What is OPUS?
Siegen University Library provides a free of charge repository named OPUS Siegen (OPUS = Online PUblication Server) with the purpose to publish, archive and retrieve electronical documents produced at the University of Siegen.
What will you find here?
You will find Open-Access-Publications from all faculties of Siegen University and from the "universi" publishing house. The University Library applies acknowledged quality standards and offers support for publishing your documents.
How to participate?
For uploading documents, sign on to OPUS via Shibboleth using your ZIMT-Account.
Recently published
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Publication Open Access From Concepts Towards Application: Tailored Hydrogel Systems as Versatile Materials in the Biomedical Field(2025)The rapidly evolving field of biomedicine demands innovative solutions to complex medical challenges, necessitating interdisciplinary approaches in materials development. Polymeric materials, particularly hydrogels, have emerged as vital components in addressing biomedical challenges due to their unique physicochemical properties and biocompatibility. This work investigates the development and application of hydrogel systems across three critical biomedical domains: biosensors, wound therapy, and implant technology. While these applications present distinct challenges, they share the fundamental requirement to precisely engineer the polymer architecture and the respective crosslinking mechanism. The research focuses on polymers based on 2-oxazoline and on acrylamide derivatives, respectively, which were selected for their synthetic versatility and adaptability to diverse application requirements. Various crosslinking strategies were systematically investigated, including simultaneous deprotection and crosslinking, multiphoton as well as one-photon photocrosslinking. For that, each methodology was evaluated within its specific application context. Specifically, the investigation encompasses comprehensive characterization of the resulting hydrogel systems, with particular emphasis on thermoresponsive behavior and surface properties including antifouling, anti-adhesive, and antibacterial characteristics. This thesis provides fundamental insights into both the underlying principles of tailored polymer network formation and their specific biomedical applications, contributing to the broader understanding of hydrogel-based materials in biomedicine.Source Type:4 1 - Some of the metrics are blocked by yourconsent settings
Publication Open Access Trump, populism, and social media(2025)This essay explores Donald Trump’s political communication as a paradigmatic shift toward media-driven populism. Focusing on Twitter, it examines how Trump bypassed traditional institutional channels, using social media for direct and polarizing engagement. Drawing on thinkers like Habermas, Luhmann, and Schmitt, the article argues that Trump’s strategy reflects a logic of “occasio” rather than “causa”: seizing moments for maximum visibility rather than pursuing consistent policy. Popularity—measured through likes, retweets, and reactions—becomes the sole currency of political legitimacy. The study challenges conventional distinctions between supporters and critics, showing how both contribute to Trump’s media presence. It concludes that Trump’s approach marks a lasting transformation of the public sphere: from deliberative reason to disruption, affect, and spectacle.43 57 - Some of the metrics are blocked by yourconsent settings
Publication Open Access Synthese und Untersuchung nanostrukturierter, katalytischer Beschichtungen auf Keramikschwämmen für das Power-to-Gas-Forschungscluster(2025)This research investigates TiO₂-based catalysts for the CO₂ methanation in the context of Power-to-Gas applications, contributing to long-term energy storage and decarbonization in line with the Paris Agreement. Open-cell ceramic foam carriers coated with nanostructured nickel layers are utilized to enable stable and efficient operation under dynamic conditions. The developed systems exhibit high methane yields close to thermodynamic equilibrium, demonstrate long-term stability and are suitable for economically viable load-change operations.17 12 - Some of the metrics are blocked by yourconsent settings
Publication Open Access Integratives Design von neuartigen Mo-Si-Legierungen und Schutzschichten für Hochtemperaturanwendungen(2024)Mo Si based alloys with high Ti concentrations represent a new class of high temperature materials offering promising properties for structural applications such as gas turbines, exceeding the thermal capabilities of Ni based superalloys. The combination of these three elements provides high melting temperatures, substantial creep resistance, and exceptional phase stability. Recent alloys in this field have successfully addressed the primary challenge of inadequate oxidation resistance known as "pesting" in air environment. Furthermore, it is recognized that water vapor, constituting approximately 10 vol.% of relevant turbine environments, causes otherwise protective oxides such as SiO2 to react, forming volatile Si(OH)4. However, the exact mechanisms remain inadequately understood. This study evaluates the high-temperature oxidation behavior of both multi phase (MoSS, T1, T2, A15) (Mo9Si8B and Mo12,5Si8,5B27,5Ti2Fe (at.%)) and two phase (MoSS, T1/D88) (Mo20Si52,8Ti and Mo21Si34Ti0,5B) Mo Si (B) (Ti) (Fe) alloys under dry and water vapor containing (wet) atmosphere. To ensure reliable oxidation protection at lower temperatures in wet atmosphere, Si and Yb silicate Environmental Barrier Coatings (EBCs) are utilized. The goal is to acquire comprehensive knowledge about the oxidation behavior of Mo Si (B) (Ti) (Fe) alloys with and without coating systems in complex atmospheres. Oxidation tests are conducted at 1200 °C in both dry and wet atmospheres for up to 100 h. Techniques such as thermogravimetric analysis (TGA), scanning electron microscopy (SEM), X ray diffraction (XRD), and transmission electron microscopy (TEM) including electron energy loss spectroscopy (EELS) are employed to assess the oxidation kinetics and to characterize the microstructural development of the oxide layers. The results from these investigations highlight that an increase in Ti content in general enhances the oxidation resistance in the Mo Si (B) (Ti) (Fe) system, manifesting itself in reduced oxide layer thicknesses and lower specific mass changes. This enhancement is closely linked to a finer and more homogeneous microstructure, which promotes the oxidation stability via shorter diffusion paths. However, a higher Ti content in coated alloys leads to thicker oxide layers and higher specific mass changes, particularly in the Mo20Si52,8Ti alloy as compared to the Mo12,5Si8,5B27,5Ti2Fe alloy. The use of a wet atmosphere results in increased specific mass changes and thicker oxide layers across all alloys, primarily due to the formation of volatile oxides such as MoO3, which accelerate the oxidation rate. Coated alloys demonstrate exceptional oxidation resistance with minimal specific mass changes and oxide layer thicknesses, especially evident for the Mo12,5Si8,5B27,5Ti2Fe alloy. Additionally, the investigation of the oxide layer on the Mo20Si52,8Ti alloy confirms the significance of a nearly pore-free SiO2 layer for effective oxidation resistance. The supplementary application of Yb silicate layers effectively minimizes the impact of water vapor and shows only a slightly worsened oxidation behavior under wet conditions, underscoring the protective nature of the coatings. These results emphasize the necessity of an effective coating system to ensure satisfactory oxidation resistance in wet atmospheres.15 11 - Some of the metrics are blocked by yourconsent settings
Publication Open Access Embedded AI for Real-time Health State Assessment and Treatment Recommendation in Rescue Operations(2025)Rescue emergencies are generally quite strenuous and challenging because they deal with human lives in a situation where it is difficult to apprehend precisely the health status of a distressed patient due to personal and work limitations. Often the rescue personnel have to deal with high levels of mental and physical stress, trauma, and emotional strain during rescue operations, especially when dealing with injured and vulnerable victims. This certainly impacts their decision-making abilities and overall well-being. Time, the main constraint in such rescue situations, also plays a vital role in decision-making. Therefore, it is necessary to recognize relevant situations i.e. health complications of the rescue patients on site, and to take appropriate first aid measures. The situation may change during the further course of initial treatment, with rescue workers judging this primarily by the visible condition of the emergency patient, the data from medical equipment (e.g., ventilator, ECG), and the mission description from the control room. Such changes are required to be responded to immediately, for example by resuscitation or appropriate medication. That's why, waiting for results from medical tests like MRI and ECG which are time-consuming and not suitable for emergency cases is not considered suitable for rescue cases. Considering these technical constraints, the doctoral thesis focuses on employing artificial intelligence (AI) models in two aspects that can expedite and improve the rescue process. Firstly, for the diagnosis of health complications in rescue situations and secondly to identify the correct medications as a part of initial treatment. A major part of this research is focused on advanced data analysis techniques that were used to extract information from 12 years of rescue records of 273,283 cases in the German city of Siegen-Wittgenstein. The initial data received from the rescue station was raw and in many cases contained incomprehensible information for which Natural Language Processing (NLP) techniques were applied to extract and interpolate relevant attributes. Subsequently, a detailed method for creating various AI models to promptly detect six key complications— Cardiovascular, Respiratory, Psychiatric, Neurological, Metabolic, and Abdominal—was conducted and is detailed in this dissertation. To develop the detection models for each complication, Artificial Intelligence(AI) algorithms like machine learning including both classical and deep learning approaches were used. To train these models attributes like patients' medical history, health diagnoses including neurological assessment, vital signs, initial impression of the rescue personnel, administered medications, and other treatment paths were used. During the course of development, one primary objective was to identify the model achieving the greatest accuracy and precision. Based on this research, Extreme Gradient Boosting (XGB) and Random Forest (RF) algorithms were found as the most promising, showcasing accuracy rates ranging from 80\% to 96\%. After recognizing health complications, further research was done to find out if AI can also be implemented to determine possible medications based on detected complications and patients' health vitals. The result achieved from it also was impressive with accuracy close to 80\%. AI models are further tested by deploying them into various accelerators, such as ARM processors, FPGAs and microcontrollers, to evaluate their performance based on inference time. The overall focus of this research is to overcome the rescue challenges in real-time by recognizing rescue situations and improving the quality of care and efficiency of rescue personnel.Source Type:19 12