37 research outputs found

    Applications of Molecular Dynamics simulations for biomolecular systems and improvements to density-based clustering in the analysis

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    Molecular Dynamics simulations provide a powerful tool to study biomolecular systems with atomistic detail. The key to better understand the function and behaviour of these molecules can often be found in their structural variability. Simulations can help to expose this information that is otherwise experimentally hard or impossible to attain. This work covers two application examples for which a sampling and a characterisation of the conformational ensemble could reveal the structural basis to answer a topical research question. For the fungal toxin phalloidin—a small bicyclic peptide—observed product ratios in different cyclisation reactions could be rationalised by assessing the conformational pre-organisation of precursor fragments. For the C-type lectin receptor langerin, conformational changes induced by different side-chain protonations could deliver an explanation of the pH-dependency in the protein’s calcium-binding. The investigations were accompanied by the continued development of a density-based clustering protocol into a respective software package, which is generally well applicable for the use case of extracting conformational states from Molecular Dynamics data

    Quantum gates and Bose-Hubbard models with dipolar systems

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    Ultracold dipolar systems, featuring strong long-range dipole-dipole interactions, have been brought under increasing quantum control over recent years. In this thesis, we study the use of these properties for quantum information processing and simulation of many-body Bose-Hubbard models with off-site interactions. We first investigate robust entangling protocols for polar molecules, finding that shaped microwave pulses provide two-qubit entangling gates based on the dipole-dipole interaction with robustness to experimentally-relevant errors. We then numerically study the ground state properties of hard-core dipolar bosons confined in cylindrical optical lattices, where the curved lattice surface causes the anisotropic dipole-dipole interactions to vary around the ring of the cylinder. This expands the physics of analogous square lattice models due to the cooperation and competition of the interactions in different directions. Finally, we investigate the applicability of the lowest-band dipolar Bose-Hubbard model itself by comparing lattice and continuum methods for small systems of strongly interacting dipolar bosons in optical lattice potentials

    Advantages and Disadvantages of Electronic Cigarettes

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    Electronic cigarettes (ECs) have been present on the consumer market for over a decade, and the number of related scientific publications in the PubMed database has now exceeded seven thousand. Despite the number of publications, there is still no consensus in the scientific community regarding their safety. However, it should be emphasized that a comparison of equivalent quantities of tobacco smoke and the aerosol produced from e-cigarettes showed that there was a significantly lower quantity of toxic compounds in the aerosol compared with the tobacco smoke. Therefore, the use of ECs could be seen as a way of reducing the health damage to cigarette smokers who cannot or are unwilling to quit using conventional methods. In addition, randomized studies are emerging suggesting that ECs could be useful in smoking cessation. On the other hand, ECs are now widely used among adolescents and may pose a serious risk of future nicotine dependence and health problems in this population, as they counteract their advantages in the population gained from smokers who quit using them. Therefore, as most authors stress, further research that will convincingly resolve the current controversies is needed. Clinicians urgently need evidence-based knowledge to better inform their patients about the use of these emerging tobacco products as a harm-reduction strategy, and regulators should regulate these products in ways that best serve public health, especially taking the youth population into account

    Methods and Results of Power Cycling Tests for Semiconductor Power Devices

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    This work intends to enhance the state of the research in power cycling tests with statements on achievable measurement accuracy, proposed test bench topologies and recommendations on improved test strategies for various types of semiconductor power devices. Chapters 1 and 2 describe the current state of the power cycling tests in the context of design for reliability comprising applicable standards and lifetime models. Measurement methods in power cycling tests for the essential physical parameters are explained in chapter 3. The dynamic and static measurement accuracy of voltage, current and temperature are discussed. The feasibly achievable measurement delay tmd of the maximal junction temperature Tjmax, its consequences on accuracy and methods to extrapolate to the time point of the turn-off event are explained. A method to characterize the thermal path of devices to the heatsink via measurements of the thermal impedance Zth is explained. Test bench topologies starting from standard setups, single to multi leg DC benches are discussed in chapter 4. Three application-closer setups implemented by the author are explained. For tests on thyristors a test concept with truncated sinusoidal current waveforms and online temperature measurement is introduced. An inverter-like topology with actively switching IGBTs is presented. In contrast to standard setups, there the devices under test prove switching capability until reaching the end-of-life criteria. Finally, a high frequency switching topology with low DC-link voltage and switching losses contributing significantly to the overall power losses is presented providing new degrees of freedom for setting test conditions. The particularities of semiconductor power devices in power cycling tests are thematized in chapter 5. The first part describes standard packages and addressed failure mechanisms in power cycling. For all relevant power electronic devices in silicon and silicon carbide, the devices’ characteristics, methods for power cycling and their consequences for test results are explained. The work is concluded and suggestions for future work are given in chapter 6.:Abstract 1 Kurzfassung 3 Acknowledgements 5 Nomenclature 10 Abbreviations 10 Symbols 12 1 Introduction 19 2 Applicable Standards and Lifetime Models 25 3 Measurement parameters in power cycling tests 53 4 Test Bench Topologies 121 5 Semiconductor Power Devices in Power Cycling 158 6 Conclusion and Outlook 229 References 235 List of Publications 253 Theses 257Diese Arbeit bereichert den Stand der Wissenschaft auf dem Gebiet von Lastwechseltests mit Beiträgen zu verbesserter Messgenauigkeit, vorgeschlagenen Teststandstopologien und verbesserten Teststrategien für verschiedene Arten von leistungselektronischen Bauelementen. Kurzgefasst der Methodik von Lastwechseltests. Das erste Themengebiet in Kapitel 1 und Kapitel 2 beschreibt den aktuellen Stand zu Lastwechseltests im Kontext von Design für Zuverlässigkeit, welcher in anzuwendenden Standards und publizierten Lebensdauermodellen dokumentiert ist. Messmethoden für relevante physikalische Parameter in Lastwechseltests sind in Kapitel 3. erläutert. Zunächst werden dynamische und statische Messgenauigkeit für Spannung, Strom und Temperaturen diskutiert. Die tatsächlich erreichbare Messverzögerung tMD der maximalen Sperrschichttemperatur Tjmax und deren Auswirkung auf die Messgenauigkeit der Lastwechselfestigkeit wird dargelegt. Danach werden Methoden zur Rückextrapolation zum Zeitpunkt des Abschaltvorgangs des Laststroms diskutiert. Schließlich wird die Charakterisierung des Wärmepfads vom Bauelement zur Wärmesenke mittels Messung der thermischen Impedanz Zth behandelt. In Kapitel 4 werden Teststandstopologien beginnend mit standardmäßig genutzten ein- und mehrsträngigen DC-Testständen vorgestellt. Drei vom Autor umgesetzte anwendungsnahe Topologien werden erklärt. Für Tests mit Thyristoren wird ein Testkonzept mit angeschnittenem sinusförmigem Strom und in situ Messung der Sperrschichttemperatur eingeführt. Eine umrichterähnliche Topologie mit aktiv schaltenden IGBTs wird vorgestellt. Zuletzt wird eine Topologie mit hoch frequent schaltenden Prüflingen an niedriger Gleichspannung bei der Schaltverluste signifikant zur Erwärmung der Prüflinge beitragen vorgestellt. Dies ermöglicht neue Freiheitsgrade um Testbedingungen zu wählen. Die Besonderheiten von leistungselektronischen Bauelementen werden in Kapitel 5 thematisiert. Der erste Teil beschreibt Gehäusetypen und adressierte Fehlermechanismen in Lastwechseltests. Für alle untersuchten Bauelementtypen in Silizium und Siliziumkarbid werden Charakteristiken, empfohlene Methoden für Lastwechseltests und Einflüsse auf Testergebnisse erklärt. Die Arbeit wird in Kapitel 6 zusammengefasst und Vorschläge zu künftigen Arbeiten werden unterbreitet.:Abstract 1 Kurzfassung 3 Acknowledgements 5 Nomenclature 10 Abbreviations 10 Symbols 12 1 Introduction 19 2 Applicable Standards and Lifetime Models 25 3 Measurement parameters in power cycling tests 53 4 Test Bench Topologies 121 5 Semiconductor Power Devices in Power Cycling 158 6 Conclusion and Outlook 229 References 235 List of Publications 253 Theses 25

    Artificial Intelligence Supported EV Electric Powertrain for Safety Improvement

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    As an environmentally friendly transport option, electric vehicles (EVs) are endowed with the characteristics of low fossil energy consumption and low pollutant emissions. In today's growing market share of EVs, the safety and reliability of the powertrain system will be directly related to the safety of human life. Reliability problems of EV powertrains may occur in any power electronic (PE) component and mechanical part, both sudden and cumulative. These faults in different locations and degrees will continuously threaten the life of drivers and pedestrians, bringing irreparable consequences. Therefore, monitoring and predicting the real-time health status of EV powertrain is a high-priority, arduous and challenging task. The purposes of this study are to develop AI-supported effective safety improvement techniques for EV powertrains. In the first place, a literature review is carried out to illustrate the up-to-date AI applications for solving condition monitoring and fault detection issues of EV powertrains, where recent case studies between conventional methods and AI-based methods in EV applications are compared and analysed. On this ground this study, then, focuses on the theories and techniques concerning this topic so as to tackle different challenges encountered in the actual applications. In detail, first, as for diagnosing the bearing system in the earlier fault period, a novel inferable deep distilled attention network is designed to detect multiple bearing faults. Second, a deep learning and simulation driven approach that combines the domain-adversarial neural network and the lumped-parameter thermal network (LPTN) is proposed for achieve IPMSM permanent magnet temperature estimation work. Finally, to ensure the use safety of the IGBT module, deep learning -based IGBT modules’ double pulse test (DPT) efficiency enhancement is proposed and achieved via multimodal fusion networks and graph convolution networks

    ECOS 2012

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    The 8-volume set contains the Proceedings of the 25th ECOS 2012 International Conference, Perugia, Italy, June 26th to June 29th, 2012. ECOS is an acronym for Efficiency, Cost, Optimization and Simulation (of energy conversion systems and processes), summarizing the topics covered in ECOS: Thermodynamics, Heat and Mass Transfer, Exergy and Second Law Analysis, Process Integration and Heat Exchanger Networks, Fluid Dynamics and Power Plant Components, Fuel Cells, Simulation of Energy Conversion Systems, Renewable Energies, Thermo-Economic Analysis and Optimisation, Combustion, Chemical Reactors, Carbon Capture and Sequestration, Building/Urban/Complex Energy Systems, Water Desalination and Use of Water Resources, Energy Systems- Environmental and Sustainability Issues, System Operation/ Control/Diagnosis and Prognosis, Industrial Ecology

    Miniaturized Transistors, Volume II

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    In this book, we aim to address the ever-advancing progress in microelectronic device scaling. Complementary Metal-Oxide-Semiconductor (CMOS) devices continue to endure miniaturization, irrespective of the seeming physical limitations, helped by advancing fabrication techniques. We observe that miniaturization does not always refer to the latest technology node for digital transistors. Rather, by applying novel materials and device geometries, a significant reduction in the size of microelectronic devices for a broad set of applications can be achieved. The achievements made in the scaling of devices for applications beyond digital logic (e.g., high power, optoelectronics, and sensors) are taking the forefront in microelectronic miniaturization. Furthermore, all these achievements are assisted by improvements in the simulation and modeling of the involved materials and device structures. In particular, process and device technology computer-aided design (TCAD) has become indispensable in the design cycle of novel devices and technologies. It is our sincere hope that the results provided in this Special Issue prove useful to scientists and engineers who find themselves at the forefront of this rapidly evolving and broadening field. Now, more than ever, it is essential to look for solutions to find the next disrupting technologies which will allow for transistor miniaturization well beyond silicon’s physical limits and the current state-of-the-art. This requires a broad attack, including studies of novel and innovative designs as well as emerging materials which are becoming more application-specific than ever before

    Simulated Annealing

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    The book contains 15 chapters presenting recent contributions of top researchers working with Simulated Annealing (SA). Although it represents a small sample of the research activity on SA, the book will certainly serve as a valuable tool for researchers interested in getting involved in this multidisciplinary field. In fact, one of the salient features is that the book is highly multidisciplinary in terms of application areas since it assembles experts from the fields of Biology, Telecommunications, Geology, Electronics and Medicine

    Probabilistic learning on graphs via contextual architectures

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    We propose a novel methodology for representation learning on graph-structured data, in which a stack of Bayesian Networks learns different distributions of a vertex's neighbour- hood. Through an incremental construction policy and layer-wise training, we can build deeper architectures with respect to typical graph convolutional neural networks, with benefits in terms of context spreading between vertices. First, the model learns from graphs via maximum likelihood estimation without using target labels. Then, a supervised readout is applied to the learned graph embeddings to deal with graph classification and vertex classification tasks, showing competitive results against neural models for graphs. The computational complexity is linear in the number of edges, facilitating learning on large scale data sets. By studying how depth affects the performances of our model, we discover that a broader context generally improves performances. In turn, this leads to a critical analysis of some benchmarks used in literature

    The bracket geometry of statistics

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    In this thesis we build a geometric theory of Hamiltonian Monte Carlo, with an emphasis on symmetries and its bracket generalisations, construct the canonical geometry of smooth measures and Stein operators, and derive the complete recipe of measure-constraints preserving dynamics and diffusions on arbitrary manifolds. Specifically, we will explain the central role played by mechanics with symmetries to obtain efficient numerical integrators, and provide a general method to construct explicit integrators for HMC on geodesic orbit manifolds via symplectic reduction. Following ideas developed by Maxwell, Volterra, Poincaré, de Rham, Koszul, Dufour, Weinstein, and others, we will then show that any smooth distribution generates considerable geometric content, including ``musical" isomorphisms between multi-vector fields and twisted differential forms, and a boundary operator - the rotationnel, which, in particular, engenders the canonical Stein operator. We then introduce the ``bracket formalism" and its induced mechanics, a generalisation of Poisson mechanics and gradient flows that provides a general mechanism to associate unnormalised probability densities to flows depending on the score pointwise. Most importantly, we will characterise all measure-constraints preserving flows on arbitrary manifolds, showing the intimate relation between measure-preserving Nambu mechanics and closed twisted forms. Our results are canonical. As a special case we obtain the characterisation of measure-preserving bracket mechanical systems and measure-preserving diffusions, thus explaining and extending to manifolds the complete recipe of SGMCMC. We will discuss the geometry of Stein operators and extend the density approach by showing these are simply a reformulation of the exterior derivative on twisted forms satisfying Stokes' theorem. Combining the canonical Stein operator with brackets allows us to naturally recover the Riemannian and diffusion Stein operators as special cases. Finally, we shall introduce the minimum Stein discrepancy estimators, which provide a unifying perspective of parameter inference based on score matching, contrastive divergence, and minimum probability flow.Open Acces
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