80.00.00 INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY
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Der Ausbau der regenerativen Energiequellen führt vermehrt zu unvorhersehbaren Schwankungen der erzeugten Leistung, da Windkraft und Photovoltaik von natürlichen Bedingungen abhängen. Gerade Kurzzeitfluktuationen im Sekunden- bis Minutenbereich, die bei Solarzellen durch die Verschattung von vorüberziehenden Wolken zustande kommen, wird bislang wenig Beachtung geschenkt. Kurzzeitspeicher müssen eine hohe Zyklenstabilität aufweisen, um zur Glättung dieser Leistungsfluktuationen in Frage zu kommen. Im Rahmen der vorliegenden Dissertation wurden elektrochemische Doppelschichtkondensatoren für die Kopplung mit Siliziumsolarzellen und organischen Solarmodulen mit Hilfe von Simulationen und Messungen untersucht. Zusätzlich wurden grundlegende Fragestellungen zur Prozessierung und Alterung von Doppelschichtkondensatoren im Hinblick auf ein in der Literatur bereits diskutiertes System betrachtet, das beide Komponenten in einem Bauteil integriert - den sogenannten photocapacitor.
Um die Druckbarkeit des gesamten elektrochemischen Doppelschichtkondensators zu ermöglichen, wurde der konventionell verwendete Flüssigelektrolyt durch einen Polymer-Gel-Elektrolyten auf Basis von Polyvinylalkohol und einer Säure ersetzt. Durch eine Verbesserung der Prozessierung konnte ein größerer Anteil der spezifischen Fläche der porösen Kohlenstoffelektroden vom Elektrolyten benetzt und somit zur Speicherung genutzt werden. Die Untersuchungen zeigen, dass mit Polymer-Gel-Elektrolyten ähnliche Kapazitäten erreicht werden wie mit Flüssigelektrolyten. Im Hinblick auf die Anwendung im gekoppelten System muss der elektrochemische Doppelschichtkondensator den gleichen Umweltbedingungen hinsichtlich Temperatur und Luftfeuchte standhalten wie die Solarzelle. Hierzu wurden umfangreiche Alterungstests durchgeführt und festgestellt, dass die Kapazität zwar bei Austrocknung des wasserhaltigen Polymer-Gel-Elektrolyten sinkt, bei einer Wiederbefeuchtung aber auch eine Regeneration des Speichers erfolgt.
Zur passenden Auslegung des elektrochemischen Doppelschichtkondensators wurde eine detaillierte Analyse der Leistungsfluktuationen durchgeführt, die mit einem eigens entwickelten MPP-Messgerät an organischen Solarmodulen gemessen wurden. Anhand der Daten wurde analysiert, welche Energiemengen für welche Zeit im Kurzzeitspeicher zwischengespeichert werden müssen, um eine effiziente Glättung der ins Netz einzuspeisenden Leistung zu erreichen. Aus der Statistik der Fluktuationen wurde eine Kapazität berechnet, die als Richtwert in die Simulationen einging und dann mit anderen Kapazitäten verglichen wurde. Neben einem idealen MPP-Tracking für verschiedene Arten von Solarzellen und Beleuchtungsprofilen konnte die Simulation auch die Kopplung aus Solarzelle und elektrochemischem Doppelschichtkondensator mit zwei verschiedenen Betriebsstrategien nachbilden. Zum einen wurde ein fester Lastwiderstand genutzt, zum anderen eine Zielspannung für den Kurzzeitspeicher und somit auch die Solarzelle vorgegeben und der Lastwiderstand variabel so angepasst, dass die Zielspannung gehalten wird. Beide Betriebsmethoden haben einen Energieverlust gegenüber der MPP-getrackten Solarzelle zu verzeichnen, führen aber zu einer Glättung der Leistung des gekoppelten Systems. Die Simulation konnte für Siliziumsolarzellen mit einem Demonstratorversuch im Labor und für organische Solarzellen unter realen Bedingungen validiert werden.
Insgesamt ergibt sich eine vielversprechende Glättung der Leistungsfluktuationen von Solarzellen durch den Einsatz von elektrochemischen Doppelschichtkondensatoren.
The interaction of synaptic proteins orchestrate the function of one of the most complex organs, the brain. The multitude of molecular elements influencing neurological correlations makes imaging processes complicated since conventional fluorescence microscopy methods are unable to resolve structures beyond the diffraction-limit.
The implementation of super-resolution fluorescence microscopy into the field of neuroscience allows the visualisation of the fine details of neural connectivity. The key element of my thesis is the super-resolution technique dSTORM (direct Stochastic Optical Reconstruction Microscopy) and its optimisation as a multi-colour approach. Capturing more than one target, I aim to unravel the distribution of synaptic proteins with nanometer precision and set them into a structural and quantitative context with one another. Therefore dSTORM specific protocols are optimized to serve the peculiarities of particular neural samples.
In one project the brain derived neurotrophic factor (BDNF) is investigated in primary, hippocampal neurons. With a precision beyond 15 nm, preand post-synaptic sites can be identified by staining the active zone proteins bassoon and homer. As a result, hallmarks of mature synapses can be exhibited. The single molecule sensitivity of dSTORM enables the measurement of endogenous BDNF and locates BDNF granules aligned with glutamatergic pre-synapses. This data proofs that hippocampal neurons are capable of enriching BDNF within the mature glutamatergic pre-synapse, possibly influencing synaptic plasticity.
The distribution of the metabotropic glutamate receptor mGlu4 is investigated in physiological brain slices enabling the analysis of the receptor in its natural environment. With dual-colour dSTORM, the spatial arrangement of the mGlu4 receptor in the pre-synaptic sites of parallel fibres in the molecular layer of the mouse cerebellum is visualized, as well as a four to six-fold increase in the density of the receptor in the active zone compared to the nearby environment. Prior functional measurements show that metabotropic glutamate receptors influence voltage-gated calcium channels and proteins that are involved in synaptic vesicle priming. Corresponding dSTORM data indeed suggests that a subset of the mGlu4 receptor is correlated with the voltage-gated calcium channel Cav2.1 on distances around 60 nm.
These results are based on the improvement of the direct analysis of localisation data. Tools like coordinated based correlation analysis and nearest neighbour analysis of clusters centroids are used complementary to map protein connections of the synapse. Limits and possible improvements of these tools are discussed to foster the quantitative analysis of single molecule localisation microscopy data.
Performing super-resolution microscopy on complex samples like brain slices benefits from a maximised field of view in combination with the visualisation of more than two targets to set the protein of interest in a cellular context. This challenge served as a motivation to establish a workflow for correlated structured illumination microscopy (SIM) and dSTORM. The development of the visualisation software coSIdSTORM promotes the combination of these powerful super-resolution techniques even on separated setups. As an example, synapses in the cerebellum that are affiliated to the parallel fibres and the dendrites of the Purkinje cells are identified by SIM and the protein bassoon of those pre-synapses is visualised threedimensionally with nanoscopic precision by dSTORM.
In this work I placed emphasis on the improvement of multi-colour super-resolution imaging and its analysing tools to enable the investigation of synaptic proteins. The unravelling of the structural arrangement of investigated proteins supports the building of a synapse model and therefore helps to understand the relation between structure and function in neural transmission processes.
The goal of this work is to improve the understanding of adsorption-induced deformation in nanoporous (and in particular microporous) materials in order to explore its potential for material characterization and provide guidelines for related technical applications such as adsorption-driven actuation. For this purpose this work combines in-situ dilatometry measurements with in-depth modeling of the obtained adsorption-induced strains. A major advantage with respect to previous studies is the combination of the dilatometric setup and a commercial sorption instrument resulting in high quality adsorption and strain isotherms. The considered model materials are (activated and thermally annealed) carbon xerogels, a sintered silica aerogel, a sintered hierarchical structured porous silica and binderless zeolites of type LTA and FAU; this selection covers micro-, meso- and macroporous as well as ordered and disordered model materials.
All sample materials were characterized by scanning electron microscopy, gas adsorption and sound velocity measurements. In-situ dilatometry measurements on mesoporous model materials were performed for the adsorption of N2 at 77 K, while microporous model materials were also investigated for CO2 adsorption at 273 K, Ar adsorption at 77 K and H2O adsorption at 298 K. Within this work the available in-situ dilatometry setup was revised to improve resolution and reproducibility of measurements of small strains at low relative pressures, which are of particular relevance for microporous materials.
The obtained experimental adsorption and strain isotherms of the hierarchical structured porous silica and a micro-macroporous carbon xerogel were quantitatively analyzed based on the adsorption stress model; this approach, originally proposed by Ravikovitch and Neimark, was extended for anisotropic pore geometries within this work. While the adsorption in silica mesopores could be well described by the classical and analytical theory of Derjaguin, Broekhoff and de Boer, the adsorption in carbon micropores required for comprehensive nonlocal density functional theory calculations. To connect adsorption-induced stresses and strains, furthermore mechanical models for the respective model materials were derived. The resulting theoretical framework of adsorption, adsorption stress and mechanical model was applied to the experimental data yielding structural and mechanical information about the model materials investigated, i.e., pore size or pore size distribution, respectively, and mechanical moduli of the porous matrix and the nonporous solid skeleton. The derived structural and mechanical properties of the model materials were found to be consistent with independent measurements and/or literature values. Noteworthy, the proposed extension of the adsorption stress model proved to be crucial for the correct description of the experimental data.
Furthermore, it could be shown that the adsorption-induced deformation of disordered mesoporous aero-/xerogel structures follows qualitatively the same mechanisms obtained for the ordered hierarchical structured porous silica. However, respective quantitative modeling proved to be challenging due to the ill-shaped pore geometry of aero-/xerogels; good agreement between model and experiment could only be achieved for the filled pore regime of the adsorption isotherm and the relative pressure range of monolayer formation. In the intermediate regime of multilayer formation a more complex model than the one proposed here is required to correctly describe stress related to the curved adsorbate-adsorptive interface. Notably, for micro-mesoporous carbon xerogels it could be shown that micro- and mesopore related strain mechanisms superimpose one another.
The strain isotherms of the zeolites were only qualitatively evaluated. The result for the FAU type zeolite is in good agreement with other experiments reported in literature and the theoretical understanding derived from the adsorption stress model. On the contrary, the strain isotherm of the LTA type zeolite is rather exceptional as it shows monotonic expansion over the whole relative pressure range. Qualitatively this type of strain isotherm can also be explained by the adsorption stress model, but a respective quantitative analysis is beyond the scope of this work.
In summary, the analysis of the model materials' adsorption-induced strains proved to be a suitable tool to obtain information on their structural and mechanical properties including the stiffness of the nonporous solid skeleton. Investigations on the carbon xerogels modified by activation and thermal annealing revealed that adsorption-induced deformation is particularly suited to analyze even small changes of carbon micropore structures.
Our universe may have started by Qubit decoherence:
In quantum computers, qubits have all their states undefined during calculation and become defined as output (“decoherence”). We study the transition from an uncontrolled, chaotic quantum vacuum (“before”) to a clearly interacting “real world”. In such a cosmology, the Big Bang singularity is replaced by a condensation event of interacting strings. This triggers a crystallization process. This avoids inflation, not fitting current observations: increasing long-range interactions limit growth and crystal symmetries ensure the same laws of nature and basic symmetries over the whole crystal. Tiny mis-arrangements provide nuclei of superclusters and galaxies and crystal structure allows arrangement of dark (halo regions) and normal matter (galaxy nuclei) for galaxy formation. Crystals come and go: an evolutionary cosmology is explored: entropic forces from the quantum soup “outside” of the crystal try to dissolve it. This corresponds to dark energy and leads to a “big rip” in 70 Gigayears. Selection for best growth and condensation events over generations of crystals favors multiple self-organizing processes within the crystal including life or even conscious observers in our universe. Philosophically this theory shows harmony with nature and replaces absurd perspectives of current cosmology.
Independent of cosmology, we suggest that a “real world” (so our everyday macroscopic world) happens only inside a crystal. “Outside” there is wild quantum foam and superposition of all possibilities. In our crystallized world the vacuum no longer boils but is cooled down by the crystallization event, space-time exists and general relativity holds. Vacuum energy becomes 10**20 smaller, exactly as observed in our everyday world. We live in a “solid” state, within a crystal, the n quanta which build our world have all their different m states nicely separated. There are only nm states available for this local “multiverse”. The arrow of entropy for each edge of the crystal forms one fate, one world-line or clear development of our world, while layers of the crystal are different system states. Mathematical leads from loop quantum gravity (LQG) point to required interactions and potentials. Interaction potentials for strings or loop quanta of any dimension allow a solid, decoherent state of quanta challenging to calculate. However, if we introduce here the heuristic that any type of physical interaction of strings corresponds just to a type of calculation, there is already since 1898 the Hurwitz theorem showing that then only 1D, 2D, 4D and 8D (octonions) allow complex or hypercomplex number calculations. No other hypercomplex numbers and hence dimensions or symmetries are possible to allow calculations without yielding divisions by zero. However, the richest solution allowed by the Hurwitz theorem, octonions, is actually the observed symmetry of our universe, E8. Standard physics such as condensation, crystallization and magnetization but also solid-state physics and quantum computing allow us to show an initial mathematical treatment of our new theory by LQG to describe the cosmological state transformations by equations, and, most importantly, point out routes to parametrization of free parameters looking at testable phenomena, experiments and formulas that describe processes of crystallization, protein folding, magnetization, solid-state physics and quantum computing. This is presented here for LQG, for string theory it would be more elegant but was too demanding to be shown here.
Note: While my previous Opus server preprint “A new cosmology of a crystallization process (decoherence) from the surrounding quantum soup provides heuristics to unify general relativity and quantum physics by solid state physics” (https://doi.org/10.25972/OPUS-23076) deals with the same topics and basic formulas, this new version is improved: clearer in title, better introduction, more stringent in its mathematics and improved discussion of the implications including quantum computing, hints for parametrization and connections to LQG and other current cosmological efforts.
This 5th of June 2021 version is again an OPUS preprint, but this will next be edited for Archives https://arxiv.org.
In this view point we do not change cosmology after the hot fireball starts (hence agrees well with observation), but the changed start suggested and resulting later implications lead to an even better fit with current observations (voids, supercluster and galaxy formation; matter and no antimatter) than the standard model with big bang and inflation: In an eternal ocean of qubits, a cluster of qubits crystallizes to defined bits. The universe does not jump into existence (“big bang”) but rather you have an eternal ocean of qubits in free super-position of all their quantum states (of any dimension, force field and particle type) as permanent basis. The undefined, boiling vacuum is the real “outside”, once you leave our everyday universe. A set of n Qubits in the ocean are “liquid”, in very undefined state, they have all their m possibilities for quantum states in free superposition. However, under certain conditions the qubits interact, become defined, and freeze out, crystals form and give rise to a defined, real world with all possible time series and world lines. GR holds only within the crystal. In our universe all n**m quantum possibilities are nicely separated and crystallized out to defined bit states: A toy example with 6 qubits each having 2 states illustrates, this is completely sufficient to encode space using 3 bits for x,y and z, 1 bit for particle type and 2 bits for its state. Just by crystallization, space, particles and their properties emerge from the ocean of qubits, and following the arrow of entropy, time emerges, following an arrow of time and expansion from one corner of the toy universe to everywhere else. This perspective provides time as emergent feature considering entropy: crystallization of each world line leads to defined world lines over their whole existence, while entropy ensures direction of time and higher representation of high entropy states considering the whole crystal and all slices of world lines. The crystal perspective is also economic compared to the Everett-type multiverse, each qubit has its m quantum states and n qubits interacting forming a crystal and hence turning into defined bit states has only n**m states and not more states. There is no Everett-type world splitting with every decision but rather individual world trajectories reside in individual world layers of the crystal. Finally, bit-separated crystals come and go in the qubit ocean, selecting for the ability to lay seeds for new crystals. This self-organizing reproduction selects over generations also for life-friendliness. Mathematical treatment introduces quantum action theory as a framework for a general lattice field theory extending quantum chromo dynamics where scalar fields for color interaction and gravity have to be derived from the permeating qubit-interaction field. Vacuum energy should get appropriately low by the binding properties of the qubit crystal. Connections to loop quantum gravity, string theory and emergent gravity are discussed. Standard physics (quantum computing; crystallization, solid state physics) allow validation tests of this perspective and will extend current results.
Protein folding achieves a clear solution structure in a huge parameter space (the so-called protein folding problem). Proteins fold in water, and get by this a highly ordered structure. Finally, inside a protein crystal for structure resolution, you have everywhere the same symmetries as there is everywhere the same unit cell. We apply this to qubit interactions to do fundamental physics:
in a modified cosmology, we replace the big bang by a condensation event in an eternal all-encompassing ocean of free qubits. Interactions of qubits in the qubit ocean are quite rare but provide a nucleus or seed for a new universe (domain) as the qubits become decoherent and freeze-out into defined bit ensembles. Second, we replace inflation by a crystallization event triggered by the nucleus of interacting qubits to which rapidly more and more qubits attach (like in everyday crystal growth). The crystal unit cell guarantees same symmetries everywhere inside the crystal. The textbook inflation scenario to explain the same laws of nature in our domain is replaced by the unit cell of the crystal formed.
Interacting qubits solidify, quantum entropy decreases (but increases in the ocean around). In a modified inflation scenario, the interacting qubits form a rapidly growing domain where the n**m states become separated ensemble states, rising long-range forces stop ultimately further growth. Then standard cosmology with the hot fireball model takes over. Our theory agrees well with lack of inflation traces in cosmic background measurements. We explain by cosmological crystallization instead of inflation: early creation of large-scale structure of voids and filaments, supercluster formation, galaxy formation, and the dominance of matter: the unit cell of our crystal universe has a matter handedness avoiding anti-matter.
We prove initiation of qubit interactions can only be 1,2,4 or 8-dimensional (agrees with E8 symmetry of our universe). Repulsive forces at ultrashort distances result from quantization, long-range forces limit crystal growth. Crystals come and go in the qubit ocean. This selects for the ability to lay seeds for new crystals, for self-organization and life-friendliness.
The phase space of the crystal agrees with the standard model of the basic four forces for n quanta. It includes all possible ensemble combinations of their quantum states m, a total of n**m states. Neighbor states reach according to transition possibilities (S-matrix) with emergent time from entropic ensemble gradients. However, in our four dimensions there is only one bit overlap to neighbor states left (almost solid, only below Planck quantum there is liquidity left). The E8 symmetry of heterotic string theory has six curled-up, small dimensions which help to keep the qubit crystal together and will never expand.
Mathematics focusses on the Hurwitz proof applied to qubit interaction, a toy model of qubit interaction and repulsive forces of qubits. Vacuum energy gets appropriate low inside the crystal. We give first energy estimates for free qubits vs bound qubits, misplacements in the qubit crystal and entropy increase during qubit decoherence / crystal formation. Scalar fields for color interaction/confinement and gravity are derived from the qubit-interaction field.
Die vorliegende Arbeit untersucht die Struktur und die Veränderung des akademischen Selbstkonzepts angehender Physiklehrkräfte. Als selbstbezogene Kognition wird es als eine Grundlage der professionellen Identität von Lehrkräften verstanden. Selbstkonzepte bilden sich aus der Kategorisierung selbstrelevanter Informationen, die eine Person in verschiedenen Kontexten sammelt, bewertet und interpretiert. Für angehende Lehrkräfte wird der professionelle Kontext durch die Struktur und die Inhalte des Lehramtsstudiums gebildet. Daraus folgt die erste zentrale Hypothese der Arbeit: Im akademischen Selbstkonzept angehender Physiklehrkräfte lassen sich drei Facetten empirisch trennen, die den inhaltlichen Domänen des Lehramtsstudiums entsprechen. Demnach strukturieren Studierende ihre Fähigkeitszuschreibungen in Bezug auf (1) die Fachwissenschaft Physik, (2) die Fachdidaktik Physik sowie (3) die Erziehungswissenschaften.
Konkrete Erfahrungen bilden als Quelle selbstrelevanter Informationen die Basis für den Aufbau bzw. die Veränderung von domänenspezifischen Selbstkonzeptfacetten. Sie stabilisieren das Selbstkonzept, falls sie im Einklang mit dem bisherigen Bild der Person von sich selbst stehen bzw. können eine Veränderung des Selbstkonzepts initiieren, wenn sie sich nicht konsistent in dieses Bild einfügen lassen. Vor diesem Hintergrund folgt die zweite zentrale Hypothese der vorliegenden Arbeit: Während der Praxisphasen des Studiums verändert sich das akademische Selbstkonzept der Studierenden.
Die Hypothesen werden mit Ansätzen der latenten Modellierung untersucht. Mittels konfirmatorischer Faktorenanalyse wird die empirische Trennbarkeit der drei angenommenen Facetten bestätigt. In einer querschnittlichen Betrachtung zeigt sich ein deutlicher Einfluss des Geschlechts der Studierenden auf den Zusammenhang zwischen ihrem fachdidaktischen Selbstkonzept und ihrer bisherigen Praxiserfahrung. Die längsschnittliche Analyse der Veränderung des Selbstkonzepts während einer zentralen fachdidaktischen Lehrveranstaltung mit ausgeprägten Praxisphasen (Lehr-Lern-Labor-Seminar) wird mit einem latenten Wachstumskurvenmodell untersucht. Das auf die Fachdidaktik Physik bezogene Selbstkonzept steigt während des Seminars leicht an, wenn die Studierenden zum Seminarbeginn bereits über Praxiserfahrung verfügten. Fehlt diese, so ist ein leichter Rückgang in der Ausprägung des Selbstkonzepts feststellbar, der für weibliche Studierende stärker ausfällt als für ihre männlichen Kommilitonen.
Mit den Befunden zu Struktur und Veränderung des akademischen Selbstkonzepts angehender Physiklehrkräfte trägt die vorliegende Arbeit dazu bei, die überwiegend qualitativen Analysen von Identitätsprozessen bei Studierenden durch den Einsatz eines theoretisch fundierten und klar umrissenen Konstrukts um eine quantitative Perspektive zu ergänzen.
This work introduced the reader to all relevant fields to tap into an ultrasound-based state of charge estimation and provides a blueprint for the procedure to achieve and test the fundamentals of such an approach. It spanned from an in-depth electrochemical characterization of the studied battery cells over establishing the measurement technique, digital processing of ultrasonic transmission signals, and characterization of the SoC dependent property changes of those signals to a proof of concept of an ultrasound-based state of charge estimation.
The State of the art & theoretical background chapter focused on the battery section on the mechanical property changes of lithium-ion batteries during operation. The components and the processes involved to manufacture a battery cell were described to establish the fundamentals for later interrogation. A comprehensive summary of methods for state estimation was given and an emphasis was laid on mechanical methods, including a critical review of the most recent research on ultrasound-based state estimation. Afterward, the fundamentals of ultrasonic non-destructive evaluation were introduced, starting with the sound propagation modes in isotropic boundary-free media, followed by the introduction of boundaries and non-isotropic structure to finally approach the class of fluid-saturated porous media, which batteries can be counted to. As the processing of the ultrasonic signals transmitted through lithium-ion battery cells with the aim of feature extraction was one of the main goals of this work, the fundamentals of digital signal processing and methods for the time of flight estimation were reviewed and compared in a separate section.
All available information on the interrogated battery cell and the instrumentation was collected in the Experimental methods & instrumentation chapter, including a detailed step-by-step manual of the process developed in this work to create and attach a sensor stack for ultrasonic interrogation based on low-cost off-the-shelf piezo elements.
The Results & discussion chapter opened with an in-depth electrochemical and post-mortem interrogation to reverse engineer the battery cell design and its internal structure. The combination of inductively coupled plasma-optical emission spectrometry and incremental capacity analysis applied to three-electrode lab cells, constructed from the studied battery cell’s materials, allowed to identify the SoC ranges in which phase transitions and staging occur and thereby directly links changes in the ultrasonic signal properties with the state of the active materials, which makes this work stand out among other studies on ultrasound-based state estimation. Additional dilatometer experiments were able to prove that the measured effect in ultrasonic time of flight cannot originate from the thickness increase of the battery cells alone, as this thickness increase is smaller and in opposite direction to the change in time of flight. Therefore, changes in elastic modulus and density have to be responsible for the observed effect.
The construction of the sensor stack from off-the-shelf piezo elements, its electromagnetic shielding, and attachment to both sides of the battery cells was treated in a subsequent section. Experiments verified the necessity of shielding and its negligible influence on the ultrasonic signals. A hypothesis describing the metal layer in the pouch foil to be the transport medium of an electrical coupling/distortion between sending and receiving sensor was formulated and tested. Impedance spectroscopy was shown to be a useful tool to characterize the resonant behavior of piezo elements and ensure the mechanical coupling of such to the surface of the battery cells. The excitation of the piezo elements by a raised cosine (RCn) waveform with varied center frequency in the range of 50 kHz to 250 kHz was studied in the frequency domain and the influence of the resonant behavior, as identified prior by impedance spectroscopy, on waveform and frequency content was evaluated to be uncritical. Therefore, the forced oscillation produced by this excitation was assumed to be mechanically coupled as ultrasonic waves into the battery cells.
The ultrasonic waves transmitted through the battery cell were recorded by piezo elements on the opposing side. A first inspection of the raw, unprocessed signals identified the transmission of two main wave packages and allowed the identification of two major trends: the time of flight of ultrasonic wave packages decreases with the center frequency of the RCn waveform, and with state of charge. These trends were to be assessed further in the subsequent sections. Therefore, methods for the extraction of features (properties) from the ultrasonic signals were established, compared, and tested in a dedicated section. Several simple and advanced thresholding methods were compared with envelope-based and cross-correlation methods to estimate the time of flight (ToF). It was demonstrated that the envelope-based method yields the most robust estimate for the first and second wave package. This finding is in accordance with the literature stating that an envelope-based method is best suited for dispersive, absorptive media [204], to which lithium-ion batteries are counted. Respective trends were already suggested by the heatmap plots of the raw signals vs. RCn frequency and SoC. To enable such a robust estimate, an FIR filter had to be designed to preprocess the transmitted signals and thereby attenuate frequency components that verifiably lead to a distorted shape of the envelope.
With a robust ToF estimation method selected, the characterization of the signal properties ToF and transmitted energy content (EC) was performed in-depth. A study of cycle-to-cycle variations unveiled that the signal properties are affected by a long rest period and the associated relaxation of the multi-particle system “battery cell” to equilibrium. In detail, during cycling, the signal properties don’t reach the same value at a given SoC in two subsequent cycles if the first of the two cycles follows a long rest period. In accordance with the literature, a break-in period, making up for more than ten cycles post-formation, was observed. During this break-in period, the mechanical properties of the system are said to change until a steady state is reached [25]. Experiments at different C-rate showed that ultrasonic signal properties can sense the non-equilibrium state of a battery cell, characterized by an increasing area between charge and discharge curve of the respective signal property vs. SoC plot. This non-equilibrium state relaxes in the rest period following the discharge after the cut-off voltage is reached. The relaxation in the rest period following the charge is much smaller and shows little C-rate dependency as the state is prepared by constant voltage charging at the end of charge voltage. For a purely statistical SoC estimation approach, as employed in this work, where only instantaneous measurements are taken into account and the historic course of the measurement is not utilized as a source of information, the presence of hysteresis and relaxation leads to a reduced estimation accuracy. Future research should address this issue or even utilize the relaxation to improve the estimation accuracy, by incorporating historic information, e.g., by using the derivative of a signal property as an additional feature. The signal properties were then tested for their correlation with SoC as a function of RCn frequency. This allowed identifying trends in the behavior of the signal properties as a function of RCn frequency and C-rate in a condensed fashion and thereby enabled to predict the frequency range, about 50 kHz to 125 kHz, in which the course of the signal properties is best suited for SoC estimation.
The final section provided a proof of concept of the ultrasound-based SoC estimation, by applying a support vector regression (SVR) to before thoroughly studied ultrasonic signal properties, as well as current and battery cell voltage. The included case study was split into different parts that assessed the ability of an SVR to estimate the SoC in a variety of scenarios. Seven battery cells, prepared with sensor stacks attached to both faces, were used to generate 14 datasets. First, a comparison of self-tests, where a portion of a dataset is used for training and another for testing, and cross-tests, which use the dataset of one cell for training and the dataset of another for testing, was performed. A root mean square error (RMSE) of 3.9% to 4.8% SoC and 3.6% to 10.0% SoC was achieved, respectively. In general, it was observed that the SVR is prone to overestimation at low SoCs and underestimation at high SoCs, which was attributed to the pronounced hysteresis and relaxation of the ultrasonic signal properties in this SoC ranges. The fact that higher accuracy is achieved, if the exact cell is known to the model, indicates that a variation between cells exists. This variation between cells can originate from differences in mechanical properties as a result of production variations or from differences in manual sensor placement, mechanical coupling, or resonant behavior of the ultrasonic sensors. To mitigate the effect of the cell-to-cell variations, a test was performed, where the datasets of six out of the seven cells were combined as training data, and the dataset of the seventh cell was used for testing. This reduced the spread of the RMSE from (3.6 - 10.0)% SoC to (5.9 – 8.5)% SoC, respectively, once again stating that a databased approach for state estimation becomes more reliable with a large data basis. Utilizing self-tests on seven datasets, the effect of additional features on the state estimation result was tested. The involvement of an additional feature did not necessarily improve the estimation accuracy, but it was shown that a combination of ultrasonic and electrical features is superior to the training with these features alone. To test the ability of the model to estimate the SoC in unknown cycling conditions, a test was performed where the C-rate of the test dataset was not included in the training data. The result suggests that for practical applications it might be sufficient to perform training with the boundary of the use cases in a controlled laboratory environment to handle the estimation in a broad spectrum of use cases.
In comparison with literature, this study stands out by utilizing and modifying off-the-shelf piezo elements to equip state-of-the-art lithium-ion battery cells with ultrasonic sensors, employing a range of center frequencies for the waveform, transmitted through the battery cell, instead of a fixed frequency and by allowing the SVR to choose the frequency that yields the best result. The characterization of the ultrasonic signal properties as a function of RCn frequency and SoC and the assignment of characteristic changes in the signal properties to electrochemical processes, such as phase transitions and staging, makes this work unique. By studying a range of use cases, it was demonstrated that an improved SoC estimation accuracy can be achieved with the aid of ultrasonic measurements – thanks to the correlation of the mechanical properties of the battery cells with the SoC.
X-ray dark-field imaging allows to resolve the conflict between the demand for centimeter scaled fields of view and the spatial resolution required for the characterization of fibrous materials structured on the micrometer scale. It draws on the ability of X-ray Talbot interferometers to provide full field images of a sample's ultra small angle scattering properties, bridging a gap of multiple orders of magnitude between the imaging resolution and the contrasted structure scale. The correspondence between shape anisotropy and oriented scattering thereby allows to infer orientations within a sample's microstructure below the imaging resolution. First demonstrations have shown the general feasibility of doing so in a tomographic fashion, based on various heuristic signal models and reconstruction approaches. Here, both a verified model of the signal anisotropy and a reconstruction technique practicable for general imaging geometries and large tensor valued volumes is developed based on in-depth reviews of dark-field imaging and tomographic reconstruction techniques.
To this end, a wide interdisciplinary field of imaging and reconstruction methodologies is revisited. To begin with, a novel introduction to the mathematical description of perspective projections provides essential insights into the relations between the tangible real space properties of cone beam imaging geometries and their technically relevant description in terms of homogeneous coordinates and projection matrices. Based on these fundamentals, a novel auto-calibration approach is developed, facilitating the practical determination of perspective imaging geometries with minimal experimental constraints. A corresponding generalized formulation of the widely employed Feldkamp algorithm is given, allowing fast and flexible volume reconstructions from arbitrary tomographic imaging geometries. Iterative reconstruction techniques are likewise introduced for general projection geometries, with a particular focus on the efficient evaluation of the forward problem associated with tomographic imaging. A highly performant 3D generalization of Joseph's classic linearly interpolating ray casting algorithm is developed to this end and compared to typical alternatives. With regard to the anisotropic imaging modality required for tensor tomography, X-ray dark-field contrast is extensively reviewed. Previous literature is brought into a joint context and nomenclature and supplemented by original work completing a consistent picture of the theory of dark-field origination. Key results are explicitly validated by experimental data with a special focus on tomography as well as the properties of anisotropic fibrous scatterers. In order to address the pronounced susceptibility of interferometric images to subtle mechanical imprecisions, an efficient optimization based evaluation strategy for the raw data provided by Talbot interferometers is developed. Finally, the fitness of linear tensor models with respect to the derived anisotropy properties of dark-field contrast is evaluated, and an iterative scheme for the reconstruction of tensor valued volumes from projection images is proposed. The derived methods are efficiently implemented and applied to fiber reinforced plastic samples, imaged at the ID19 imaging beamline of the European Synchrotron Radiation Facility. The results represent unprecedented demonstrations of X-ray dark-field tensor tomography at a field of view of 3-4cm, revealing local fiber orientations of both complex shaped and low-contrast samples at a spatial resolution of 0.1mm in 3D. The results are confirmed by an independent micro CT based fiber analysis.
Das Ziel der vorliegenden Arbeit war die Entwicklung neuer, robuster Methoden der Spin-Lock-basierten MRT. Im Fokus stand hierbei vorerst die T1ρ-Quantifizierung des Myokards im Kleintiermodell. Neben der T1ρ-Bildgebung bietet Spin-Locking jedoch zusätzlich die Möglichkeit der Detektion ultra-schwacher, magnetischer Feldoszillationen. Die Projekte und Ergebnisse, die im Rahmen dieses Promotionsvorhabens umgesetzt und erzielt wurden, decken daher ein breites Spektrum der Spin-lock basierten Bildgebung ab und können grob in drei Bereiche unterteilt werden. Im ersten Schritt wurde die grundlegende Pulssequenz des Spin-Lock-Experimentes durch die Einführung des balancierten Spin-Locks optimiert. Der zweite Schritt war die Entwicklung einer kardialen MRT-Sequenz für die robuste Quantifizierung der myokardialen T1ρ-Relaxationszeit an einem präklinischen Hochfeld-MRT. Im letzten Schritt wurden Konzepte der robusten T1ρ-Bildgebung auf die Methodik der Felddetektion mittels Spin-Locking übertragen. Hierbei wurden erste, erfolgreiche Messungen magnetischer Oszillationen im nT-Bereich, welche lokal im untersuchten Gewebe auftreten, an einem klinischen MRT-System im menschlichen Gehirn realisiert.