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Promotion of the transfer of materials science research results to the market launch by means of a structured framework program for interdisciplinary competence acquisition and demonstrator development - A case study Förderung des Transfers materialwissenschaftlicher Forschungsergebnisse hin zur Markteinführung durch ein strukturiertes Rahmenprogramm zur interdisziplinären Kompetenzaneignung und Demonstrator-Entwicklung-eine Fallstudie
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Effect of blast-cleaning on the fatigue strength of welded and non-welded constructional details
No full text474488Blast-cleaning, which is closely related to shot peening, is used to achieve a surface preparation grade of Sa 3 prior to the application of corrosion protection coatings. The blast-cleaning treatment with sharp-edged material is carried out with defined parameters (pressure, distance and angle). As a result of the blast-cleaning treatment, residual compressive stresses are induced near the surface, whereby the surface layer becomes work-hardened. Findings from the literature show that welded components made of mild structural steels (S235, S355) exhibit an improvement in fatigue strength. Constructional details with fillet and butt welds, whose potential crack location is the weld toe, can benefit from this. Improvement factors for post-treatment methods, such as TIG dressing, burr-grinding or high-frequency mechanical impact methods, have already been considered in standards or guidelines (IIW, FKM, EN 1993). In contrast, there are still no generally applicable improvement factors depending on the constructional detail when using blast-cleaning. The fatigue strength verification has become a design driver, particularly for structures subjected to high cyclic loads, which has a significant impact on manufacturing costs due to the amount of materials used. In particular for wind turbines, which are becoming larger and larger, and which are subjected to longer operating lifetimes, there are high cost pressures. The aim of the paper is to show whether the fatigue strength of welded and non-welded constructional details can be improved or whether a reduction in fatigue strength must be accepted by increasing the surface roughness. For this purpose, fatigue tests were carried out at constant amplitude loading (CAL) in the finite life region of the S-N curve and statistically evaluated according to EN 1993-1-9. It will also be shown that critical compressive preloads might influence the fatigue strength.7
Crack Behavior and Dynamic Response of Alumina Under Impact Loading
No full text10131022Two different methods of impact experiments were performed against alumina targets. Firstly, the ballistic performance of a protection system consisting of alumina tiles glued on a thick steel backup was investigated at impact velocities of 1050 m/s and 1500 m/s, respectively. The thickness of the tiles was varied. Differing terminal ballistic behaviour was observed at both velocities. Secondly, an attempt is made to understand the differing results with the aid of additionally performed edge-on impact experiments against thin alumina tiles in which the fracture behaviour of this ceramic was investigated
Defying Temperature: Reliable Compute-in-Memory in Monolithic 3D using BEOL Ferroelectric TFT
No full textMonolithic 3D integration represents a major breakthrough in the quest for high-density, energy-efficient systems. Ferroelectric thin-film transistors (Fe-TFT) have garnered increasing attention due to their outstanding capability in realizing brain-inspired computing and compatibility with the back-end-of-the-line (BEOL) fabrication process. Nevertheless, monolithic 3D ICs inevitability suffer from excessive temperatures which degrade the device characteristics degrading the system performance. In this work, we are the first to demonstrate how existing Fe-TFT crossbar arrays can be employed to sense temperature and detect run-time thermal fluctuations. This enables the Fe-TFT array to self-adaptively adjust bias conditions and operate reliably for the entire temperature range. We demonstrate the proof-of-concept using meticulously calibrated device simulations and temperature measurements of fabricated BEOL Fe-TFT devices. Further, we perform an extensive device-to-system thermal modeling for Fe-TFT-based monolithic 3D ICs to (1) acquire accurate thermal maps, (2) assess the temperature's influence on the inference accuracy of deep neural networks, and (3) showcase the efficacy of our technique in defeating temperature effects
A Novel Approach for Sensor Fusion Object Detection in Waste Sorting: The Case of WEEE
No full text177186This paper investigates the application of AI-based methods for characterizing waste materials in sorting processes. With the increasing use of sensors in waste sorting systems, there is an opportunity to integrate data and improve accuracy. AI methods, such as deep object detection models, have the potential to optimize waste management processes and promote sustainability. This research examines the utilization of Sensor Fusion Object Detection in a multi-sensor sorting system, focusing on two different data fusion methods: concatenation and image mirroring. In the first approach, image data is concatenated with data from a hyperspectral near-infrared camera (NIR) and an inductive sensor, where dimensionality reduction techniques are applied to the data from both sensors. The second approach relies on a specific combination of NIR and inductive sensor data to simulate the format of image data. A Siamese Object Detection architecture is developed to train the model. The real-world testing results show that both approaches improve waste characterization accuracy and reliability by augmenting the models' mean average precision (mAP). These findings demonstrate the potential for AI-based methods to transform the waste separation and management process, leading to more sustainable practices and resource efficiency
Distinct molecular mechanisms contribute to the reduction of melanoma growth and tumor pain after systemic and local depletion of alpha-Synuclein in mice
No full textEpidemiological studies show a coincidence between Parkinson's disease (PD) and malignant melanoma. It has been suggested that this relationship is due, at least in part, to modulation of alpha-Synuclein (αSyn/Snca). αSyn oligomers accumulate in PD, which triggers typical PD symptoms, and in malignant melanoma, which increases the proliferation of tumor cells. In addition, αSyn contributes to non-motor symptoms of PD, including pain. In this study, we investigated the role of αSyn in melanoma growth and melanoma-induced pain in a mouse model using systemic and local depletion of αSyn. B16BL6 wild-type as well as αSyn knock-down melanoma cells were inoculated into the paws of αSyn knock-out mice and wild-type mice, respectively. Tumor growth and tumor-induced pain hypersensitivity were assessed over a period of 21 days. Molecular mechanisms were analyzed by RT-PCR and Western Blot in tumors, spinal cord, and sciatic nerve. Our results indicate that both global and local ablation of Snca contribute to reduced tumor growth and to a reduction of tumor-induced mechanical allodynia, though mechanisms contributing to these effects differ. While injection of wild-type cells in Snca knock-out mice strongly increased the immune response in the tumor, local Snca knock-down decreased autophagy mechanisms and the inflammatory reaction in the tumor. In conclusion, a knockdown of αSyn might constitute a promising approach to inhibiting the progression of melanoma and reducing tumor-induced pain.371
Learning to Rank Features to Enhance Graph Neural Networks for Graph Classification
No full textA common strategy to enhance the predictive performance of graph neural networks (GNNs) for graph classification is to extend input graphs with node-and graph-level features. How-ever, identifying the optimal feature set for a specific learning task remains a significant challenge, often requiring domain-specific expertise. To address this, we propose a general two-step method that automatically selects a compact, informative subset from a large pool of candidate features to improve classification accuracy. In the first step, a GNN is trained to estimate the importance of each feature for a given graph. In the second step, the model generates feature rankings for the training graphs, which are then aggregated into a global ranking. A top-ranked subset is selected from this global ranking and used to train a downstream graph classification GNN. Experiments on real-world and synthetic datasets show that our method outperforms various baselines, including models using all candidate features, and achieves state-of-the-art results on several benchmarks.Online Firs
Extraction of valuable components from waste biomass
No full text147168Nature holds a great potential of complex valuable compounds that either are important precursor structures for derivatization in chemistry or pharmacy or are in itself structures or molecule mixtures with bioactivity that are yet too complex for synthetic production. Waste biomass is an additional resource of these structures that has too long been neglected. However, as the aims to build a sustainable fossil-free and bio-based economy from politics are clear, residues and waste from food production and consumption can no longer be overlooked. The production of biomass in addition to food supply would cost too much land and other resources, especially considering climate change effects of and on agriculture. Therefore, cascade approaches and holistic, full-potential use of biomass are in focus. Novel biorefineries should encompass circular and cascadian processes in order to ensure more sustainability. This chapter will focus on the extraction and potentials of high-value chemical compounds that can be directly obtained from residual biomass but also consider associated limitations like natural fluctuations, seasonal dependencies or harmonised extraction methods. Resources like vegetable oils, seafood and livestock remains, algal biomass, lignocellulosic biomass fruit pomace and waste food or water can deliver compounds for use in several high value bioproducts like biopharmaceuticals, bionutrients, biochemicals, biofertilizers, and biomaterials. Many of those are relevant as additives for food production, e.g. dyes, antioxidants, or health-beneficial additives. Another important field of application are biocosmetics or biocleanser where extracted compounds from residual biomass can be used as antioxidants, surfactants, emulsifiers, thickeners, fragrances, collagen analoga and dyes
Insights into the design of sustainable production technology Einblicke in die Gestaltung nachhaltiger Produktionstechnik
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Die Rolle der organisationsübergreifenden Zusammenarbeit für die Resilienz: Eine Analyse von organisationalen Prozessen, Strategien, Praktiken und Quellen
No full textThis dissertation examines the influences of inter-organizational cooperation on resilience and its implementation. Recent events like the COVID-19 pandemic and the Russia-Ukraine war have underscored the importance of organizational resilience. Yet there is still a need in organizational resilience research for multifaceted and empirical studies on the relationships between the resilience process, resilience capabilities and resources, other related sources of resilience, and the various resilience outcomes. In particular, research on the proactive phase of the resilience process - also known as strategic resilience - is still in its early stages. Inter-organizational cooperation, which spans multiple levels of analysis, offers a promising approach to filling these gaps, even though its role for resilience remains underexplored. Furthermore, from a practical perspective, it is known that firms form alliances in times of crisis as well as innovation-related partnerships during renewal processes.
To address these issues and to provide a holistic and interdisciplinary approach for explaining the building and implementation of resilience, this thesis employed both theoretical and practical methods within its research design. It begins with a narrative literature review that conceptualizes inter-organizational resilience as outlined in the first publication, drawing on interdisciplinary scientific scholars. This is followed by a desk research method in the second publication, to deepen the understanding and practical relevance of aforementioned conceptualizations. Furthermore, this thesis examined the subject through case studies, including 22 in-depth narrative interviews and various secondary data sources, with two different foci in the third and fourth publications.
The findings contribute to resilience research by developing a conceptual multi-level resilience framework that illustrates the dynamics of inter-organizational cooperation across the phases of anticipation, coping, and adaptation, highlighting the importance of capabilities and resources as key resilience sources. Second, it identifies interorganizational cooperation as a crucial strategy during crises, highlighting specific outcome trajectories. Third, it links proactive resilience to a holistic innovation strategy mix, showing how inter-organizational diversity, intra-organizational participation, and integrative learning processes contribute to building proactive resilience resources and capabilities. Fourth, the thesis demonstrates how cooperation projects between established firms and start-ups are implemented as practical measures to enhance proactive resilience, emphasizing the critical role of relationship quality. Collectively, these contributions provided insights into how inter-organizational cooperation strengthens resilience processes, capabilities, and resources, offering strategies and practices for achieving resilience outcomesDiese Dissertation untersucht den Einfluss der Zusammenarbeit zwischen Organisationen auf die Resilienz und deren Umsetzung. Ereignisse wie die COVID-19 Pandemie und der russisch-ukrainische Krieg haben die Bedeutung von organisationaler Resilienz unterstrichen. Gleichzeitig besteht in der organisationalen Resilienzforschung noch Bedarf an vielschichtigen Untersuchungen und empirischen Studien zu den Beziehungen zwischen Resilienzprozess, -fähigkeiten und -ressourcen, anderen verwandten -quellen und verschiedenen -auswirkungen. Insbesondere die Forschung zur proaktiven Phase des Resilienzprozesses befindet sich in einem frühen Stadium. Ein relevanter Ansatz zur Schließung dieser Lücke ist die organisationsübergreifende Zusammenarbeit auf mehreren Analyseebenen, da deren Rolle für Resilienz noch wenig erforscht ist. Aus der Praxis ist zudem bekannt, dass Unternehmen in Krisenzeiten Innovationskooperationen für Erneuerungsprozesse eingehen.
Um diese Aspekte zu beleuchten und einen ganzheitlichen und interdisziplinären Ansatz zur Erklärung des Aufbaus und der Umsetzung von Resilienz zu bieten, wurden in dieser Arbeit theoretische wie praktische Methoden angewandt. Die Arbeit beginnt mit einer narrativen Literaturrecherche, die das Konzept der organisationsübergreifenden Resilienz auf der Grundlage interdisziplinärer wissenschaftlicher Erkenntnisse in der ersten Publikation entwickelt. Darauf folgt in der zweiten Studie eine Desk-Research-Methodik, um Verständnis und Praxisrelevanz der Ergebnisse zu vertiefen. Zudem wird das Forschungsthema anhand von Fallstudien mit 22 narrativen Interviews und verschiedenen Sekundärdatenquellen mit zwei unterschiedlichen Schwerpunkten in der dritten und vierten Publikation untersucht.
Die Ergebnisse leisten einen Beitrag zur Resilienzforschung, indem sie einen konzeptionellen Mehrebenenrahmen für Resilienz entwickeln, der die Dynamik der Zusammenarbeit zwischen Organisationen in den Phasen der Antizipation, Bewältigung und Anpassung aufzeigt und die Bedeutung von Fähigkeiten und Ressourcen als wichtige Resilienquellen hervorhebt. Zweitens stellt die organisationsübergreifende Zusammenarbeit eine entscheidende Strategie in Krisen dar, wobei spezifische Vorgehensweisen aufgezeigt werden. Drittens wird die Verbindung zwischen proaktiver Resilienz und einem ganzheitlichen Innovationsstrategie-Mix hergestellt, indem gezeigt wird, wie organisationsübergreifende Diversität, unternehmensinterne Partizipation und integrative Lernprozesse zum Aufbau von Resilienzressourcen und -fähigkeiten beitragen. Viertens wird gezeigt, wie Kooperationsprojekte zwischen etablierten Unternehmen und Start-ups als praktische Maßnahme zur Steigerung proaktiver Resilienz funktionieren, wobei die Rolle der Beziehungsqualität hervorgehoben wird. Diese Beiträge bieten Einblicke, wie organisationsübergreifende Zusammenarbeit Resilienzprozesse, -fähigkeiten und -ressourcen stärkt und liefern Strategien und Praktiken zur Umsetzung von Resilien