Publikationen

Browse

Now showing 1 - 20 of 5494

Optimization methods for optical design
(Universität Ulm, 2026-05-19) Seger, Tobias; Urban, Karsten; Walther, Andrea
Optical systems play a crucial role in various fields, from enhancing vision in everyday life to enabling advanced technologies in telecommunications and imaging. A fundamental aspect of designing optical systems involves solving an optimization problem to meet performance specifications. This dissertation addresses both the local and global optimization of optical systems. For local optimization, we develop techniques for both differential ray tracing and differential ray aiming using algorithmic differentiation. By exploiting sparsity patterns in the computational graph, we derive that the Jacobian of the objectives in optical design with respect to the system parameters can be evaluated in the same runtime complexity as the objectives themselves. Numerical experiments demonstrate the superiority of the method compared to numerical differentiation. For global optimization, we present a proof-of-principle for employing generative models in optical design. Concretely, we train a generative adversarial network to learn the distribution of feasible configurations within the search space of an optical design task. Furthermore, we investigate hybrid optimization schemes as another method for exploring the search space. We introduce a novel pruning strategy to prevent the re-exploration of already discovered local minima. Informed by past optimization trajectories, the strategy successfully prunes unpromising local optimization trials.
CO2 activation by sub-nanometer gas-phase copper, cobalt and yttrium oxide clusters
(Universität Ulm, 2026-05-15) Mikolaj, Pavol; Lang, Sandra Marianne; Beránek, Radim
The work presented in this thesis delivers fundamental insights into the interplay between metal oxide clusters and CO2, H2O and mixtures thereof. Combining experiments and theory, we identified key forces behind CO2 activation and its binding on metal oxide clusters. Infrared multiple-photon dissociation (IR-MPD) spectroscopy revealed the nonactivated binding of CO2 to all cations while CO2 is activated by all anions across the investigated metals. Computational analysis, alongside cross-validation of additional IR-MPD spectra with prior studies provide a strong foundation for a claim that CO3 is preferably bound in a η2-configuration to CuxOy– and CoxOy–, whereas both η2- and η3-bound species may form on YxOy–. CO2 dissociation appears to be unfavorable due to the instability of CO, indicating that potential hydrogenation reactions will most likely proceed via formate or bicarbonate intermediates. Additionally, water dehydrogenation and H2O/CO2 coadsorption by a series of gas-phase copper and copper oxide clusters (Cu2O+, Cu3+, Cu3O+ and Cu3O2+) was studied in an octopole ion trap under multi-collision conditions. This work experimentally validates theoretical predictions of the ability of small copper and copper oxide clusters for water dehydrogenation and emphasizes water’s direct involvement in CO2 hydrogenation.
Synthese und Charakterisierung von neuartigen Dithienopyrrol- und Cyclopentadien-basierten Materialien
(Universität Ulm, 2026-05-12) Bajrami, Jessi Sara; Bäuerle, Peter; Esser, Birgit
Diese Dissertation befasst sich mit der Synthese und Charakterisierung von neuartigen Dithienopyrrol- und Cyclopentadien-basierten Materialien.
Temporal PPARɣ modulation alters Schwann cell responses and regeneration dynamics after peripheral nerve injury
(Universität Ulm, 2026-05-11) Seitz, Antonia; Knöll, Bernd; Meyer zu Reckendorf, Sofia; Wegner, Michael
Peripheral nerve injuries (PNIs) pose a major clinical challenge due to the lack of effective therapeutic strategies that promote functional regeneration, leading to long-term disability, reduced quality of life for affected patients, and a substantial socioeconomic burden. Recent work from our lab using an ex vivo nerve injury model demonstrated that Schwann cell (SC) reprogramming from a myelinating to a repair phenotype after PNI is accompanied by a marked downregulation of lipid metabolism involving the peroxisome proliferator-activated receptor gamma (PPARɣ). Building on these findings, this thesis investigated PPARɣ as a potential therapeutic target in peripheral nerve regeneration in vivo, by treating sciatic nerve-injured mice with the PPARɣ agonist pioglitazone (PIO). Since SCs exhibit distinct metabolic and functional demands during the acute degeneration and the later regeneration phase, these two phases were targeted individually. PIO was administered systemically either i) acutely (daily, days 0-5 post injury) or ii) during the subsequent regenerative phase (every other day, days 5-21 post injury) to assess whether phase-specific PPARɣ activation differentially affects nerve repair outcomes. Based on previous findings, it was hypothesized that early PPARɣ activation disrupts the physiological injury response by maintaining elevated PPARɣ levels, thereby impeding SC reprogramming and regeneration, whereas delayed activation may accelerate remyelination and recovery by promoting the transition back to a myelinating phenotype. To test these hypotheses, acute and late PIO treatment paradigms were systematically evaluated at the molecular, functional, and metabolic levels using histological, behavioral, and in vitro metabolic analyses. Expectedly, acute PIO treatment disrupted the injury response by maintaining elevated PPARɣ levels after nerve damage, thereby suppressing SC reprogramming into the repair phenotype. This inhibition delayed axonal and myelin debris clearance, impaired axonal regrowth, and resulted in thinner myelin sheaths, collectively hindering both molecular and functional recovery of motor and sensory nerves – thus confirming the first hypothesis. In contrast, delayed PIO administration during the regeneration phase significantly enhanced nerve repair, particularly at intermediate stages, by promoting remyelination, increasing myelin thickness, and improving both molecular and functional outcomes. RNA sequencing data revealed that mitochondrial metabolism was among the most robustly upregulated pathways following PIO treatment, leading to further investigation of its metabolic effects in vivo and in vitro. Late PIO administration was associated with elevated mitochondrial content in remyelinating SCs and regenerating axons, suggesting a metabolic shift that supports enhanced repair. Complementary metabolic analyses in cultured repair SCs confirmed that PIO boosts mitochondrial content and respiration, increases glycolytic activity, and enhances lipid metabolism. Similar mitochondrial effects observed in human SCs further underscored its translational potential. Together, these findings demonstrate that PIO promotes metabolic adaptations that improve nerve and target tissue regeneration, highlighting its potential as a targeted metabolic therapy for peripheral nerve injury. Moreover, they emphasize the importance of dynamic metabolic regulation in nerve repair and the critical role of treatment timing, since pharmacological interventions as demonstrated in this thesis with PIO, can be highly beneficial within a defined therapeutic window, but detrimental if applied outside it.
ALS mutations shift the isoelectric point of the KIF5A C-terminal inducing protein aggregation, TDP43 mislocalization and impaired protein synthesis
(Universität Ulm, 2026-05-08) Zanella, Pietro; Böckers, Tobias; Knöll, Bernd; Verpelli, Chiara
In this Thesis we investigated the pathomechanism associated with KIF5A, a gene encoding for a neuronally enriched kinesin casually linked to ALS. While identified ALS mutations cluster in the cargo-biding domain of KIF5A and are predicted to lead to a 39 amino acid long C-terminal aberrant sequence, missense mutations in the N-terminal domain affecting the ability to walk on the microtubule have been previously linked to CMT and SP10. We reprogrammed to human induced pluripotent stem cells (hiPSC) keratinocytes acquired from an ALS patient harbouring a heterozygous mutation (c2993-1 G>A) within the KIF5A gene. By CRISPR-cas9, we obtained the isogenic control for the patient cell line and a second pair of isogenic cells introducing in a commercially available hiPSC line the same heterozygous mutation. The mutation did not affect the differentiation of hiPSCs into moto neurons (MNs) as the cultures at DIV 21 were characterized by an abundant motor neurons population expressing Islet1 and other neurological markers (CHAT, Homer1, NEFH and TUBB3) at similar levels. Using a custom-made antibody targeting the aberrant C-terminal sequence, we confirmed the expression of the pathological KIF5A only in ALS cells. After nine weeks of culture, by comparing the isogenic controls to their respective ALS cell lines, we observed in the latter a downregulation of the WT isoform of KIF5A and the formation of abnormally large KIF5A positive cytosolic structures. Notably, these phenotypes were more intense in the patient derived cell lines, which were also expressing the pathological KIF5A at significantly higher levels than CRISPR cells suggesting, therefore, a possible connection between the insurgence of pathological manifestations and upregulation of KIF5A ALS. While we could detect in both ALS MNs a modest but statistically significant mislocalization of TDP-43, a hallmark common to many other ALS-related mutations, puromycin incorporation and survival were not significantly different between ALS and control cell lines indicating a threshold of resilience allowing neurons to resist to the pathological alterations triggered by KIF5A aggregates. Overexpressing KIF5A constructs based on the cDNA of WT and different pathological KIF5A isoforms in rat primary cortical neurons, we observed the formation of cytotoxic accumulations only in neurons transfected with the ASL construct highlighting a key role of protein aggregation in the ALS pathomechanism. Therefore, we focus on understanding the biochemical proprieties by which the aberrant C-terminal sequence led KIF5A ALS to aggregation. We obtained by site-direct mutagenesis KIF5A ALS variants with progressively lower isoelectric point (pI) on the C-terminal domain. The generation of the KIF5A var1.2.3, characterized by a terminal local pI similar to the WT while retaining most of the aberrant amino acids, proved that aggregation is strictly connected to the local pI shift in the C-terminal domain of KIF5A ALS as, contrary to the pathological isoform, overexpression of KIF5A var1.2.3 did not lead to cytotoxic accumulation neither in human embryonic kidney cells nor in primary cortical neurons. We took advantage of the overexpression of the KIF5A variant 1.2.3 to confirm whether the phenotypes previously observed in MNs were connected to the aggregation of the protein. According to our hypothesis, neurons overexpressing KIF5A ALS showed reduced endogenous KIF5A, TDP-43 mislocalization and protein synthesis impairment while cells transfected with KIF5A var1.2.3 showed similar behaviour to KIF5A WT transfected neurons and controls. Lastly, healthy controls MNs were also transfected with KIF5A constructs. Interestingly, control MNs overexpressing KIF5A ALS not only showed TDP-43 mislocalization but also the sequestration of the transcription factor within the exogenous aggregates. The plethora of diverse, but connected, phenotypes triggered by KIF5A aggregation, both in overexpression and at endogenous level with different intensity, suggests a time-dependent accumulation of the toxic mutant protein that might contribute to determine the timings of neuronal sufferance and degeneration, which includes TDP-43 pathology as observed in the majority of ALS cases.
Some open mathematical problems on fullerenes
(Universität Ulm, 2025-03-10) Bille, Artur; Buchstaber, Victor; Spodarev, Evgeny
Fullerenes are hollow carbon molecules where each atom is connected to exactly three other atoms, arranged in pentagonal and hexagonal rings. Mathematically, they can be combinatorially modeled as planar, 3-regular graphs with facets composed only of pentagons and hexagons. In this work, we outline a few of the many open questions about fullerenes, beginning with the problem of generating fullerenes randomly. We then introduce an infinite family of fullerenes on which the generalized Stone–Wales operation is inapplicable. Furthermore, we present numerical insights into a graph invariant, called the character of a fullerene, derived from its adjacency and degree matrices. As supported by numerical results, this descriptor may lead to a new method for linear enumeration of all fullerenes.
Role of spacers in molecularly linked RuRh dyads: a comparative synthetic and ultrafast spectroscopic investigation
(Universität Ulm, 2025-04-10) Semwal, Mohini; Lämmle, Martin; Brohmer, Elias H. P.; Volk, Steffen; Zedler, Linda; Kupfer, Stephan; Mengele, Alexander K.; Shillito, Georgina E.; Rau, Sven; Dietzek-Ivanšić, Benjamin
© In Copyright http://rightsstatements.org/vocab/InC/1.0/
Phenothiazine polymers as versatile electrode materials for next-generation batteries
(Universität Ulm, 2025-05-19) Esser, Birgit; Morhenn, Isabel H.; Keis, Michael
Conspectus Organic battery electrode materials are key enablers of different postlithium cell chemistries. As a p-type compound with up to two reversible redox processes at relatively high potentials of 3.5 and 4.1 V vs. Li/Li + , phenothiazine is an excellently suited redox-active group. It can easily be functionalized and incorporated into polymeric structures, a prerequisite to obtain insolubility in liquid battery electrolytes. Phenothiazine tends to exhibit π-interactions (π*−π*-interactions) to stabilize its radical cationic form, which can increase the stability of the oxidized form but can also strongly influence its cycling performance as a battery electrode material. In recent years, we investigated a broad range of phenothiazine-based polymers as battery electrode materials, providing insight into the effect of π-interactions on battery performance, leading to design principles for highly functional phenothiazine-based polymers, and enabling the investigation of full cells. We observed that π-interactions are particularly expressed in “mono”-oxidized forms of poly(3-vinyl- N -methylphenothiazine) (PVMPT) and are enabled in the battery electrode due to the solubility of oxidized PVMPT in many carbonate-based liquid electrolytes. PVMPT dissolves during charge and is redeposited during discharge as a stable film on the positive electrode, however, still retaining half of its charge. This diminishes its available specific capacity to half of the theoretical value. We followed three different strategies to mitigate dissolution and inhibit the formation of π-interactions in order to access the full specific capacity for the one-electron process: Adjusting the electrolyte composition (type and ratio of cyclic vs. linear carbonate), encapsulating PVMPT in highly porous conductive carbons or cross-linking the polymer to X-PVMPT. All three strategies are excellently suited to pursue full-cell concepts using PVMPT or X-PVMPT as positive electrode material. The extent of π-interactions could also be modified by structural changes regarding the polymer backbone (polystyrene or polynorbornene) or exchanging the heteroatom sulfur in phenothiazine by oxygen in phenoxazine. By changing the molecular design and attaching electron-donating methoxy groups to the phenothiazine units, its second redox process can be reversibly enabled, even in carbonate-based electrolytes. Studies by us as well as others provided a selection of high-performing phenothiazine polymers. Their applicability was demonstrated as positive electrode in full cells of different configurations, including dual-ion battery cells using an inorganic or organic negative electrode, anion-rocking-chair cells as examples of all-organic batteries, or even an aluminum battery with a performance exceeding that of aluminum-graphite battery cells. In changing the design concept to conjugated phenothiazine polymers, a higher intrinsic semiconductivity can result, enabling the use of a lesser amount of the conductive carbon additive in the composite electrode. It also provides a handle to alter the optical properties of the polymers, for instance by designing donor–acceptor type conjugated polymers with visible-light absorption, where we demonstrated an application in a photobattery. This Account provides an overview of these findings, also in the context of other literature in the field. It highlights phenothiazine polymers as versatile electrode materials for next-generation batteries.
Mutation T9I in envelope confers autophagy resistance to SARS-CoV-2 omicron
(Universität Ulm, 2025-06-20) Klute, Susanne; Nchioua, Rayhane; Cordsmeier, Arne; Vishwakarma, Jyoti; Koepke, Lennart; Alshammary, Hala; Jung, Christoph; Hirschenberger, Maximilian; Hoenigsperger, Helene; Fischer, Jana-Romana; Sivarajan, Rinu; Zech, Fabian; Stenger, Stefan; Serra-Moreno, Ruth; Gonzalez-Reiche, Ana Silvia; Sordillo, Emilia Mia; van Bakel, Harm; Simon, Viviana; Kirchhoff, Frank; Jacob, Timo; Kmiec, Dorota; Pichlmair, Andreas; Ensser, Armin; Sparrer, Konstantin Maria Johannes
Omicron has emerged as the most successful variant of SARS-CoV-2. In addition to mutations in Spike that mediate humoral immune escape, the Omicron-specific Envelope (E) T9I mutation has been associated with increased transmission fitness. However, the underlying mechanism remained unclear. Here, we demonstrate that the E T9I mutation confers resistance to autophagy. Rare Omicron patient isolates encoding the ancestral E T9 remain sensitive to autophagy. Conversely, introducing the E T9I mutation in recombinant 2020 SARS-CoV-2 renders it resistant to autophagy. Our data indicate that the E T9I mutation protects virions against lysosomal degradation. At the molecular level, the T9I mutation increases the localization of E at autophagic vesicles and promotes interaction with autophagy-associated proteins SNX12, STX12, TMEM87B, and ABCG2. Our results show that the E T9I mutation renders incoming virions resistant to autophagy, suggesting that evasion of this antiviral mechanism contributes to the efficient spread of Omicron.
Invasive Fascioloides magna infections impact gut microbiota in a definitive host in Europe
(Universität Ulm, 2024-11-25) Fleischer, Ramona; Velling, Marc; Peters, Wibke; Peterka, Tomas; Franke, Frederik; Vymyslicka, Pavla Junkova; Rehbein, Steffen; Heurich, Marco; Sommer, Simone
nvasive parasites that expand their natural range can be a threat to wildlife biodiversity and may pose a health risk to non-adapted, naive host species. The invasive giant liver fluke, Fascioloides magna, native to North America, has extended its range in Europe and uses mainly red deer (Cervus elaphus) as definitive hosts. The penetration of the intestinal barrier by the young flukes to reach the liver via the abdominal cavity as well as the release of fluke metabolism products and excreta with the bile and/or changes in the microbial community of the biliary system may enable the translocation of intestinal bacteria across the intestinal barrier and, in turn, could be associated with inflammation and changes in the intestinal bacterial community. The gut commensal community plays a key role in host nutrition and interacts with cells of the immune system to maintain host health. For this study, the gut bacterial community of red deer infected with F. magna and of non-infected red deer from one of the largest forest ecosystems in Central Europe, located on the border between the Czech Republic and Germany, was investigated. The individual fluke burden was associated with changes in the gut microbial composition of the gut of infected individuals, whereas the diversity and composition of the gut bacteria were only slightly different between fluke-infected and uninfected deer. Several bacterial taxa at the genus level were unique to individuals carrying either one or many liver flukes. Our results suggest that the microbiota of red deer is stable to perturbation by low numbers of F. magna. However, a larger parasite burden may cause changes in the gut microbial composition in definitive hosts implying that non-invasive fecal microbiome assessments could serve as indicator for wildlife health monitoring.
Enhancing PV feed-in power forecasting through federated learning with differential privacy using LSTM and GRU
(Universität Ulm, 2024-11-23) Riedel, Pascal; Belkilani, Kaouther; Reichert, Manfred; Heilscher, Gerd; Schwerin, Reinhold von
Given the inherent fluctuation of photovoltaic (PV) generation, accurately forecasting solar power output and grid feed-in is crucial for optimizing grid operations. Data-driven methods facilitate efficient supply and demand management in smart grids, but predicting solar power remains challenging due to weather dependence and data privacy restrictions. Traditional deep learning (DL) approaches require access to centralized training data, leading to security and privacy risks. To navigate these challenges, this study utilizes federated learning (FL) to forecast feed-in power for the low-voltage grid. We propose a bottom-up, privacy-preserving prediction method using differential privacy (DP) to enhance data privacy for energy analytics on the customer side. This study aims at proving the viability of an enhanced FL approach by employing three years of meter data from three residential PV systems installed in a southern city of Germany, incorporating irradiance weather data for accurate PV power generation predictions. For the experiments, the DL models long short-term memory (LSTM) and gated recurrent unit (GRU) are federated and integrated with DP. Consequently, federated LSTM and GRU models are compared with centralized and local baseline models using rolling 5-fold cross-validation to evaluate their respective performances. By leveraging advanced FL algorithms such as FedYogi and FedAdam, we propose a method that not only predicts sequential energy data with high accuracy, achieving an of 97.68%, but also adheres to stringent privacy standards, offering a scalable solution for the challenges of smart grids analytics, thus clearly showing that the proposed approach is promising and worth being pursued further.
Advanced deep learning approaches for the detection of clutter in automotive radar point clouds
(Universität Ulm, 2026-05-05) Kopp, Johannes; Dietmayer, Klaus; Waldschmidt, Christian
The output of radar sensors used for the environment perception in highly automated and autonomous driving contains a large number of errors. Instead of accurately representing the positions and velocities of surrounding obstacles, many of the detection points in the generated point clouds are unwanted clutter. This means that they are false positive measurements and do not correspond to actual objects. Which points exactly are defective, however, is often very difficult to discern just from the radar data alone. As a result, the clutter points are easily misinterpreted and pose an enormous challenge to radar-based environment perception methods like object detection, dynamic occupancy grid mapping and tracking. To resolve the above problem, this thesis focuses on the development of artificial neural networks that are able to identify clutter, and that can be employed as part of a preprocessing step for marking or removing the erroneous points. The networks take the data produced in one or more radar measurement cycles as input and classify each included point either as corresponding to a real moving object, as representing some stationary obstacle, or as a clutter detection. Four possible setups for neural networks of fundamentally different types are devised and compared with one another regarding their accuracy and computational cost. In addition to the network architectures, the training settings and the exact forms of the input data are tailored specifically to radar clutter detection. The necessary datasets with ground truth adequate for the task are newly created through a set of custom automatic and semi-automatic label generation methods. Moreover, it is explored how the usually separate and completely independent neural networks for clutter detection and for a semantic segmentation of moving objects can be combined. To this end, different ways for solving the two tasks together using only a single network are designed. The most effective approach does not just cut the overall inference time in half but also manages to set new performance records for both of the assignments. It is therefore deployed to a test vehicle and studied in a large-scale practical evaluation. Lastly, a method for adapting a neural network model trained on data of mid-resolution radar sensors to data of low-resolution radars is developed. It alleviates the performance drop normally caused by such a change with the help a novel rule-based domain translation algorithm for radar point clouds and an extended self-training procedure. The classification accuracy for the target sensor configuration is substantially improved without requiring access to any corresponding labeled data samples.
Hierarchal Heuristic CFD-Based Comparative Approach for Packing Development of Gas-Liquid Mass Transfer Contactors
(Universität Ulm, 2026-05-04) Ashour, Mohamed Adel; Stucke, Dennis; Grützner, Thomas
A hierarchal Heuristic CFD-Based approach is outlined as a comparative screening tool for packing design and development of gas-liquid mass transfer contactors. The presented ideas, methodologies, and metrics are part of ongoing research that is yet to, but planned to, be fully published. The authors retain all the rights to the ideas and contents of this short document. Parts of this text is submitted as a part of a larger contribution to the 13th International Conference on Distillation & Absorption in Salzburg.
Exploring dropout in internet-delivered cognitive behavioral therapy for insomnia: a secondary analysis of prevalence, self-reported reasons, and baseline and intervention data as predictors
(Universität Ulm, 2025-06-28) Simon, Laura; Steinmetz, Lisa; Bendig, Eileen; Küchler, Ann-Marie; Riemann, Dieter; Ebert, David Daniel; Spiegelhalder, Kai; Baumeister, Harald
Introduction Internet-delivered cognitive behavioral therapy for insomnia (iCBT-I) is an effective treatment. However, dropout is a common challenge in digital therapeutics. This study examines dropout in iCBT-I by analyzing reported reasons for dropout and investigating whether baseline variables and intervention usage data can predict dropout. Methods This is an exploratory secondary analysis of a clinical trial investigating a stepped care model for insomnia featuring an eight-module iCBT-I. Reasons for dropout from the iCBT-I were assessed via self-developed items in follow-up surveys, and a dropout survey was sent to all patients who had not completed at least seven modules of the iCBT-I within 12 weeks. The proportion of respondents who agreed with the respective items was calculated. Additionally, bivariate models were specified to explore whether baseline variables and intervention usage data can predict dropout. Results The patients included in this sub-study had a mean age of 49.3 (SD=13.0), with 73.4 % identifying as female. At pre-treatment, their mean insomnia severity was 18.6 (SD=3.9). Among the 233 patients, 103 (44.2 %) were categorized as dropouts. The most frequently reported reasons for dropout were distractions from daily life, the perception of the content not being useful, and difficulties resuming after a break. None of the examined baseline variables significantly predicted dropout, whereas the time needed to complete the first module (OR=1.16; 95 %CI=1.08–1.27) and the number of sleep diary entries in the first week (OR=0.73; 95 %CI=0.65–0.80) significantly predicted dropout. Discussion This study highlights dropout as a relevant challenge in iCBT-I, affecting over 40 % of patients. Self-reported reasons indicate the importance of compatibility with distractions from daily life and perceived effectiveness. The prediction models suggest that dropout risk profiles can be developed based on first-week treatment data. Future research should focus on validating such models to improve effectiveness and user retention.
Research on interphases in multivalent batteries by reflection anisotropy spectroscopy and electrochemical impedance spectroscopy
(Universität Ulm, 2026-05-04) Löw, Mario; May, Matthias; Bansmann, Joachim
The significant decrease in solar and wind power costs over the past decade has made them competitive options in the energy market. However, due to their fluctuating supply, the energy they generate must be stored. Two possible systems that could be utilized for this purpose are rechargeable multivalent batteries and hydrogen. Rechargeable multivalent batteries are expected to replace state-of-the-art lithium-ion batteries in the future due to their higher capacity and the higher availability of their raw materials. Photoelectrochemical water splitting is projected to become a cost-effective method for producing hydrogen. In both systems, the interface between the electrode and the electrolyte is a critical factor which needs further investigation under in-situ and operando conditions. In order to change this, this thesis uses reflection anisotropy spectroscopy (RAS) and electrochemical impedance spectroscopy (EIS) to investigate these interfaces under in-situ and operando conditions. Here, RAS examines the dynamic evolution of optical properties at interfaces, which can help detect adsorption phenomena or surface reconstruction. In contrast, EIS investigates the formation of solid electrolyte interphase (SEI) and cationic transference numbers, an essential electrolyte property for addressing potential dendrite formation. In the context of solar-water splitting, the interface of InP in an acidic solution is examined using RAS to identify potential-dependent surface corrosion and the formation of a passivation layer. Here a low acid concentration of 10mM leads to a reversible process of the reduction of the surface oxide at cathodic potential and its reformation close to open-circuit voltage. In contrast, a high acid concentration (0.5 N) leads to initial surface corrosion. The research also delves into multivalent batteries, particularly aluminium and magnesium batteries. For instance, the interaction of Grignard, one of the first electrolytes for rechargeable magnesium batteries, was examined using RAS and EIS. Here, the liquid pathway through the SEI dominates after prolonged contact with the electrolyte. Further, the addition of stabilized THF (tetrahydrofuran) to the Grignards results in an unordered passivation layer on top of the surface and should, therefore, be avoided. Similarly, the interaction between the promising boron-based Mg[B(HFIP)4]2 and the magnesium anode was studied using RAS, where a partially ordered structure was observed in the pure electrolyte. At the same time, the addition of tris(trimethylsilyl) borate (TMSB) leads to a more isotropic surface. For rechargeable aluminium batteries, the surface corrosion of the aluminium anode when in contact with the commonly used but corrosive electrolyte [EMImCl]:AlCl3 was investigated using RAS and EIS. The prolonged contact with the electrolyte turned the initially dense native oxide layer into an SEI with predominant liquid pathways. Simultaneously, the roughness of the surface increases. During electrochemical cycling, changes in the surface anisotropy were detected, which could be correlated with the stripping and plating of aluminium. Finally, the same electrolyte was utilized to monitor the electrodeposition of aluminium onto highly ordered pyrolytic graphite (HOPG). This investigation shows that the morphology of the deposited aluminium is dependent on the applied cathodic potential, with a rough island-like deposition at less cathodic potentials. In comparison, a smooth layer covering the whole sample is observed at more cathodic potentials. Further, the investigation shows that the initial nucleation contains a step in which ordered nuclei are formed. The investigation in the anodic potential range shows the formation of a SEI as well as the irreversible swelling of the topmost graphite layer due to the intercalation of AlCl4–.
Design and characterization of halide solid electrolytes : from structure to electrochemical functionality
(Universität Ulm, 2026-04-29) Ganesan, Priya; Fichtner, Maximilian; Hölzle, Markus
The demand for safe and more powerful alternatives to conventional Li-ion batteries drives the research towards alternative battery chemistries with higher energy density. In this regard, one promising system is all solid-state batteries (ASSB) containing no combustible liquids and featuring a lithium metal anode to increase the energy density > 350 Wh/kg. However, a key limitation of ASSB is the electrochemical and mechanical stability of the required solid electrolyte. In this regard, halide based solid-state electrolytes (HSE) with Li- M-X (M = In, Y, Zr, Er, Sc; X = Cl, F) based systems are promising owing to their good ionic conductivity and high voltage stability. However, the HSEs are still under study to realize their practical applications and a better understanding of the interplay between the crystal structure and their electrochemical performance is essential. The goal of this thesis is to design new structures and compositions based on Li-M-X compounds in scope of understanding their structural and electrochemical properties. Well known HSEs like Li3InCl6 and Li3ScCl6 exhibit room temperature ionic conductivity > 1 mS cm-1, but the cost per kg exceeds the commercial threshold (> 500 USD/kg), with the abundance of In being less than 10 ppm and Sc being 22 ppm in the earth’s crust. In this regard. Li2ZrCl6 was investigated in the light of improving their properties by substitution study. The cost effectiveness and the abundance of Zr (165 ppm) based electrolyte makes it an interesting candidate as solid electrolyte. The precursors used in the synthesis of this electrolyte are abundant and are well within the price limit (< 20 USD/kg). Hence, Li2ZrCl6 is an interesting class of materials with economic viability. However, their conductivity and the performance are lower than other HSEs based on rare earth metals. Therefore, there is a need to understand their structure, properties, and chemistry to further improve them. The two critical challenges of this material are the stability with lithium metal anode and its ionic conductivity. Hence, the goal of this thesis was to design new Li2ZrCl6 based compounds with improved electrochemical properties. In this context, the influence of fluorine substitution on Li2ZrCl6 to form Li2ZrCl6-xFx (0 ≤ x ≤ 1.2) was systematically investigated. A remarkably improved anodic stability by fluorination was demonstrated and the electrochemical stability window of the expected interphase products was determined by theoretical calculations. While fluorine substitution provides an increased interfacial stability, the ionic conductivity decreases due to strong F---Li interaction, unfortunately. Hence, an element with low electronegativity and high polarizability would be an ideal candidate. This is because increased polarizability and lower electronegativity results in widened migration pathway, reducing the energy barriers, with increase in ion mobility. The sulphur substituted Li2ZrCl6-2xSx (0 ≤ x ≤ 0.5) was also investigated. Thanks to the low electronegativity and polarizability of sulphur, it improves the ionic conductivity in comparison to the undoped counterpart. The formation of biphasic mixtures namely trigonal and monoclinic was confirmed by neutron and X-ray diffraction studies. Theoretical calculations further confirmed the better diffusion for S doped system with two-dimensional diffusion pathway, rather than one-dimensional pathway for the undoped counterpart. However, sulphur is known for its low voltage stability and the formation of insulating species such as polysulphides and sulphates that reduce their electrochemical stability. Finally, the insights and benefits of the before studied substitutions were put together in one material by a dual anion substitution (both sulphur and fluorine) and studied in comparison to undoped Li2ZrCl6. In addition, four different electrolytes with sulphur, fluorine, sulphur-fluorine co-doped and undoped compounds were systematically tested in full cells with LiNi0.6Mn0.2Co0.2O2 (NMC622) positive electrode. Of all the electrolytes under study, the co-doping strategy provides a synergistic effect by increasing both ionic conductivity and electrochemical stability of the solid electrolyte. Hence, selection of dopants, leveraging the contrasting electronegativities of fluorine and sulphur, can yield a synergistic positive effect. The results indicate that the co-doped systems demonstrate increased capacity retention and reduced oxygen diffusion. The results are discussed in the following chapters in detail and have been published as scientific articles.
Methylation analysis of small and large cell variant of nodal marginal zone B-cell lymphoma
(Universität Ulm, 2026-04-27) Spada, Francesca; Möller, Peter; Buske, Christian; Anagnostopoulos, Ioannis; Cogliatti, Sergio
Among lymphoma, nMZoL is a rare subtype of non-Hodgkin lymphoma (NHL), accounting for less than 2% of cases. First described in 1986, nMZoL arises from B-cells of the nodal marginal zone and exhibits a highly variable clinical presentation. Conversely, nDLBCL is the most common subtype of NHL, characterized by aggressive behavior and significant heterogeneity in genetic and molecular profiles. The accurate differentiation between these subtypes is essential, as treatment strategies and prognoses differ significantly. Epigenetic mechanisms, particularly DNA methylation, play a pivotal role in lymphoma pathogenesis. Aberrant methylation patterns contribute to tumor progression by silencing tumor suppressor genes or activating oncogenes. Our study analyzed a large cohort of nMZoL and nDLBCL, sourced from nine German reference centers for lymphoma. We focused on genome-wide methylation profiling, a rapidly advancing field, to identify methylation signatures that differentiate nMZoL from nDLBCL. Genome-wide methylation data were generated using the Infinium MethylationEPIC BeadChip assay. 43 differentially methylated loci were identified between nMZoL and nDLBCL, with distinct methylation patterns associated with each entity. Additionally, the work explores histomorphological features, including the assessment of growth patterns (perifollicular, interfollicular, nodular/follicular, and diffuse), cell size (small, large, and abnormally large), and the status of the FDC network. The KI-67 proliferation index was categorized into low (<6%), intermediate (6-39%), and high (>40%). Cell and nuclear sizes were measured manually using ImageJ software, with thresholds based on standard deviations from centroblast sizes. Detailed characterization of growth patterns, cell sizes, and FDC network status provides practical criteria for differentiating between nMZoL and nDLBCL in routine pathological assessments. The identification of IgD as a potential ancillary marker for nMZoL supports its use in diagnostic workflows, particularly in cases with ambiguous morphology. Those results are summarized in a practical scheme easily testable and usable by every pathologist. In conclusion, this thesis advances the field of lymphoma research by bridging gaps in the current knowledge of nMZoL and nDLBCL. By combining traditional histomorphology with cutting-edge methylation profiling, the study sets the stage for more precise and personalized approaches to lymphoma diagnosis and management.
Novel concepts in endogenous and exogenous regulation of antiviral autophagy
(Universität Ulm, 2026-04-24) Hoenigsperger, Helene; Sparrer, Konstantin; Knöll, Bernd; Pfänder, Stephanie; Sieben, Christian
Autophagy is an evolutionarily conserved catabolic process essential for maintaining cellular homeostasis. Dysregulated autophagy is associated with several diseases like neurodegenerative disorders and cancer. Thus, autophagic flux, i.e. the turnover of cellular components by autophagy, is tightly controlled through post-translational modifications of major autophagy-related proteins. Beyond its homeostasis-governing role, autophagy functions as an integral part of anti-microbial innate immune defences. To evade autophagy, viruses have evolved intricate strategies. Nonetheless, autophagy activation is a promising therapeutic approach, outcompeting viral evasion mechanisms. However, current autophagy-modulating agents are insufficient and unspecific. Uncovering its endogenous regulatory pathways and viral evasion strategies may allow molecular insights that can be translated into autophagy-regulating therapeutics. Using a robust autophagy reporter system, I screened a kinase inhibitor library, whereas Casein Kinase 2 (CSNK2) emerged as a potent negative regulator of autophagy. Mechanistically, CSNK2 phosphorylates the tripartite motif-containing proteins TRIM2/3/71, thereby maintaining the inhibitory phosphorylation of ULK1 S757 and suppressing autophagy initiation. Pharmacological inhibition of CSNK2 activated autophagy and led to significant suppression of MeV and IAV replication in an autophagy-dependent manner. To design further novel autophagy-regulating approaches, I took advantage of the intricate interplay between viruses and autophagy. First, I dissected the impact of SARS-CoV-2 ORF7a on autophagy, which revealed that the 15 amino acid long N-terminal signal peptide is sufficient to activate autophagy. To engineer this signal peptide into an autophagy-inducing compound, a cell-permeable tag was attached to this sequence, resulting in the novel synthetic peptide 7aSP-R8. This peptide efficiently activated autophagy by inhibition of mTOR in various cell lines and primary cells. Finally, 7aSP-R8 restricted replication of diverse viruses including herpes- and flaviviruses. Taken together, I identified the CSNK2-TRIM2/3/71 axis to negatively regulate autophagy via facilitating the inhibitory phosphorylation S757 on ULK1. Targeting CSNK2 activates autophagic flux and restricts viral replication. In parallel, I discovered that the post-trafficking function of the signal peptide of SARS-CoV-2 ORF7a is to induce de novo autophagy. Engineering this signal peptide led to a self-delivering synthetic peptide that inhibits replication of a broad panel of viruses. Ultimately, these findings uncover new regulatory layers of autophagy and demonstrate that molecular insights into this degradation pathway may inspire antiviral autophagy-modulating approaches.
Theory and design of an intrinsically-linear multi-bit delta-sigma modulator
(Universität Ulm, 2026-04-24) Dalla Longa, Matteo; Ortmanns, Maurits; Bonizzoni, Edoardo
High linearity analog-to-digital converters (ADCs) are required in all applications for which it is important to preserve the signal frequency content. For this purpose, ΔΣ modulators (ΔΣMs) are often the preferred ADC architecture, due to their relaxed requirements on the analog circuitry compared to other architectures. Although single-bit versions are often used due to the intrinsic linearity of their feedback digital-to-analog converter (DAC), they have several disadvantages over their multi-bit counterparts, such as reduced maximum stable amplitude (MSA) and higher oversampling ratio (OSR) requirements. Multi-bit ΔΣMs have superior performance, but to achieve high linearity, they require some way to linearize their multi-bit feedback DAC, which would otherwise often be the limiting factor. To achieve this, two techniques are used mainly in the state of the art (SoA), calibration and dynamic element matching (DEM), which introduce additional complexity and come with disadvantages and limitations. Moreover, in the SoA a technique has been developed to built a 5-level intrinsically linear capacitive digital-to-analog converter (C-DAC), which while promising as feedback DAC in ΔΣMs, due to the reduced number of levels it does not allow to obtain all the advantages of true multi-bit operation. In this dissertation, a technique to expand the intrinsically linear DAC to true multi-bit operation is proposed, in order to be used in multi-bit ΔΣMs. The main goal is to develop an ADC architecture that can achieve high linearity, with robustness to process and operational condition variations, while keeping the complexity low. The theory behind the proposed DAC is thoroughly analyzed and a prototype discrete-time (DT) ΔΣM employing it in the feedback loop is built and measured, and SoA linearity performance is reported. Therefore, this work introduces an innovative way to achieve high linearity in multi-bit DACs, without the drawbacks of the conventional techniques. The proposed technique is not limited to be used in ΔΣMs, as the DAC can also be included in other ADCs architectures employing internal DACs, such as pipeline ADCs, opening the possibility of further research.
Combining NAD(P)H-FLIM and PLIM of Ir5 pH sensor to optimize photodynamic therapy through metabolic intracellular pattern segmentation
(Universität Ulm, 2025-11-03) Reess, K.; Naskar, N.; Kritchenkov, I. S.; Tunik, S. P.; Rueck, A.
AbstractMetabolic Fluorescence Lifetime Imaging Microscopy (FLIM) algorithms have become invaluable tools for exploring deep into the complex dynamics of cellular metabolism. Monitoring subcellular parameters is of interest, particularly during photodynamic therapy (PDT), to enhance treatment efficacy. By joining together Metabolic FLIM with PLIM, it is possible to evaluate cellular metabolic states, such as oxygen consumption, redox states, pH levels, and energy production pathways. The aim of this work is to use NADH FLIM and PLIM techniques to distinguish different metabolic pattern signatures in tumor and normal cell lines using a PLIM pH sensitive complex from the family of phosphorescent [(N^C)2Ir(N^N)]+ complexes. This investigation used a combination of 2-photon (2P) excited FLIM and PLIM techniques, coupled with time-correlated single-photon counting (TCSPC) detection. All the data were collected from living cells and were analyzed through exponential fitting. For the pattern segmentation we have used the phasor plot approach. By constructing a calibration curve and simultaneously acquiring NADH-FLIM and PLIM data from our pH sensor, we were able to identify metabolic regions and distinguished different pattern signatures in tumor and normal cell lines. This combined approach provides a comprehensive view of the tumor microenvironment, offering critical insights into parameters that influence photosensitizer localization, ROS generation, and therapeutic response. By identifying metabolic and pH heterogeneity at the single-cell level, this method contributes to improving the selectivity, precision, and overall efficacy of PDT treatments.

Browse

Recent Submissions