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A CLASSIFICATION OF GRID-FORMING CONVERTER CONTROL AND ITS APPLICATION TO IMPROVE POWER SYSTEM STABILITY AND RESILIENCE
No full text25382542Over the last decade, different methods of grid-forming control have been formulated, all aiming to emulate the basic behavior of synchronous generators. Comparative studies show that some of these methods have similar or even identical characteristics if parameterized in an adequate way. Focusing on the power control loop, one important difference is whether the grid-forming control will react to disturbances in the grid frequency and voltage amplitude based on the rate of change or based on the deviation from nominal. In terms of active power control, this correlates to the inverter contributing only to inertia, only to the frequency containment reserve or both. This article provides a comparison and classification of existing grid-forming control methods and illustrates the application in a simulative case study and experimental field test
3D binder jet printing of Ti-6Al-4V alloy for potential application in biomedicine
No full textThe 3D binder jet printing process offers many advantages over other AM technologies concerning fabrication time, cost-effectiveness, residual stresses, and the need for the build plate. Nevertheless, small-scale production of large and complex-shaped parts is still challenging because of low densification, heterogeneous shrinkage, and shape distortion during sintering. Besides, the potential of the process has also been shown for few materials. Herein, the potential of 3D binder jet printing of Ti-6Al-4V alloy for small-scale production of biomedical parts is shown. The microstructure and mechanical properties of the sintered parts are compared with ASTM F2885 MIM standard. It is shown that fine-tuning of the particle size distribution of the powder bed and controlled de-binding and sintering in partial pressure of argon yield high-density green (65%) and sintered (>96.5%) parts with minimum shape distortion. The potential of the process for small-scale production of titanium parts is demonstrated
Politische Handlungsbedarfe für die industrielle Transformation in Sachsen-Anhalt. SETUp-Positionspapier 2025
No full textZukunftsfähige Transformation durch verlässliche Energiepolitik, Infrastruktur und Kooperation Die energieintensive Industrie Sachsen-Anhalts steht vor der doppelten Herausforderung, die politisch geforderte Klimaneutralität zu erreichen und gleichzeitig im internationalen Wettbewerb bestehen zu müssen. Die Unternehmen des SETUp-Verbundes - ein eigenfinanziertes, branchenübergreifendes Industrienetzwerk und strategischer Partner des Landes - sichern über 5.000 Arbeitsplätze, verbrauchten im Jahr 2024 rund 1.600 GWh Erdgas und 300 GWh Strom und haben ihre Effizienzpotenziale weitgehend ausgeschöpft, Prozesse elektrifiziert und belastbare Transformationspfade bis 2045 entwickelt. Die Industrie kann und will transformieren – aber ob sie es kann, entscheidet das Land.
Die industrielle Transformation folgt einer klaren technischen Dreifachstrategie: Erneuerbarer Strom, Elektrifizierung und grüner Wasserstoff. Diese drei Säulen definieren, wie die Unternehmen fossile Energieträger verlassen und ihre Produktion klimaneutral gestalten. Analysen realer Lastgänge zeigen, dass die benötigte elektrische Energie des Verbundes im Transformationspfad von heute 300 GWh/a auf rund 700 GWh/a steigt. Für nicht elektrifizierbare Prozesse werden zusätzlich 1200 GWh/a grüner Wasserstoff benötigt. Damit verursachen bereits sieben Unternehmen Infrastrukturbedarfe, die ohne vorausschauende Landesplanung nicht realisierbar sind. Heute bremsen insbesondere fehlende Netzanschlusskapazitäten von +5 bis +100 MW je Standort, unklare Perspektiven beim Wasserstoffkernnetz, steigende Energie- und Netzentgelte sowie lange Genehmigungsverfahren die notwendige Transformation. Ohne Infrastruktur, planbare Energiepreise und verlässliche Zeitachsen können Investitionen nicht ausgelöst werden.
Gleichzeitig verfügt Sachsen-Anhalt über herausragende Standortvorteile: ein strukturelles Erneuerbare-Energien-Überangebot, bestehende H2-Modellregionen, qualifizierte Fachkräfte, verfügbare Flächen und hohe industrielle Akzeptanz. Diese Stärken können zu einem echten Wettbewerbsvorteil werden – wenn sie jetzt strategisch genutzt und in belastbare politische Rahmenbedingungen überführt werden. Die Industrie steht bereit, Verantwortung zu übernehmen und in klimafreundliche, zukunftsfähige Produktion zu investieren. Doch klar ist: Defossilisierung darf nicht zu Deindustrialisierung werden. Damit Sachsen-Anhalt industrielles Kernland bleibt und gleichzeitig klimafreundliches Industrieland wird, braucht es fünf zentrale politische Entscheidungen
Pipeline for synthetic remote sensing data generation using Unreal Engine
No full textThe effectiveness of AI models in remote sensing critically depends on the availability of large, annotated datasets. However, in many application areas such as defense, real-world data is expensive, restricted, or unavailable. To address this limitation, we present a highly customizable synthetic data generation pipeline based on the Unreal Engine. The workflow enables the creation of photorealistic satellite imagery and automatically provides annotations in formats such as COCO Panoptic. Key features include a modular spawn point system for dynamic scene composition and a dedicated graphical user interface (SimUI), specifically designed for configuring data generation. Our pipeline not only provides a solution for generating synthetic data of high diversity and visual fidelity, but also directly addresses the critical bottleneck of usability. The complexity of the native Unreal Engine interface represents a substantial barrier to effective use, particularly for researchers without prior experience in game engines. By lowering this barrier, the proposed system makes advanced synthetic data generation more accessible and practical. In a user study with ten participants, the pipeline reduced the time required to generate a dataset of 800 images with diverse aircraft formations to an average of under ten minutes, compared to several hours of training typically needed for the native Unreal Engine interface. These results demonstrate that the proposed pipeline combines scalability, realism, and usability, thereby offering an effective solution to overcome the data scarcity bottleneck in remote sensing object detection
Chances and Limitations of Personal and Anonymized Data Processing Implementing Appropriate Technical and Organizational Measures and Creating Added Value in Smart Cities
No full text773787Article 32 GDPR regulates the obligation to implement appropriate technical and organizational measures whenever personal data is being processed. In this paper, we want to link questions arising from taking appropriate technical and organizational measures with considering the chances and limitations of both, personal and anonymized data processing and the potential added value of personal and anonymized data exchange within a smart city context. We demonstrate the link through a legal analysis and 30 structured interviews with smart city participants
Interpreting Black-box Machine Learning Models for High Dimensional Datasets
No full textMany datasets are of increasingly high dimension- ality, where a large number of features could be irrelevant to the learning task. The inclusion of such features would not only introduce unwanted noise but also increase computational complexity. Deep neural networks (DNNs) outperform machine learning (ML) algorithms in a variety of applications due to their effectiveness in modelling complex problems and handling high-dimensional datasets. However, due to non-linearity and higher-order feature interactions, DNN models are unavoidably opaque, making them black-box methods. In contrast, an interpretable model can identify statistically significant features and explain the way they affect the model's outcome. In this paper, we propose a novel method to improve the interpretability of blackbox models in the case of high-dimensional datasets. First, a black-box model is trained on full feature space that learns useful embeddings on which the classification is performed. To decompose the inner principles of the black-box and to identify top-k important features (global explainability), probing and perturbing techniques are applied. An interpretable surrogate model is then trained on top-k feature space to approximate the black-box. Finally, decision rules and counterfactuals are derived from the surrogate to provide local decisions. Our approach outperforms tabular learners, e.g., TabNet and XGboost, and SHAP-based interpretability techniques, when tested on a number of datasets having dimensionality between 54 and 20,53111GitHub: https://github.com/rezacsedu/DeepExplainHidim
Impact of Off-State Stress on SiGe-channel p-FETs in 22nm FDSOI under Large-Signal Operation
No full text173176With the growing interest in high-frequency applications for CMOS, conventional DC reliability analysis might not be sufficient to tackle the reliability issues in this domain. Especially in complex modulation schemes and high-efficiency power amplifier (PA) applications, the transistors are subjected to a strong lateral field when the gate voltage lies below the threshold. Under those conditions, hot-carriers (HC) injection during off-state has become more pronounced. In this work, the impact of off-state stress on p-channel FDSOI during such conditions is analyzed and separated from normal HC degradation. A reverse-degradation with negative threshold voltage shift is observed, which is in the opposite direction than normal HC degradation. A mean to restore the device's large-signal performance after HC degradation is also investigated
Investigation of the long-term adhesion and barrier properties of a PDMS-Parylene stack with PECVD ceramic interlayers for the conformal encapsulation of neural implants
No full textIn this paper, we investigate the long-term adhesion strength and barrier property of our recently proposed encapsulation stack that includes PDMS-Parylene C and PECVD interlayers (SiO2 and SiC) for adhesion improvement. To evaluate the adhesion strength of our proposed stack, the sample preparation consisted in depositing approximately 25 nm of SiC and 25 nm of SiO2 on half wafers, previously coated with Parylene C. Next, 50 µm PDMS was spin-coated on top. Finally, the samples were detached from the Si wafer and soaked in a PBS solution at 67 °C to accelerate the aging process. Two samples were also implanted, subcutaneously, on the left and right subscapular regions of a rat. The optical inspection and peel tests performed after two months confirmed our preliminary findings and showed a significant improvement of the adhesion in our proposed encapsulation stack compared to the case of PDMS on Parylene C alone. In addition, the X-ray photoelectron spectroscopy (XPS) analysis at the interface between SiC and Parylene C showed different peaks for the interface compared to the reference spectra, which could be an indication of a chemical bond. Finally, water vapor transmission rate (WVTR) tests were performed to investigate the barrier property of our proposed encapsulation stack against water vapor transmission. The results demonstrated that the proposed stack acts as a significantly (two orders of magnitude) higher barrier against moisture compared to only Parylene C and PDMS encapsulation layers. The proposed method yields a fully transparent encapsulation stack over a broad wavelength spectrum that can be used for the conformal encapsulation of flexible devices and thus, making them compatible with techniques such as optical imaging and optogenetics
Nitrogen pollution in rivers as potential driver of invertebrate species turnover
No full textNitrogen pollution represents one of the most significant threats to European freshwater ecosystems, with nitrite (NO2-N) standing out as a highly toxic compound for aquatic organisms, particularly vertebrates. Despite its recognized toxicity, little is known about its effects on invertebrates, even as riverine ecosystems experience profound species turnover. Here, we investigated the lethal and sublethal effects of nitrite on three representative amphipod species (Gammarus fossarum, G. pulex, and G. roeselii), which occupy distinct river sections and ecological niches. These species serve as models for assessing how nitrogen pollution may shape invertebrate communities across freshwater habitats. A series of laboratory bioassays revealed that G. fossarum, a species associated with upstream sections and pristine conditions, was the most sensitive to nitrite exposure, followed by the midstream species G. pulex and the long-established downstream species G. roeselii. To contextualize these findings, we compared the nitrite vulnerability of these amphipods with that of other freshwater invertebrates, offering a comprehensive perspective on how nitrogen pollution reshapes aquatic communities. While many invertebrate groups exhibit lower vulnerability to nitrite due to their reliance on hemocyanin - an oxygen-transport molecule mostly unaffected by nitrite oxidation - our results underscore significant interspecific differences in tolerance. For sensitive insect species, lethal effects occurred already at environmentally relevant concentrations, highlighting their exceptional vulnerability. In contrast, more tolerant groups such as amphipods survived higher concentrations, yet still displayed sublethal impairments, most notably a reduced leaf litter consumption - a key process in stream nutrient cycling - and altered behavioral responses at comparable exposure levels. Molluscs exhibit the highest tolerance, whereas insects are the most sensitive. Among crustaceans, tolerance varies widely, with a relationship to chloride content of the water mitigating the toxicity of nitrite. Chloride concentrations generally rise along the course of a river, placing upstream regions with naturally low chloride levels and their species at heightened risk. These differences highlight the potential role of nitrogen pollution as a driver of species turnover, particularly in multistressor environments. By linking species-specific sensitivity to broader ecological processes, like leaf litter consumption, this study provides critical insights into cascading effects of nitrogen pollution on freshwater biodiversity and ecosystem stability.3
Analysis of the Effect of cutting Fluids on the Impact Resistance of Polycarbonate Sheets by Means of a Hypothesis Test
No full text23582365Vision panels in machine tools protect the operator from ejected fragments in case of an accident. Due to its excellent impact resistance, polycarbonate is used as material for such vision panels. However, when exposed to cutting fluids the impact resistance of polycarbonate vision panels decreases significantly. A previous study examined the effect of two different cutting fluids on polycarbonate sheets by impact tests. Both cutting fluids employed were highly alkaline but differed in composition, with one cutting fluid containing phenoxyethanol as solvent and the other dicyclohexylamin as amine. Due to the exposure to cutting fluids, a maximum decrease of 10 % in impact resistance was observed. However, the results were subject to considerable scatter, such that the decrease in impact resistance could be the result of statistical scatter instead of the exposure to cutting fluids. Owing the limited number of test samples in impact tests, a pronounced scatter is a typical phenomenon observed when studying the impact resistance of polycarbonate sheets. The effects of material alterations on the impact resistance of polycarbonate arising from contact with cutting fluids are initially difficult to distinguish from scattering due to the inertia of chemical degradation processes. However, a statistical evaluation permits to draw meaningful conclusions even in the case of pronounced scattering. Despite the advantages offered by a statistical evaluation, impact test results are rarely analyzed by statistical means, leaving the influence of the different cutting fluids and its constituents to remain uncertain. Therefore, the present study examines the influence of cutting fluids containing phenoxyethanol and dicyclohexylamin on polycarbonate sheets subjected to impact tests by means of a hypothesis test. By comparing the results of impact tests of polycarbonate sheets with and without prior exposure to cutting fluids the influence of cutting fluids on the impact resistance is assessed. It is shown that the previously observed decrease in impact resistance can be attributed to statistical scatter. For future studies, the present investigation provides an estimate of the time and test sample number necessary to obtain statistically significant results when studying the aging of polycarbonate due to the exposure to cutting fluids