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.

The development of controlled biodegradable materials is of fundamental importance in immunodrug delivery to spatiotemporally controlled immune stimulation but avoid systemic inflammatory side effects. Based on this, polycarbonate nanogels are developed as degradable micellar carriers for transient immunoactivation of lymph nodes. An imidazoquinoline‐type TLR7/8 agonist is covalently conjugated via reactive ester chemistry to these nanocarriers. The nanogels not only provide access to complete disintegration by the hydrolysable polymer backbone, but also demonstrate a gradual disintegration within several days at physiological conditions (PBS, pH 6.4–7.4, 37 °C). These intrinsic properties limit the lifetime of the carriers but their payload can still be successfully leveraged for immunological studies in vitro on primary immune cells as well as in vivo. For the latter, a spatiotemporal control of immune cell activation in the draining lymph node is found after subcutaneous injection. Overall, these features render polycarbonate nanogels a promising delivery system for transient activation of the immune system in lymph nodes and may consequently become very attractive for further development toward vaccination or cancer immunotherapy. Due to the intrinsic biodegradability combined with the high chemical control during the manufacturing process, these polycarbonate‐based nanogels may also be of great importance for clinical translation.

Aluminium-copper alloys of the 2xxx type receive their excellent mechanical properties by the formation of copper-rich precipitates during hardening. Size, distribution and crystal structure of the formed precipitates determine the final strength of those alloys. Adding traces of certain elements, which bind to vacancies, significantly influences the decomposition behaviour, i.e. the diffusion of the copper atoms. For high-purity ternary alloys (Al-1.7 at.% Cu-X), we investigate the interaction of copper and trace element atoms (X=In, Sn, and Pb) with quenched-in vacancies by Positron Annihilation Lifetime Spectroscopy (PALS). By employing Vickers microhardness, Differential Scanning Calorimetry (DSC) and Small Angle X-Ray Scattering (SAXS) we obtain a comprehensive picture of the decomposition process: opposite to predicted binding energies to vacancies by ab-initio calculations we find during ageing at room and elevated temperature a more retarded clustering of copper in the presence of In rather than for Sn additions, while Pb, having the highest predicted binding to vacancies, shows nearly no retarding effect compared to pure Al-Cu. If the latter would be due to a limited solubility of lead, it had to be below 2 ppm. Transmission Electron Microscopy (TEM) as imaging method complements our findings. Annealing the quenched Al-1.7 at.% Cu-X-alloys containing 100 ppm In or Sn at 150∘C leads to finely distributed θ′-precipitates on the nanoscale, since due to the trace additions the formation temperature of θ′ is lowered by more than 100∘C. According to TEM small agglomerates of trace elements (In, Sn) may support the early nucleation for the θ′-precipitates.

The US National Research Council (NRC) report "Toxicity Testing in the 21st Century: A Vision and a strategy (Tox21)", published in 2007, calls for a complete paradigm shift in tox-icity testing. A central aspect of the proposed strategy includes the transition from apical end-points in in vivo studies to more mechanistically based in vitro tests. To support and facilitate the transition and paradigm shift in toxicity testing, the Adverse Outcome Pathway (AOP) concept is widely recognized as a pragmatic tool. As case studies, the AOP concept was ap-plied in this work to develop AOPs for proximal tubule injuries initiated by Receptor-mediated endocytosis and lysosomal overload and Inhibition of mtDNA polymerase-. These AOPs were used as a mechanistic basis for the development of in vitro assays for each key event (KE). To experimentally support the developed in vitro assays, proximal tubule cells from rat (NRK-52E) and human (RPTEC/TERT1) were treated with model compounds. To measure the dis-turbance of lysosomal function in the AOP – Receptor-mediated endocytosis and lysosomal overload, polymyxin antibiotics (polymyxin B, colistin, polymyxin B nonapeptide) were used as model compounds. Altered expression of lysosomal associated membrane protein 1/2 (LAMP-1/2) (KE1) and cathepsin D release from lysosomes (KE2) were determined by im-munofluorescence, while cytotoxicity (KE3) was measured using the CellTiter-Glo® cell via-bility assay. Importantly, significant differences in polymyxin uptake and susceptibility be-tween cell lines were observed, underlining the importance of in vitro biokinetics to determine an appropriate in vitro point of departure (PoD) for risk assessment. Compared to the in vivo situation, distinct expression of relevant transporters such as megalin and cubilin on mRNA and protein level in the used cell lines (RPTEC/TERT1 and NRK-52E) could not be con-firmed, making integration of quantitative in vitro to in vivo extrapolations (QIVIVE) neces-sary. Integration of QIVIVE by project partners of the University of Utrecht showed an im-provement in the modelled biokinetic data for polymyxin B. To assess the first key event, (KE1) Depletion of mitochondrial DNA, in the AOP – Inhibition of mtDNA polymerase-, a RT-qPCR method was used to determine the mtDNA copy number in cells treated with mod-el compounds (adefovir, cidofovir, tenofovir, adefovir dipivoxil, tenofovir disoproxil fumarate). Mitochondrial toxicity (KE2) was measured by project partners using the high-content imaging technique and MitoTracker® whereas cytotoxicity (KE3) was determined by CellTiter-Glo® cell viability assay. In contrast to the mechanistic hypothesis underlying the AOP – Inhibition of mtDNA polymerase-, treatment with model compounds for 24 h resulted in an increase rather than a decrease in mtDNA copy number (KE1). Only minor effects on mitochondrial toxicity (KE2) and cytotoxicity (KE3) were observed. Treatment of RPT-EC/TERT1 cells for 14 days showed only a slight decrease in mtDNA copy number after treatment with adefovir dipivoxil and tenofovir disoproxil fumarate, underscoring some of the limitations of short-term in vitro systems. To obtain a first estimation for risk assessment based on in vitro data, potential points of departure (PoD) for each KE were calculated from the obtained in vitro data. The most common PoDs were calculated such as the effect concentra-tion at which 10 % or 20_% effect was measured (EC10, EC20), the highest no observed effect concentration (NOEC), the lowest observed effect concentration (LOEC), the benchmark 10 % (lower / upper) concentrations (BMC10, BMCL10, BMCU10) and a modelled non-toxic con-centration (NtC). These PoDs were then compared with serum and tissue concentrations de-termined from in vivo studies after treatment with therapeutic / supratherapeutic doses of the respective drugs in order to obtain a first estimate of risk based on in vitro data. In addition, AOPs were used to test whether the quantitative key event relationships between key events allow prediction of downstream effects and effects on the adverse outcome (AO) based on measurements of an early key event. Predictions of cytotoxicity from the mathematical rela-tionships showed good concordance with measured cytotoxicity after treatment with colistin and polymyxin b nonapeptide. The work also revealed uncertainties and limitations of the ap-plied strategy, which have a significant impact on the prediction and on a risk assessment based on in vitro results.

The self-assembly of umbrella-shaped mesogens is explored with subphthalocyanine cores and oligo(thienyl) arms with different lengths in the light of their application as light-harvesting and photoconducting materials. While the shortest arm derivatives self-assemble in a conventional columnar phase with a single mesogen as a repeating unit, the more extended derivatives generate dimers that pile up into liquid crystalline columns. In contrast to the antiparallel arrangement known from single crystals, the present mesogens align as parallel dimers in polar columnar phases as confirmed by X-ray scattering, experimental densities, dielectric spectroscopy, second harmonic generation, alignment, and conductivity studies. UV–vis and fluorescence spectroscopies reveal a broad absorption in the visible range and only weak emission of the Q-band. Thus, these light-collecting molecules forming strongly polar columnar mesophases are attractive for application in the area of photoconductive materials.