Opioid receptors (ORs) are among the most intensively studied members of the G protein-coupled receptor (GPCR) family due to their important role in pain management and their involvement in psychological and neurological disorders. However, currently available opioid drugs exhibit both serious drawbacks, such as addiction, and life-threatening side effects, such as respiratory depression. Contrary to the classic monomeric model, indirect evidence suggests that ORs might form dimers, which could be endowed with a distinct pharmacological profile, and, thus, be exploited to develop innovative drugs. However, direct evidence for the spontaneous formation of OR dimers in living cells under physiological condition are missing. The focus of this thesis was the design, synthesis and characterization of new, highly subtype-selective OR fluorescent ligands to be used as tools for state-of-the-art microscopy methods, such as single molecule microscopy (SMM), in heterologous cells and potentially in native tissue, in order to investigate OR organization and mobility on the surface of intact, living cells, at low/physiological expression levels. The μOR is the OR subtype which plays the most critical role in pain modulation, while mediating the effects of the most powerful analgesic drugs. Also, it is the OR subtype which is mostly responsible for the major adverse effects of the currently marketed opioid drugs. We aimed to develop a new μOR-selective fluorescent ligand with a potential irreversible binding mode. Although the approach was in principle successful, i.e. the labelled cells were visible and distinguishable; this initial attempt was not suitable for SMM due to the ligands’ poor selectivity and affinity as well as due to its high background noise. A second generation of the fluorescent ligand was designed; however the synthesis and characterization are part of another doctoral thesis. Lately, δOR has received attention as a promising drug target, due to its distinct pharmacological profile which features low abuse liability and lack of physical dependence. In addition, δOR expression has been associated with cancer regulation in the periphery, thus further highlighting the interest of imaging tools for this receptor. In this thesis, the development and characterization of two new δOR-selective fluorescent probes with excellent optical properties, based on the well-studied ligand naltrindole (NTI) is presented. Their application in SMM studies is currently underway at the group of Prof. Dr. Davide Calebiro at the University of Birmingham. The κOR is a subtype which has also emerged as a drug target due to its low abuse potential. Despite a growing interest in this receptor, κOR-selective fluorescent probes have been particularly scarce in literature. Herein, the design, synthesis and characterization of the first reported set of fluorescent κOR-selective probes with antagonistic properties, based on the established ligand 5’-guanidinonaltrindole (5’-GNTI) is presented. Two of these were employed for SMM experiments to investigate κOR homodimerization, localization and trafficking. Our findings do not support homodimerization of the κOR-bound probe complexes, while showing that the majority of them follow a normal Brownian diffusion on the cell surface.

Most antioxidants reported so far only achieved limited success in AD clinical trials. Growing evidences suggest that merely targeting oxidative stress will not be sufficient to fight AD. While multi-target directed ligands could synergistically modulate different steps in the neurodegenerative process, offering a promising potential for treatment of this complex disease. Fifteen target compounds have been designed by merging melatonin and ferulic acid into the cap group of a tertiary amide HDAC6 inhibitor. Compound 10b was screened as the best hybrid molecule exhibit potent HDAC6 inhibition and potent antioxidant capacity. Compound 10b also alleviated LPS-induced microglia inflammation and led to a switch from neurotoxic M1 to the neuroprotective M2 microglial phenotype. Moreover, compound 10b show pronounced attenuation of spatial working memory and long-term memory damage in an in vivo AD mouse model. Compound 10b can be a potentially effective drug candidate for treatment of AD and its druggability worth to be further studied. We have designed ten novel neuroprotectants by hybridizing with several common antioxidants, including ferulic acid, melatonin, lipoic acid, and trolox. The trolox hybrid compound exhibited the most potent neuroprotective effects in multiple neuroprotection assays. Besides, we identified the synergistic effects between trolox and vitamin K derivative, and our trolox hybrid compound showed comparable neuroprotection with the mixture of trolox and vitamin K derivative. We have designed and synthesized 24 quinone derivatives based on five kinds of different quinones including ubiquinone, 2,3,5-trimethyl-1,4-benzoquinone, memoquin, thymoquinone, and anthraquinone. Trimethylbenzoquinone and thymoquinone derivatives showed more potent neuroprotection than other quinones in oxytosis assay. Therefore, trimethylbenzoquinone and thymoquinone derivatives can be used as lead compounds for further mechanism study and drug discovery for treatment of neurodegenerative disease. We designed a series of photoswitchable HDAC inhibitors, which could be effective molecular tools due to the high spatial and temporal resolution. In total 23 target compounds were synthesized and photophysicochemically characterized. Azoquinoline-based compounds possess more thermally stable cis-isomers in buffer solution, which were further tested in enzyme-based HDAC inhibition assay. However, none of those tested compounds show significant differences in activities between trans-isomers and corresponding cis-isomers.

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.