the competitive growth criterion, and formation of bcc alpha-FeGe has been rationalized in the remelted layers.

A fast time-domain algorithm for the assessment of tissue blood flow in laser-Doppler flowmetry

In this study, we derive a fast, novel time-domain algorithm to compute the nth-order moment of the power spectral density of the photoelectric current as measured in laser-Doppler flowmetry (LDF). It is well established that in the LDF literature these moments are closely related to fundamental physiological parameters, i.e. concentration of moving erythrocytes and blood flow. In particular, we take advantage of the link between moments in the Fourier domain and fractional derivatives in the temporal domain. Using Parseval's theorem, we establish an exact analytical equivalence between the time-domain expression and the conventional frequency-domain counterpart. Moreover, we demonstrate the appropriateness of estimating the zeroth-, first- and second-order moments using Monte Carlo simulations. Finally, we briefly discuss the feasibility of implementing the proposed algorithm in hardware.

Laser processing of high-Tc superconducting thin films

High-Tc superconducting thin films can be deposited and processed by pulsed and CW lasers, and a respectable materials technology for the Y-Ba-Cu-O superconductor is rapidly emerging. The pulsed laser deposition technique is simple because it produces films with compositions nearly identical to those of the target pellets. A larger variety of substrates can be used, compared to other deposition technologies, because of the relatively low temperature requirements. The laser deposition mechanism has been investigated. As-deposited superconducting films, epitaxial films with smooth surfaces, and multilayer structures with abrupt interfaces have been produced. The electrical transport properties can be changed locally using a focused argon-ion laser by modifying the oxygen stoichiometry. This laser writing can be erased by room-temperature exposure to an oxygen plasma. Other laser patterning methods such as material removal, melt-quench, and direct pattern transfer are being developed.

Heteroepitaxial Yba2cu3o7-X-Prba2cu3o7-X-Yba2cu3o7-X Weak Links Grown By Laser Deposition

Summary form only given. The authors have developed a controllable HTSC (high-temperature superconductor) weak-link fabrication process for producing weak links from the high-temperature superconductor YBa2Cu3O7-x (YBCO), using PrBa2Cu3O7-x (PBCO) as a lattice-matched semiconducting barrier layer. The devices obtained show current-voltage characteristics similar to those observed for low-temperature superconductor/normal-metal/superconductor (SNS) devices. The authors found good scaling of the critical currents Ic with area, A, and scaling of the resistances Rj with 1/A; the typical values of the IcRj product of 3.5 mV are consistent with traditional SNS behavior. The authors observed Shapiro steps in response to 100-GHz millimeter-wave radiation and oscillation of the DC supercurrent in a transverse magnetic field, thus demonstrating that both the AC and DC Josephson effects occur in these devices.

Low temperature processing and chacterization of SrBi2Nb2O9 thin films grown by pulsed laser ablation

Ex-situ grown thin films of SrBi2Nb2O9 (SBN) were deposited on platinum substrates using laser ablation technique. A low substrate-temperature-processing route was chosen to avoid any diffusion of bismuth into the Pt electrode. It was observed that the as grown films showed an oriented growth along the 'c'-axis (with zero spontaneous polarization). The as grown films were subsequently annealed to enhance crystallization. Upon annealing, these films transformed into a polycrystalline structure, and exhibited excellent ferroelectric properties. The switching was made to be possible by lowering the thickness without losing the electrically insulating behavior of the films. The hysteresis results showed an excellent square-shaped loop with results (P-r = 4 muC/cm(2) E-c = 90 kV/cm) in good agreement with the earlier reports. The films also exhibited a dielectric constant of 190 and a dissipation factor of 0.02, which showed dispersion at low frequencies. The frequency dispersion was found to obey Jonscher's universal power law relation, and was attributed to the ionic charge hopping process according to earlier reports. The de transport studies indicated an ohmic behavior in the low voltage region, while higher voltages induced a bulk space charge and resulted in non-linear current-voltage dependence.

Time-dependent analysis of an N2O gasdynamic laser

A simplified two-temperature model is presented for the vibrational energy levels of the N2O and N2 molecules of an N2O-N2-He gasdynamic laser (GDL), and the governing equations for the unsteady flow of the gas mixture in a convergent-divergent contour nozzle are solved using a time-dependent numerical technique. Final steady-state distributions are obtained for vibrational temperatures, population inversion, and the small-signal laser gain along the nozzle. It is demonstrated that, for plenum temperatures lower than 1200 K, an N2O GDL such as the present is more efficient than a CO2 GDL in identical operating conditions