TY - JOUR A1 - Gedeon, Steven A1 - Huber, Florian T1 - Using AI-Enabled Images and Comic Narrative to Enhance Entrepreneurship Education JF - Entrepreneurship Education and Pedagogy N2 - This learning innovation is an engaging technique to help students learn abstract concepts such as entrepreneurship theory, mindsets, and methods in a playful and exciting way. We explore how current AI tools can be used by entrepreneurship educators to enhance their course materials by creating memorable images and story-based, highly visual comic book content (“graphic novels”). We implemented these enhancements in an interactive learning platform based on Articulate Storyline and tested them in an introductory entrepreneurship course with over 2000 students per year on building an entrepreneurial mindset. In this article, we include sample copies of the images and graphic novel comics and highlight key methods, lessons, results, and design artifacts created during the course of our learning journey. Educators may add these free Open Educational Resource (OER) assets to their own courses by linking to the online version. We believe this approach to entrepreneurship education enhances students’ engagement, memory retention, and the ability to identify and name underlying concepts and entrepreneurship theories. We hope to spark the interest of other entrepreneurship educators to use similar approaches at their universities. UR - https://doi.org/10.1177/25151274251358708 Y1 - 2025 UR - https://doi.org/10.1177/25151274251358708 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-68060 SN - 2515-1274 VL - 9 IS - 2 SP - 327 EP - 345 PB - Sage CY - London ER - TY - JOUR A1 - Azzam, Mohamed A1 - Sauer, Dirk Uwe A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Comprehensive Analysis of Float Current Behavior and Calendar Aging Mechanisms in Lithium‐Ion Batteries JF - Batteries & Supercaps N2 - Aiming to quantify degradation currents from solid electrolyte interphase formation (ISEIgrowth) and gain of active lithium due to cathode lithiation (ICL), resulting from electrolyte decomposition, the float current behavior of lithium-ion batteries is investigated with different cathode materials. The float current, IFloat , represents the recharge current required to maintain the cell at a fixed potential during calendar aging. This current arises as lithium is irreversibly consumed at the anode or inserted into the cathode, shifting the electrode potentials. To account for the asymmetric response of the electrodes, a voltage-dependent scaling factor, SF, is introduced, derived from the slopes of the electrode-specific voltage curves. Using this factor in combination with measured float currents and capacity loss rates from check-up tests, ISEIgrowth and ICL is quantified at 30 °C across various float voltages. Although the SF and capacity data are limited to 30 °C, the model is extended to a range of 5–50 °C using only float current measurements. The results show that using capacity loss rates alone underestimate ISEIgrowth and that ICL, contributes significantly to the observed float current at elevated voltages, indicating that cathode lithiation plays an increasingly important role in high-voltage calendar aging. UR - https://doi.org/10.1002/batt.202500349 Y1 - 2025 UR - https://doi.org/10.1002/batt.202500349 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-68054 SN - 2566-6223 VL - 9 IS - 1 PB - Wiley CY - Weinheim ER - TY - JOUR A1 - Volpato, Guilherme A1 - de Souza Pinto Pereira, Adriano A1 - Neumeier, Steffen A1 - Hotza, Dachamir A1 - Göken, Mathias A1 - Tetzlaff, Ulrich A1 - Fredel, Márcio Celso T1 - Influence of a Standard Heat Treatment on the Microstructure and Properties of Inconel X‐750 Produced by Laser Powder Bed Fusion JF - Advanced Engineering Materials N2 - The production of nickel‐base superalloys through powder bed fusion using a laser beam (PBF‐LB) offers a promising method for reducing the cost of aeronautical components, especially those with complex geometries. However, when these materials are processed using PBF‐LB, the standard heat treatments developed for conventional manufacturing routes do not consistently yield predictable microstructures or mechanical properties. Thus, this study analyzes how PBF‐LB affects the microstructure and mechanical behavior of Inconel alloy X‐750 when compared to a hot‐rolled counterpart after undergoing a standard precipitation‐hardening heat treatment (solution annealing, stabilization, and precipitation). Microstructure is examined using analytical electron microscopy and high‐energy X‐ray diffraction, while mechanical behavior is assessed through microhardness. Significant differences between both manufacturing routes are detected, so that PBF‐LB processing led to an increase in grain size, anisotropy, fraction of low‐angle grain boundaries, mean angle of misorientation, and dislocation density. Moreover, PBF‐LB promoted the formation of γ′‐Ni3(Al,Ti) and η‐Ni3Ti phases during solution annealing and stabilization, respectively. Notably, the formation of γ′ contributes to an anomalous microhardness increase observed between these steps. These findings suggest that PBF‐LB may inhibit recrystallization and facilitate precipitation during heat treatment, thereby affecting the performance of components produced using this technology. UR - https://doi.org/10.1002/adem.202500306 Y1 - 2025 UR - https://doi.org/10.1002/adem.202500306 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-67931 SN - 1527-2648 VL - 27 IS - 24 PB - Wiley CY - Weinheim ER - TY - JOUR A1 - Emberger, Lukas A1 - Nair, Gireesh A1 - Lichtenegger, Klaus A1 - Moser, Maria A1 - Summ, Thorsten A1 - Natiesta, Thomas A1 - Fan, Jianhua A1 - Wang, Pengcheng A1 - Unterberger, Viktor A1 - Ohnewein, Philip T1 - Open data in the solar thermal community: Status, barriers, and opportunities JF - Solar Energy Advances N2 - Open data in the renewable energy sector could contribute to a greener future and reduce carbon emissions. This study investigates existing open datasets in the solar thermal domain, challenges in publishing and using open data and its potential impact. The results support the common belief that open data is useful, offering considerable benefits for data re-users and the solar thermal community. While substantial open data in the solar thermal domain already exists, some datasets like plant statistics and cost data are hard to utilize due to licensing, accessibility, and quality issues. The study shows that data owners benefit less from publishing data compared to data re-users and service providers. While data sharing seems appealing to data owners, several barriers discourage data sharing. Suggestions to promote the use and publications of open data in solar thermal domain are discussed. UR - https://doi.org/10.1016/j.seja.2025.100114 Y1 - 2025 UR - https://doi.org/10.1016/j.seja.2025.100114 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-66691 SN - 2667-1131 VL - 2025 IS - 5 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - James, Stuart Daniel A1 - Killinger, Markus A1 - Mutanga, Chiedza Ngonidzashe A1 - Pirard, Romain A1 - Einax, Mario A1 - Huber, Matthias A1 - Bader, Tobias T1 - The hybrid renewable energy community approach (HyRECA): Synergising electricity access with bush encroachment mitigation in rural Southern Africa JF - Renewable and Sustainable Energy Transition N2 - Rural electrification and bush encroachment in Southern Africa have long been studied separately. Research shows that hybrid renewable energy systems (HRES) offer viable solutions for off-grid communities, and bush encroachment mitigation is widely recognised as an ecological priority. Using Jamataka, Botswana, as a case study, this study integrates both, asking under which conditions encroacher bush-based HRES are economically viable, which electricity access levels local populations can afford, and whether biomass utilisation contributes to mitigation. Findings indicate strong potential for bush-based HRES in off-grid areas, but competitiveness declines where low-cost grid electricity is available. Economic viability is examined through levelised cost of electricity (LCOE) across alternative HRES configurations. HOMER Pro® simulations indicate PV/biomass/battery systems are most cost-effective off-grid, achieving 100 % renewable fractions, near zero CO₂ emissions, and LCOE of 0.246 $/kWh. In grid-connected contexts without feed-in, PV/diesel/grid combinations dominate (LCOE 0.117 $/kWh) due to low tariffs, but with higher emissions. A novel affordability analysis using household willingness to pay and the World Bank Multi-Tier Framework indicates that all households reach at least Tier 3 electricity access under grid-connected systems and >70 % off-grid, supporting household-use of medium-power appliances. Sustainable biomass extraction clears ∼12 ha annually (∼120 t) in Jamataka, aiding bush encroachment mitigation. Upscaling indicates potential to electrify 1.35 million people in >900 bush-encroached villages across Botswana, Namibia, and South Africa, using <1 % of encroached land – highlighting significant untapped potential. Future research should validate findings through geospatial modelling with high-resolution biomass data and spatially sensitive biomass cost models for region-wide planning. UR - https://doi.org/10.1016/j.rset.2025.100136 Y1 - 2025 UR - https://doi.org/10.1016/j.rset.2025.100136 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-66620 SN - 2667-095X VL - 2026 IS - 9 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Baum, Heinz-Georg A1 - Fink, Christian A1 - Fischer, Thomas M. A1 - Günther, Edeltraud A1 - Günther, Thomas A1 - Haller, Axel A1 - Kafadar, Kalina A1 - Marten, Kai-Uwe A1 - Schultze, Wolfgang A1 - Wittmann, Robert T1 - „Konnektivität“ als Strukturprinzip akademischen Wirkens von Prof. Dr. Dr. h.c. mult. Adolf G. Coenenberg – Ein Nachruf JF - Schmalenbach Impulse UR - https://doi.org/10.54585/JAEY3059 Y1 - 2025 UR - https://doi.org/10.54585/JAEY3059 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-66127 SN - 2749-9804 N1 - Ausgenommen von der Lizenz sind im Beitrag enthaltene Zitate und sonstige eingebundene externe Inhalte. VL - 5 PB - Schmalenbach-Gesellschaft fur Betriebswirtschaft CY - Frechen ER - TY - JOUR A1 - Venâncio, Raissa A1 - Pinzón C., Manuel J. A1 - Aguiar dos Santos, João Pedro A1 - Galantini, Isabela A1 - Cruz, Hugo A1 - Rufino Júnior, Carlos Antônio A1 - Doubek, Gustavo A1 - Branco, Luís A1 - Franco, Débora V. A1 - Da Silva, Leonardo M. A1 - Gonçalves, Josué A1 - Zanin, Hudson T1 - Tailoring electrolyte solvation for improved Na-based supercapacitor efficiency: an operando characterization approach JF - Journal of Materials Chemistry A UR - https://doi.org/10.1039/D5TA07938A Y1 - 2025 UR - https://doi.org/10.1039/D5TA07938A SN - 2050-7488 SN - 2050-7496 VL - 14 IS - 10 SP - 5786 EP - 5805 PB - RSC CY - Cambridge ER - TY - JOUR A1 - Upadhyay, Navneet A1 - Georges, Munir T1 - Transform-based nonlinear speech enhancement for monaural scenarios JF - International Journal of Speech Technology UR - https://doi.org/10.1007/s10772-025-10239-4 Y1 - 2025 UR - https://doi.org/10.1007/s10772-025-10239-4 SN - 1572-8110 VL - 29 IS - 1 PB - Springer Science+Business Media CY - Dordrecht ER - TY - JOUR A1 - Reuthlinger, Eva A1 - Sinha, Tanja T1 - Impact Investing from an European Perspective – Do Good and Earn Money? JF - Copernican Journal of Finance & Accounting N2 - Impact Investing provides a promising way to fund sustainable development while balancing financial, social, and environmental goals. This study compares the performance of Impact, Conventional, and ESG Portfolios in the European stock market over more than 10 years, using Markowitz Optimization and Naive Diversification. The findings show that Impact Portfolios yield the highest returns, without sacrificing financial performance when integrating sustainability criteria that go beyond the classical ESG investing. UR - http://dx.doi. org/10.12775/CJFA.2025.005 Y1 - 2025 UR - http://dx.doi. org/10.12775/CJFA.2025.005 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-65823 SN - 2300-3065 VL - 14 IS - 1 SP - 87 EP - 109 PB - Nicolaus Copernicus University CY - Toruń ER - TY - JOUR A1 - Panzer, Hannes A1 - Landesberger, Martin A1 - Luzin, Vladimir A1 - Rauner, Dominik A1 - Wolf, Daniel A1 - Zaeh, Michael T1 - Evaluating the predictive capabilities of part-scale residual stress simulations of PBF-LB/M up to crack formation by a comparison to neutron diffraction JF - Engineering Fracture Mechanics N2 - Additive manufacturing technologies have proven to be an excellent alternative to conventional production methods, especially when geometrically complex parts and low production quantities are aimed at. Specifically, powder bed fusion of metals using a laser beam (PBF-LB/M) additionally allows for the manufacturing of mechanically highly stressable parts. However, the heat input through the laser beam into the material and an irregular cooling during the processing result in the formation of high residual stresses. These lead to form deviations outside the specified tolerances and may accumulate to an extent, at which stress-induced cracking occurs. This emphasizes the need for an accurate prediction of the residual stresses during the PBF-LB/M process with the goal of a first-time-right additive manufacturing. In this study, three specimens exhibiting high residual stress formations during PBF-LB/M were manufactured from the nickel-based superalloy Inconel 718. Afterwards, the stresses were measured by means of neutron diffraction. The results provided the validation data for a subsequent finite element simulation, representing the build-up process on a part-scale, in which the data evaluation was conducted in accordance with the measurements for a high comparability. A comparison between the simulation and the neutron diffraction results of all three specimens showed a very good agreement of the normal stresses in all three coordinate directions, both for tensile and compressive stresses. The obtained results highlight the validity of the applied simplified part-scale simulation. The latter can, therefore, be utilized to increase the process understanding of residual stress and crack formations. It can also be used to enable process parameter modifications or geometry adaptions, aiming at a first-time-right additive manufacturing. UR - https://doi.org/10.1016/j.engfracmech.2025.111713 Y1 - 2025 UR - https://doi.org/10.1016/j.engfracmech.2025.111713 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-65712 SN - 0013-7944 VL - 2026 IS - 331 PB - Elsevier CY - Kidlington ER - TY - JOUR A1 - Mehta, Kedar A1 - Betz, Florian T1 - Agri-photovoltaics in India: Geospatial suitability for sustainable water–energy–food nexus solutions JF - Energy for Sustainable Development UR - https://doi.org/10.1016/j.esd.2025.101915 Y1 - 2025 UR - https://doi.org/10.1016/j.esd.2025.101915 SN - 2352-4669 VL - 2026 IS - 91 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Gleissner, Christian A1 - Kotonski, Julia T1 - Crystallographic groups and Calabi-Yau 3-folds of type II0 JF - The Asian Journal of Mathematics UR - https://dx.doi.org/10.4310/AJM.251216034253 Y1 - 2025 UR - https://dx.doi.org/10.4310/AJM.251216034253 SN - 1945-0036 VL - 29 IS - 4 SP - 517 EP - 534 PB - International Press of Boston CY - Somerville ER - TY - JOUR A1 - Bienert, Jörg A1 - Regnet, Simon T1 - Stability Analysis for an Ultra-Lightweight Glider Airplane with Electric Driven Two-Blade Propeller JF - Vibration N2 - Safety is the most important requirement in flight operations. This also affects the application for an extreme lightweight glider in this paper. Essential properties are the target weight below 120 kgand the electric propulsion. The unsymmetric inertia from the two-blade propeller at the rear in combination with the light and flexible aluminium tube support makes it necessary to investigate the risk of mechanical instability. Starting from the equations of motion, the time-variant system matrices are set up. The simulation of Floquet multiplier and Hill’s hyper-eigenvalue problem provide the necessary information about the system stability. The conclusion is that the potential instability due to structural damping in the observed system can be avoided in the range of operation. The damping, experimentally determined by approximately 2%, is sufficient. UR - https://doi.org/10.3390/vibration9010003 Y1 - 2025 UR - https://doi.org/10.3390/vibration9010003 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-65640 SN - 2571-631X VL - 9 IS - 1 PB - MDPI CY - Basel ER - TY - JOUR A1 - Gregor, Markus A1 - Bauder, Maximilian A1 - Kirsten Vidal de Oliveira, Aline A1 - Mast, Pascal A1 - Rüther, Ricardo A1 - Schweiger, Hans-Georg T1 - Approaches for Lifetime Prediction of Vehicle Traction Battery Systems During a Technical Inspection: A Systematic Review JF - World Electric Vehicle Journal N2 - Creating trust in society for new technologies, such as a new types of powertrains, and making them marketable requires transparent, neutral, and independent technical verification. This is crucial for the acceptance and success of electrified vehicles in the used car markets. A key component of electric vehicles is the traction battery, whose current and future condition, particularly regarding aging, determines its residual value and safe operation. This review aims to identify and evaluate methods for predicting the lifetime of onboard traction batteries, focusing on their applicability in technical inspections. A systematic literature and patent review was conducted using targeted keywords, yielding 22 patents and 633 publications. From these, 150 distinct lifetime prediction methods were extracted and categorized into a four-level mind map. These methods are summarized, cited, and structured in detailed tables. The relationships between approaches are explained to clarify the current research landscape. Long Short-Term Memory, Convolutional Neural Networks, and Particle Filters were identified as the most frequently used techniques. However, no methods were found suitable for predicting the lifetime of traction batteries during technical vehicle inspections, which operate under short test durations, limited data access, and diverse real-world operating conditions. Most studies focused on cell-level testing and did not address complete battery systems in operational vehicles. This gap highlights the need for applied research and the development of practical methods to support battery assessment in real-world conditions. Advancing this field is essential to foster confidence in battery systems and enable a sustainable transition to electromobility. UR - https://doi.org/10.3390/wevj17010003 Y1 - 2025 UR - https://doi.org/10.3390/wevj17010003 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-65631 SN - 2032-6653 VL - 17 IS - 1 PB - MDPI CY - Basel ER - TY - JOUR A1 - Haryanto, Aditya A1 - Vaculin, Ondrej T1 - YoFlow Method for Scenario Based Automatic Accident Detection JF - IEEE Open Journal of Intelligent Transportation Systems N2 - Recent advances in sensor and computing technologies have enabled road side units (RSUs) to not only monitor traffic flow but also process data in real time to improve road safety. However, leveraging RSUs for proactive accident detection remains a challenging and underexplored task, partly due to the lack of diverse accident data. To address this, this study proposes two key contributions: (i) a scenario-based synthetic data generation framework, and (ii) YoFlow, a novel system for vehicle-tovehicle accident detection from a simulated RSU camera perspective. The proposed framework leverages the PEGASUS method for scenario generation strategy and BeamNG.tech for generating synthetic traffic videos. This approach led to the development of the SB-SIF dataset, which includes five representative intersection crash scenarios derived from German accident data. The SB-SIF dataset contains 914 crash videos, 123 near-miss events, and 924 normal traffic instances and is publicly available at: https://doi.org/10.5281/zenodo.15267252. The proposed YoFlow system identifies accidents by analyzing temporal variations in vehicle speed vectors, using YOLO for vehicle classification and CUDA-accelerated dense optical flow to capture abrupt motion changes. The extracted features are processed and classified using an XGBoost model, achieving 94% recall and 90% precision in accident detection. UR - https://doi.org/10.1109/OJITS.2025.3639557 KW - accident detection KW - traffic accident KW - surveillance camera KW - optical flow KW - traffic scenarios Y1 - 2025 UR - https://doi.org/10.1109/OJITS.2025.3639557 SN - 2687-7813 VL - 7 SP - 61 EP - 73 PB - IEEE CY - New York ER - TY - JOUR A1 - Mehta, Kedar A1 - Lwakatare, Bertha A1 - Zörner, Wilfried A1 - Ehrenwirth, Mathias T1 - Mini-grid performance in Sub-Saharan Africa: case studies from Tsumkwe and Gam, Namibia JF - Sustainable Energy Research N2 - This paper investigates the performance analysis and operational challenges of mini-grids in Sub-Saharan Africa, focusing on the Tsumkwe and Gam mini-grids, the only officially recognized mini-grids in Namibia. The study addresses a critical gap in understanding mini-grid efficiency, technical difficulties, and future potential. The key research questions focus on assessing mini-grid performance, identifying technical and operational challenges, quantifying the relationship between electricity demand and supply, and providing recommendations for enhancing rural electrification through mini-grids. These insights are crucial for evaluating the effectiveness of mini-grids in the African context and understanding their role in advancing rural electrification. By using a mixed-method approach, the research combines quantitative and qualitative data to offer a comprehensive analysis of these two mini-grid systems of Namibia. The data collected from 2017 to 2022 include metrics on energy supply, consumption, photovoltaic generation, community load, and meteorological conditions. Qualitative insights were gathered through field visits, surveys, and interviews with mini-grid operators, allowing for a thorough examination of community perspectives, operational issues, and technical performance. The findings reveal that the Tsumkwe mini-grid has seen a decline in efficiency due to maintenance problems and battery overheating, while the Gam mini-grid, initially oversized, now struggles with increased demand and new connections. This study provides the first detailed technical insights, identifies consumer archetypes, and evaluates the energy dynamics of mini-grids in Namibia. Recommendations include improved maintenance protocols, advanced battery management, and enhanced data monitoring. By analyzing Tsumkwe and Gam, this paper offers valuable lessons for mini-grid development in Sub-Saharan Africa, stressing the need for continuous evaluation and strategic improvements to achieve sustainable rural electrification. UR - https://doi.org/10.1186/s40807-025-00174-y Y1 - 2025 UR - https://doi.org/10.1186/s40807-025-00174-y UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-65316 SN - 2731-9237 VL - 12 IS - 1 PB - SpringerOpen CY - Singapore ER - TY - JOUR A1 - Mehta, Kedar A1 - Jain, Rushabh Bansilal A1 - Zörner, Wilfried T1 - Agrivoltaics Around the World: Potential, Technology, Crops and Policies to Address the Energy–Agriculture Nexus for Sustainable and Climate-Resilient Land Use JF - Energies N2 - The urgent pursuit of climate-resilient agriculture and clean energy systems, central to the Energy–Agriculture Nexus and the UN Sustainable Development Goals, has accelerated global interest in agrivoltaic (Agri-PV) technologies. This paper presents a global systematic review and meta-analysis of 160 peer-reviewed studies, structured through a five-stage thematic synthesis: (1) mapping global and regional Agri-PV deployment and potential, (2) analyzing system design and modeling methodologies, (3) evaluating crop suitability under partial shading, (4) reviewing enabling policies and regulatory frameworks, and (5) assessing techno-economic feasibility and investment barriers. Results reveal that Europe and Asia lead Agri-PV development, driven by incentive-based policies and national tenders, while limited regulatory clarity and high capital costs constrain wider adoption. Despite technological progress, no integrated model fully captures the coupled energy, water, and crop dynamics essential for holistic assessment. Strengthening economic valuation, policy coherence, and standardized modeling approaches will be critical to scale Agri-PV systems as a cornerstone of sustainable and climate-resilient land use. UR - https://doi.org/10.3390/en18246417 Y1 - 2025 UR - https://doi.org/10.3390/en18246417 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-65288 SN - 1996-1073 VL - 18 IS - 24 PB - MDPI CY - Basel ER - TY - JOUR A1 - Meintrup, David A1 - Singer, Peter T1 - A Friendly Guide to the Real Exponential Function JF - The American Mathematical Monthly N2 - We propose an elementary introduction to the real exponential function of Leonhard Euler that combines ideas of Felix Klein and Adolf Hurwitz and uses an approximation of the primitive of the hyperbola. In this way, we can avoid the difficulties of common approaches yet still obtain classical results. UR - https://doi.org/10.1080/00029890.2025.2554556 Y1 - 2025 UR - https://doi.org/10.1080/00029890.2025.2554556 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-65107 SN - 1930-0972 VL - 132 IS - 10 SP - 1043 EP - 1047 PB - Taylor & Francis CY - London ER - TY - JOUR A1 - Schwan, Hannes A1 - Mohan, Nihesh A1 - Schmid, Maximilian A1 - Saha, Rocky Kumar A1 - Klassen, Holger A1 - Müller, Klaus A1 - Elger, Gordon T1 - Sintering for High Power Optoelectronic Devices JF - Micromachines N2 - Residual-free eutectic Au80Sn20 soldering is still the dominant assembly technology for optoelectronic devices such as high-power lasers, LEDs, and photodiodes. Due to the high cost of gold, alternatives are desirable. This paper investigates the thermal performance of copper-based sintering for optoelectronic submodules on first and second level to obtain thermally efficient thin bondlines. Sintered interconnects obtained by a new particle-free copper ink, based on complexed copper salt, are compared with copper flake and silver nanoparticle sintered interconnects and benchmarked against AuSn solder interconnects. The copper ink is dispensed and predried at 130 °C to facilitate in situ generation of Cu nanoparticles by thermal decomposition of the metal salt before sintering. Submounts are then sintered at 275 °C for 15 min under nitrogen with 30 MPa pressure, forming uniform 2–5 µm copper layers achieving shear strengths above 31 MPa. Unpackaged LEDs are bonded on first level using the copper ink but applying only 10 MPa to avoid damaging the semiconductor dies. Thermal performance is evaluated via transient thermal analysis. Results show that copper ink interfaces approach the performance of thin AuSn joints and match silver interconnects at second level. However, at first level, AuSn and sintered interconnects of commercial silver and copper pastes remained superior due to the relative inhomogeneous thickness of the thin Cu copper layer after predrying, requiring higher bonding pressure to equalize surface inhomogeneities. UR - https://doi.org/10.3390/mi16101164 Y1 - 2025 UR - https://doi.org/10.3390/mi16101164 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64984 SN - 2072-666X VL - 16 IS - 10 PB - MDPI CY - Basel ER - TY - JOUR A1 - Zippelius, Andreas A1 - Mohd, Zubair Akhtar A1 - Schmid, Maximilian A1 - Elger, Gordon T1 - Comparison of different Input data for the prediction of LED solder joints using Artificial Neural Networks JF - IEEE Transactions on Device and Materials Reliability N2 - Scarcity of raw data is a major issue for applying data driven methods to reliability prediction, so making the best use of what is available is critical. This paper studies how different aspects of measurement data can be used best. Specifically, the reliability of the solder joint of LED packages is predicted based on Transient Thermal Analysis and Scanning Acoustic Microscopy data from a large measurement campaign. The impact of using full temporal information vs measurements at individual datapoints is investigated as well as the benefit of including the SAM data, and different ways of presenting the TTA information, either as a full curve or as expert-selected features. The impact of formatting categorical information of solder and LED package type as one-hot encoding or using embeddings is considered. Finally, the performance for Pass/Fail predictions of the best identified model with a model architecture developed on a similar dataset is compared. We identified the most relevant sources of information for predicting the behavior and the best format for the data, which helps guide the choice for future model architectures. UR - https://doi.org/10.1109/TDMR.2025.3633876 Y1 - 2025 UR - https://doi.org/10.1109/TDMR.2025.3633876 SN - 1558-2574 PB - IEEE CY - New York ER - TY - JOUR A1 - Rouegui, Meryem A1 - Bellabair, Hind A1 - El Asli, Abdelghani A1 - Amar, Amine A1 - Zörner, Wilfried A1 - Rachidi, Fouad A1 - Lghoul, Rachid T1 - Bio-Methanization of Sheep Manure and Beet Waste in the Meknes–Fès Region, Morocco: Effects of Pretreatment and Machine Learning Applications for Biochemical Methane Potential Prediction JF - Recycling N2 - Sheep manure and beet waste (the uneatable leaf part of the beet) are promising feedstock for biogas production due to their abundance and organic richness. However, their high lignocellulosic content reduces anaerobic digestibility and controls methane yield. This study investigates the effect of various pretreatment strategies, namely physical, thermal, and combined physical–thermal methods, on the Biochemical Methane Potential (BMP) of sheep manure and beet waste. Batch anaerobic digestion experiments were conducted under mesophilic conditions, with BMP values recorded for each treatment. The highest BMP for sheep manure, 125 Nml CH4/g VS, was achieved using combined physical and thermal pretreatment. This approach enhanced methane production by 16%, 25%, and 60% compared to physical pretreatment (PP) alone, thermal pretreatment (TP) alone, and no pretreatment, respectively, while the one BMP for beet waste is 80 Nml CH4/g VS and obtained with thermal pretreatment. To predict BMP outcomes, three machine learning approaches are applied, namely Linear Regression (LM), Random Forest Regression (RFR), and Gradient Boosting Machine (GBM), using digestion time (N days), total solids (Ts), volatile solids (Vs), pretreatment type, and biomass type. The variance analysis confirmed that the interaction between pretreatment and biomass type significantly improved model performance. While diagnostic checks revealed non-linear patterns limiting the linear model, ensemble methods achieved stronger results. The RFR model explained 79.5% of the variance with a Root Mean Square Error (RMSE) of about 15.7, whereas the GBM model achieved the lowest RMSE of 5.05. GBM captures complex non-linear interactions. In addition, variable importance analyses identified digestion time, solid content, and pretreatment as the most influential factors for methane yield, with the combined chemical and physical pretreatment producing the highest biogas outputs. These findings underscore the potential of advanced machine learning models, particularly GBM (Gradient Boosting Machine), for optimizing anaerobic digestion strategies and maximizing biogas recovery from sheep manure and beet waste. UR - https://doi.org/10.3390/recycling10060213 Y1 - 2025 UR - https://doi.org/10.3390/recycling10060213 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64862 SN - 2313-4321 VL - 10 IS - 6 PB - MDPI CY - Basel ER - TY - JOUR A1 - Pandey, Amit A1 - Kühn, Stephan A1 - Weis, Alexander A1 - Wunderle, Bernhard A1 - Elger, Gordon T1 - Evaluating optical performance degradation of automotive cameras under accelerated aging JF - Optics and Lasers in Engineering N2 - Automotive cameras are subject to environmental stress, which degrades performance by reducing image sharpness. To qualify for automotive use and to ensure that the cameras maintain sharpness according to the hard requirements of end-of-line testing, cameras have to undergo standardized accelerated aging tests. These tests are performed to demonstrate reliability and functional safety over lifetime. Few studies have been published that demonstrate how aging contributes to the degradation of optical performance. This study addresses this gap by combining accelerated thermal aging with sharpness tracking to investigate degradation over time. To quantify sharpness degradation, six series-production cameras were subjected to accelerated thermal aging between −40◦𝐶 and +85◦𝐶. Each camera underwent 2000 aging cycles, equivalent to 80% of their lifetime based on the Coffin-Manson model of the LV124 standard. Sharpness was measured by calculating the Spatial Frequency Response (SFR) from images captured of a double-cross reticle projected by a virtual object generator with three illumination wavelengths (625nm, 520nm, and 470nm). The change in sharpness was evaluated with SFR50 and SFR at 60 line pairs per millimeter (SFR@60). During the first 250 cycles, a wear-in effect was observed, where sharpness increased before leveling off, as seen previously. The results also indicated a slow decline in sharpness showing long-term stability. Analysis indicated that before aging, the best focal plane was located closer to the focal position of the red wavelength, which lies furthest from the objective. By the end of the aging process, the best focal plane had shifted toward the focal position of the blue wavelength, which is located closer to the objective. This suggests a forward movement of the image sensor due to aging. Even after 2000 cycles, all cameras maintained an SFR@60 above 0.5. A Random Forest regression model was trained to predict the age based on the SFR curves, achieving a mean absolute error of 126 cycles and a 𝑅2 score of 0.96. UR - https://doi.org/10.1016/j.optlaseng.2025.109396 Y1 - 2025 UR - https://doi.org/10.1016/j.optlaseng.2025.109396 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64821 SN - 1873-0302 VL - 2026 IS - 196 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kaupp, Sabine A1 - Huber, Florian T1 - Does mental model similarity equal innovation team performance? JF - Innovation & Management Review N2 - Purpose This paper addresses challenges and opportunities of interdisciplinary teamwork in innovation management, focusing on how team mental models (TMMs) can foster more effective collaboration among team members from diverse backgrounds. The research examines the relationship between TMM similarity and team performance in interdisciplinary innovation teams. Design/methodology/approach An exploratory study was conducted with 55 participants across 15 teams. TMM similarity was measured by analyzing team interactions using a web-based interface that facilitated contrasted comparison ratings. These ratings were first processed into individual graphs via a shortest-node-finding pathfinder algorithm, then compared. Subject matter experts evaluated team performance. Findings The results reveal a significant positive correlation between TMM similarity and team performance in interdisciplinary innovation teams, suggesting that greater alignment in team members' mental models enhances overall innovation project performance. Research limitations/implications Although the academic programs sampled replicate the environment, challenges and various other aspects of innovation projects, they can only be considered proxies for innovation projects within real organizations. Further research within professional environments, using a larger sample, is recommended. Practical implications The findings highlight the value of assessing and fostering TMM similarity to improve teamwork and performance in interdisciplinary innovation projects. The interface and code used are publicly available to encourage their implementation in organizations. Originality/value This research provides novel insights into the application of TMMs within interdisciplinary innovation teams, extending the concept beyond its traditional use in unidisciplinary and structured task settings. UR - https://doi.org/10.1108/INMR-09-2023-0152 Y1 - 2025 UR - https://doi.org/10.1108/INMR-09-2023-0152 SN - 2515-8961 VL - 22 IS - 4 SP - 280 EP - 292 PB - Emerald CY - Bingley ER - TY - JOUR A1 - Peintner, Jakob A1 - Manger, Carina A1 - Berger, Melanie A1 - Riener, Andreas T1 - Balancing transparency and control: The impact of AI explanation detail on user perception in automated vehicles JF - Transportation Research Interdisciplinary Perspectives N2 - As automated vehicle technology advances, explainable AI has emerged as a critical tool to enable users to understand and predict the behavior of AI systems, particularly in safety-critical applications such as automated driving. However, increased transparency in AI explanations may inadvertently contribute to an “illusion of control”, a cognitive bias in which drivers overestimate their influence or understanding of the AI’s actions. We aim to better understand how the level of detail in AI explanations affects users of automated vehicles. In a virtual reality study, N = 44 participants experienced different explanation levels (low, medium, high) in an automated ride (SAE L4) compared to a baseline condition with no explanations. The results show a significant improvement in participants’ user experience, acceptance, and explanation satisfaction, with more detailed explanations. Our findings also indicate that as AI explanations become more detailed, users’ perceived level of control increases significantly, although this perception does not correlate with actual control capabilities. At the same time, it decreased their desire to take control, indicating users’ susceptibility to the ’illusion of control’ bias in the context of automated driving. Overall, this suggests that the design of explanation interfaces should strive for a balanced level of detail that promotes AI transparency without causing cognitive overload. At the same time, explainable AI can be utilized to decrease users’ desire to intervene in the AI’s actions. UR - https://doi.org/10.1016/j.trip.2025.101742 Y1 - 2025 UR - https://doi.org/10.1016/j.trip.2025.101742 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64740 SN - 2590-1982 VL - 2025 IS - 34 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Wan, Lei A1 - Zhao, Jianxin A1 - Wiedholz, Andreas A1 - Bied, Manuel A1 - Martinez de Lucena, Mateus A1 - Jagtap, Abhishek Dinkar A1 - Festag, Andreas A1 - Fröhlich, Antônio A1 - Keen, Hannan Ejaz A1 - Vinel, Alexey T1 - A Systematic Literature Review on Vehicular Collaborative Perception—A Computer Vision Perspective JF - IEEE Transactions on Intelligent Transportation Systems N2 - The effectiveness of autonomous vehicles relies on reliable perception capabilities. Despite significant advancements in artificial intelligence and sensor fusion technologies, current single-vehicle perception systems continue to encounter limitations, notably visual occlusions and limited long-range detection capabilities. Collaborative Perception (CP), enabled by Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication, has emerged as a promising solution to mitigate these issues and enhance the reliability of autonomous systems. Beyond advancements in communication, the computer vision community is increasingly focusing on improving vehicular perception through collaborative approaches. However, a systematic literature review that thoroughly examines existing work and reduces subjective bias is still lacking. Such a systematic approach helps identify research gaps, recognize common trends across studies, and inform future research directions. In response, this study follows the PRISMA 2020 guidelines and includes 106 peer-reviewed articles. These publications are analyzed based on modalities, collaboration schemes, and key perception tasks. Through a comparative analysis, this review illustrates how different methods address practical issues such as pose errors, temporal latency, communication constraints, domain shifts, heterogeneity, and adversarial attacks. Furthermore, it critically examines evaluation methodologies, highlighting a misalignment between current metrics and CP’s fundamental objectives. By delving into all relevant topics in-depth, this review offers valuable insights into challenges, opportunities, and risks, serving as a reference for advancing research in vehicular collaborative perception. UR - https://doi.org/10.1109/TITS.2025.3631141 Y1 - 2025 UR - https://doi.org/10.1109/TITS.2025.3631141 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64708 SN - 1558-0016 VL - 27 IS - 1 SP - 81 EP - 118 PB - IEEE CY - New York ER - TY - JOUR A1 - Agostinelli, Simone A1 - Asatiani, Aleksandre A1 - Axmann, Bernhard A1 - Hannibal, Glenda A1 - Modlinski, Artur ED - del-Río-Ortega, Adela ED - Marrella, Andrea ED - Reijers, Hajo A. ED - Wilde, Adriana T1 - Trust Calibration for RPA JF - Dagstuhl Reports N2 - This working group focused on foundational issues of trust in RPA: How we can conceptualize trust between users and software robots and specify it in a way that, eventually, we can measure that trust empirically. UR - https://doi.org/10.4230/DagRep.14.7.52 Y1 - 2025 UR - https://doi.org/10.4230/DagRep.14.7.52 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64681 SN - 2192-5283 VL - 14 IS - 7 SP - 61 EP - 64 PB - Schloss Dagstuhl CY - Dagstuhl ER - TY - JOUR A1 - Gleißner, Christian A1 - Kotonski, Julia T1 - The classification of rigid torus quotients with canonical singularities in dimension three JF - Rendiconti Lincei: Matematica e Applicazioni N2 - We provide a fine classification of rigid 3-dimensional torus quotients with isolated canonical singularities, up to biholomorphism and diffeomorphism. This complements the classification of Calabi–Yau 3-folds of type III0​, which are those quotients with Gorenstein singularities. UR - https://doi.org/10.4171/RLM/1070 Y1 - 2025 UR - https://doi.org/10.4171/RLM/1070 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64657 SN - 1720-0768 VL - 36 IS - 2 SP - 315 EP - 352 PB - EMS Press CY - Berlin ER - TY - JOUR A1 - Kaiser, Carolin A1 - Jungbluth, Michael A1 - Ulrichshofer, Anna A1 - Kames, Lucas A1 - Cato, Patrick T1 - How sponsored content affects consumer decisions in AI-powered retail JF - NIM Insights Y1 - 2025 UR - https://www.nim.org/forschung/uebersicht-forschungsprojekte/forschungsprojekt/how-sponsored-sontent-affects-consumer-decisions-in-ai-powered-retail SN - 2944-5981 VL - 7 SP - 26 EP - 29 PB - NIM CY - Nürnberg ER - TY - JOUR A1 - Jamadar, Mohammad I. A1 - Sekhar, Ravi A1 - Yada, Vijay Ramarao A1 - Rairikar, Sandeep D. A1 - Thipse, Sukrut T1 - Emission Testing of Flex Fuel Vehicles up to M100/E100: Upgradation of Existing Test Facility for Vehicles below 3.5-ton GVW for Testing Methanol or Ethanol Operated Vehicles JF - Journal Européen des Systèmes Automatisés​ N2 - This paper is focused on enhancing the existing dilute emission measurement system to accommodate the emission testing of vehicles operating with gasoline blends with methanol and ethanol, dedicated M100/E100 etc. India is moving towards achieving the E20 blend on the pan-country level by April 2025 with the initiations of NITI Aayog and exploring alternate fuels like 100% methanol and ethanol. Government of India is now focused on introducing the flex fuel vehicle (FFV) technology that supports the usage of higher ethanol blends. As per CMVR guidelines for M and N category vehicles with a gross vehicle weight less than 3,500 kg; a dilute emission measurement system is used to evaluate tailpipe pollutants and fuel economy. Most of the present emission systems are compatible with testing the vehicle till M15 and E20 blends. Beyond this percentage, usage of a test facility for M100, E100, and other flex-fuel vehicles, require certain modifications in existing test facility to maintain the precision and reliability of the results considering higher water content in exhaust and effect of condensation on emission measurement due to dilution. The modifications needed, implementation and their impact are experimentally briefed in the present paper. UR - https://doi.org/10.18280/jesa.580816 Y1 - 2025 UR - https://doi.org/10.18280/jesa.580816 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64502 SN - 2116-7087 VL - 58 IS - 8 SP - 1721 EP - 1732 PB - IIETA CY - Edmonton ER - TY - JOUR A1 - Chaturvedi, Pushpendra Kr. A1 - Kumar, Nand A1 - Toftum, Jørn A1 - Andersen, Rune Korsholm A1 - Lamba, Ravita A1 - Mehta, Kedar T1 - Exploring influential parameters affecting residential building energy use: advancing energy efficiency through machine learning JF - Clean Technologies and Environmental Policy UR - https://doi.org/10.1007/s10098-025-03301-x Y1 - 2025 UR - https://doi.org/10.1007/s10098-025-03301-x SN - 1618-9558 VL - 27 IS - 11 SP - 6975 EP - 6996 PB - Springer CY - Berlin ER - TY - JOUR A1 - Schuhmacher, Alexander A1 - Gassmann, Oliver A1 - Kwisda, Sebastian A1 - Kremer, Malte A1 - Hinder, Markus A1 - Hartl, Dominik T1 - The R&D productivity challenge: transforming the pharmaceutical ecosystem JF - Drug Discovery Today N2 - The persistent decline in pharmaceutical R&D productivity has been extensively analyzed and debated for over two decades, with profound implications for the structure and strategy of the pharmaceutical industry. This systemic challenge forced many leading companies to adapt their R&D models, influencing internal capabilities and external innovation strategies. In response, the industry has evolved into a complex, interdependent biopharmaceutical ecosystem encompassing large pharmaceutical corporations, biotech innovators and specialized service providers. Although R&D productivity affects all research-driven companies, its consequences are particularly pronounced for large pharmaceutical firms, because the scale and capital intensity of their R&D activities make productivity a crucial determinant of long-term competitiveness and sustainability. By contrast, other stakeholders are only partially adversely affected, whereas some can even obtain value from it. UR - https://doi.org/10.1016/j.drudis.2025.104494 Y1 - 2025 UR - https://doi.org/10.1016/j.drudis.2025.104494 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64218 SN - 1878-5832 VL - 30 IS - 11 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Schwertner, Stefan A1 - Buchberger, Tobias A1 - Diehl, Simon A1 - Ferg, Rebekka A1 - Hanzl, Christian A1 - Hartmann, Christoph A1 - Hölzle, Markus A1 - Kleiner, Jan A1 - Komsiyska, Lidiya A1 - Lewerenz, Meinert A1 - Liebhart, Bernhard A1 - Schmid, Michael A1 - Schneider, Dominik A1 - Scholz, Florian A1 - Speer, Sascha A1 - Stöttner, Julia A1 - Terbrack, Christoph A1 - Hinterberger, Michael A1 - Endisch, Christian T1 - Design and Implementation of an Intelligent Reconfigurable High-Voltage Battery System for Next-Generation Electric Vehicles JF - Batteries N2 - Battery system engineers face the challenge of balancing competing requirements regarding performance, maintainability, sustainability, safety, and cost—especially in the automotive industry. IBS potentially offer a solution with fewer trade-offs. They feature a battery management system with advanced sensing and data analysis capabilities that facilitate improved battery monitoring and operation. Reconfigurable energy storage units enable sophisticated operating strategies, including complete cell state control, full energy content utilization, and a measured response to faults. This article presents the design, development, and operation of a full-scale intelligent battery system prototype comprising 324 automotive lithium-ion cells with a nominal voltage of 400V. The system exhibits a modular single cell architecture and an advanced centralized battery management system. We detail the system architecture, hardware and software component design, and system integration. Initial tests demonstrate the battery’s operability, extended functionality, and enhanced safety. Our analysis shows that the additional losses introduced by reconfigurability are more than offset by the benefits of full energy utilization—even for new cells, with increasing advantage as aging progresses. The results underscore the potential of intelligent battery systems and motivate further research and development toward economic assessment and industrial adoption. UR - https://doi.org/10.3390/batteries11110424 Y1 - 2025 UR - https://doi.org/10.3390/batteries11110424 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64086 SN - 2313-0105 VL - 11 IS - 11 PB - MDPI CY - Basel ER - TY - JOUR A1 - Puget, Chloé A1 - Ganz, Jonathan A1 - Bertram, Christof A1 - Conrad, Thomas A1 - Baeblich, Malte A1 - Voss, Anne A1 - Landmann, Katharina A1 - Haake, Alexander F. H. A1 - Spree, Andreas A1 - Hartung, Svenja A1 - Aeschlimann, Leonore A1 - Soto, Sara A1 - de Brot, Simone A1 - Dettwiler, Martina A1 - Aupperle-Lellbach, Heike A1 - Bolfa, Pompei A1 - Bartel, Alexander A1 - Kiupel, Matti A1 - Breininger, Katharina A1 - Aubreville, Marc A1 - Klopfleisch, Robert T1 - Artificial intelligence predicts c-KIT exon 11 genotype by phenotype in canine cutaneous mast cell tumors: Can human observers learn it? JF - Veterinary Pathology N2 - Canine cutaneous mast cell tumors (ccMCTs) are frequent neoplasms with variable biological behaviors. Internal tandem duplication mutations in c-KIT exon 11 (c-KIT-11-ITD) are associated with poor prognosis but predict therapeutic response to tyrosine kinase inhibitors. In a previous work, deep learning algorithms managed to predict the presence of c-KIT-11-ITD on digitalized hematoxylin and eosin-stained histological slides (whole-slide images, WSIs) in up to 87% of cases, suggesting the existence of morphological features characterizing ccMCTs carrying c-KIT-11-ITD. This 3-stage blinded study aimed to identify morphological features indicative of c-KIT-11-ITD and to evaluate the ability of human observers to learn this task. 17 untrained pathologists first classified 8 WSIs and 200 image patches (highly relevant for algorithmic classification) of ccMCTs as either positive or negative for c-KIT-11-ITD. Second, they self-trained to recognize c-KIT-11-ITD by looking at the same WSIs and patches correctly sorted. Third, pathologists classified 15 new WSIs and 200 new patches according to c-KIT-11-ITD status. In addition, participants reported microscopic features they considered relevant for their decision. Without training, participants correctly classified the c-KIT-11-ITD status of 63%–88% of WSIs and 43%–55% of patches. With self-training, 25%–38% of WSIs and 55%–56% of patches were correctly classified. High cellular pleomorphism, anisokaryosis, and sparse cytoplasmic granulation were commonly suggested as features associated with c-KIT-11-ITD-positive ccMCTs, none of which showed reliable predictivity in a follow-up study. The results indicate that transfer of algorithmic skills to the human observer is difficult. A c-KIT-11-ITD-specific morphological feature remains to be extracted from the artificial intelligence model. UR - https://doi.org/10.1177/03009858251380284 Y1 - 2025 UR - https://doi.org/10.1177/03009858251380284 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63841 SN - 1544-2217 VL - 63 IS - 2 SP - 369 EP - 379 PB - Sage CY - London ER - TY - JOUR A1 - Manger, Carina A1 - Vogl, Annalena A1 - Riener, Andreas T1 - Cognitive Biases in User Interaction with Automated Vehicles: The Influence of Explainability and Mental Models JF - Applied Sciences N2 - To develop truly human-centered automated systems, it is essential to acknowledge that human reasoning is prone to systematic deviations from rational judgment, known as Cognitive Biases. The present study investigated such flawed reasoning in the context of automated driving. In a multi-step study with N = 34 participants, the occurrence of four Cognitive Biases was examined: Truthiness Effect, Automation Bias, Action Bias, and Illusory Control. Additionally, the study explored how the Explainability of the automation’s behavior and the driver’s Mental Model influenced the manifestation of these biases. The findings indicate a notable susceptibility to the Truthiness Effect and Illusory Control, although all biases appeared highly dependent on the specific driving context. Moreover, Explainability strongly impacted the perceived credibility of information and participants’ agreement with the system’s behavior. Given the exploratory nature of the study, this work aims to initiate a discussion on how Cognitive Biases shape human reasoning and decision-making in interactions with automated vehicles. Based on the results, several directions for future research are proposed: (1) investigation of additional cognitive biases, (2) analysis of biases across different levels of automation, (3) exploration of mitigation strategies versus deliberate use of biases, (4) examination of dynamic and context-dependent manifestations, and (5) validation in high-fidelity simulations or real-world settings. UR - https://doi.org/10.3390/app152011030 Y1 - 2025 UR - https://doi.org/10.3390/app152011030 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63831 SN - 2076-3417 VL - 15 IS - 20 PB - MDPI CY - Basel ER - TY - JOUR A1 - Santos, Cassiano A1 - Neto, Milad Kalume A1 - Kanieski, João Marcos A1 - Rufino Júnior, Carlos Antônio A1 - Schweiger, Hans-Georg A1 - Zanin, Hudson T1 - A multidimensional assessment of electrification in automotive powertrains: Technical, operational, and strategic perspectives JF - Results in Engineering N2 - Global transportation is undergoing a profound transformation, driven by the convergence of decarbonization targets and advances in electrification technologies. Electrification, ranging from mild Hybrid Electric Vehicles (mHEVs) to Battery Electric Vehicles (BEVs), represents the main technological path in the transition from internal combustion engines. This transition is inherently multidimensional, simultaneously reshaping vehicle design, manufacturing systems, supply chains, customer value, and environmental outcomes in interconnected ways. Each architecture, including mHEV, Hybrid Electric Vehicle (HEV), Plug-in Hybrid Electric Vehicle (PHEV), and BEV, presents different tradeoffs in these dimensions, requiring a structured framework for systematic comparison. To address this gap, this work details an integrated framework that systematically compares electrification pathways across five interrelated dimensions: vehicle concepts, research and development, manufacturing and logistics, customer experience, and environmental footprint. This framework culminates in a decision matrix that consolidates trade-offs into a practical SWOT based tool for strategic planning. UR - https://doi.org/10.1016/j.rineng.2025.107377 Y1 - 2025 UR - https://doi.org/10.1016/j.rineng.2025.107377 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63829 SN - 2590-1230 VL - 2025 IS - 28 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Theiler, Michael A1 - Nörpel, Felix A1 - Baumann, Alexander A1 - Endisch, Christian T1 - Thermal fault detection in battery systems using principal component analysis with adaptive thresholding JF - Journal of Energy Storage N2 - Lithium-ion cells pose serious safety risks when they enter a state with highly exothermic reactions known as thermal runaway. Because elevated temperature is the ultimate trigger for this failure mode, reliable and timely detection of abnormal cell temperature is critical. Early detection enables, user warning, fast emergency response, and provides the basis for effective active prevention strategies. In this work, we present an unsupervised data-driven approach that detects thermal faults by monitoring inter-cell voltage deviations. We apply principal component analysis (PCA) to capture systematic changes in voltage homogeneity that occur when a cell within a battery module heats abnormally. By systematically analyzing the effects of thermal stress on voltage homogeneity under varying operating conditions, we reveal requirements for a reliable detection method. Leveraging these insights, we introduce an adaptive thresholding mechanism. This novel approach significantly boosts the sensitivity to faults for a wide range of operating conditions while maintaining detection robustness. We validate the method through extensive experiments in which we externally heat a single cell within a module with the power of 1 W. Compared to both conventional linear PCA and nonlinear kernel PCA with a constant threshold, linear PCA with adaptive thresholding achieves a significantly better balance between sensitivity and robustness across the full range of test conditions. UR - https://doi.org/10.1016/j.est.2025.119101 Y1 - 2025 UR - https://doi.org/10.1016/j.est.2025.119101 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63603 SN - 2352-1538 VL - 2026 IS - 141, Part B PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Bhanderi, Savankumar A1 - Agrawal, Shiva A1 - Elger, Gordon T1 - Deep segmentation of 3+1D radar point cloud for real-time roadside traffic user detection JF - Scientific Reports N2 - Smart cities rely on intelligent infrastructure to enhance road safety, optimize traffic flow, and enable vehicle-to-infrastructure (V2I) communication. A key component of such infrastructure is an efficient and real-time perception system that accurately detects diverse traffic participants. Among various sensing modalities, automotive radar is one of the best choices due to its robust performance in adverse weather and low-light conditions. However, due to low spatial resolution, traditional clustering-based approaches for radar object detection often struggle with vulnerable road user detection and nearby object separation. Hence, this paper proposes a deep learning-based D radar point cloud clustering methodology tailored for smart infrastructure-based perception applications. This approach first performs semantic segmentation of the radar point cloud, followed by instance segmentation to generate well-formed clusters with class labels using a deep neural network. It also detects single-point objects that conventional methods often miss. The described approach is developed and experimented using a smart infrastructure-based sensor setup and it performs segmentation of the point cloud in real-time. Experimental results demonstrate 95.35% F1-macro score for semantic segmentation and 91.03% mean average precision (mAP) at an intersection over union (IoU) threshold of 0.5 for instance segmentation. Further, the complete pipeline operates at 43.61 frames per second with a memory requirement of less than 0.7 MB on the edge device (Nvidia Jetson AGX Orin). UR - https://doi.org/10.1038/s41598-025-23019-6 Y1 - 2025 UR - https://doi.org/10.1038/s41598-025-23019-6 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63458 SN - 2045-2322 VL - 15 PB - Springer Nature CY - London ER - TY - JOUR A1 - Yarza Navarro-Schär, Vanessa Gabriela A1 - Eller, Eric A1 - Schulz, Marco A1 - Lermer, Eva T1 - The trust–NPS correlation: The role of trust in promoting customer loyalty in Swiss financial institutions JF - PLOS ONE N2 - The Net Promoter Score (NPS) is a widely used key performance indicator (KPI) for measuring customer loyalty and guiding customer-centric strategies. While customer trust has been identified as an important influencing factor for NPS, existing research treats trust as a unidimensional construct, leaving the specific trust components that drive customer loyalty behaviors largely unexplored. This study addresses this theoretical gap by examining the relationship between various trust components and NPS in the financial services sector. A survey of 1,370 Swiss consumers assessed trust across ten theoretically-derived dimensions alongside their NPS ratings for five financial service companies. Employing median-split analysis, results demonstrate that high customer trust is associated with a significantly higher NPS (+36.5) compared to low trust (−68.6). Critically, quantile regression analysis revealed heterogeneous effects of trust components across different NPS distribution levels, with ability, experience, and reputation showing consistent positive effects across all quantiles. In contrast, joint interests and continuity emerged as relevant only at higher NPS quantiles, while reciprocity proved significant exclusively at the 25th percentile, demonstrating that distinct trust determinants become salient depending on customers’ advocacy levels. These findings challenge prevailing theoretical assumptions about customer trust’s homogeneous influence on customer loyalty, revealing instead a differentiated pattern of trust component effects. The study advances trust theory by demonstrating that trust dimensions not only vary in their influence on customer advocacy behaviors but also exhibit different effect patterns across the NPS distribution, contradicting assumptions of uniform trust impact on loyalty outcomes. The results indicate that NPS optimization requires strategic focus on specific trust dimensions, particularly those demonstrating consistent positive associations across quantile levels. This research contributes novel theoretical insights into the conditional trust-loyalty relationship while providing empirically-grounded guidance for customer-centric business strategies. UR - https://doi.org/10.1371/journal.pone.0334423 Y1 - 2025 UR - https://doi.org/10.1371/journal.pone.0334423 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63488 SN - 1932-6203 VL - 20 IS - 11 PB - PLOS CY - San Francisco ER - TY - JOUR A1 - Kolff, Maurice A1 - Himmels, Chantal A1 - Venrooij, Joost A1 - Parduzi, Arben A1 - Pool, Daan M. A1 - Riener, Andreas A1 - Mulder, Max T1 - Effect of motion mismatches on ratings of motion incongruence and simulator sickness in urban driving simulations JF - Transportation Research Part F: Traffic Psychology and Behaviour N2 - This paper investigates the effects of motion mismatches on simulator sickness and subjective ratings of the motion. In an open-loop driving simulator experiment, participants were driven through a recorded urban drive twelve times, in which mismatches were induced by manipulating the following three aspects in motion cueing: (i) mismatches in specific vehicle axes, (ii) mismatch types (scaling, missing, and false cues), and (iii) inconsistent scaling between different motion axes. Subjects (N=52) reported simulator sickness post-hoc (after each drive), as well as continuously during each drive, a first in simulator sickness research. Furthermore, subjective post-hoc motion incongruence ratings on the quality of the motion were extracted. Results show that longitudinal motion mismatches lead to the most simulator sickness and the highest ratings, followed by mismatches in lateral motion, then yaw rate. False cues induce the most sickness, followed by missing and then scaled motion. Inconsistent scaling between the axes has no significant effect. The continuous sickness ratings support that the occurrence and severity of simulator sickness are indeed related to mismatches in simulator motion of specific maneuvers. This paper contributes to an improved understanding of the relationship between simulator motion and sickness, allowing for more targeted motion cueing strategies to prevent and reduce sickness in driving simulators. These strategies may include the appropriate selection of the simulator, the motion cueing, and the sample of participants, following the presented results. UR - https://doi.org/10.1016/j.trf.2025.103370 Y1 - 2025 UR - https://doi.org/10.1016/j.trf.2025.103370 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63433 SN - 1873-5517 VL - 2025 IS - 115 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Doepfert, Markus A1 - Chu, Jiahe A1 - Hamacher, Thomas T1 - HAMLET: A modular agent-based Python framework for energy markets and systems JF - SoftwareX N2 - HAMLET is an agent-based Python framework designed to model the intricate interactions between energy markets, systems, and stakeholders. Its modular architecture provides a flexible and adaptable platform for analyzing complex energy systems. With numerous pre-built templates for energy system components, HAMLET enables researchers to focus on their area of expertise without the need to develop the surrounding ecosystem from scratch. By integrating market and system dynamics, HAMLET supports diverse applications, including market design optimization, grid management, policy refinement, and energy management system development. HAMLET delivers detailed insights into the technical, economic, and social impacts of new system designs, addressing a critical gap in energy system modeling. UR - https://doi.org/10.1016/j.softx.2025.102346 Y1 - 2025 UR - https://doi.org/10.1016/j.softx.2025.102346 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63428 SN - 2352-7110 VL - 2025 IS - 32 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Zepf, Andreas A1 - Gelner, Alexander A1 - Härtl, Martin A1 - Jaensch, Malte T1 - 3D-CFD-Based optimization of piston Geometry, injector nozzle Design, and injection strategy for the alternative diesel fuel Oxymethylene ether (OME) JF - Fuel N2 - Oxymethylene ethers (OMEs) represent a promising alternative to conventional diesel fuels, offering carbon–neutral mobility and soot-free combustion due to the absence of carbon–carbon bonds. This prevents the soot-NOx trade-off. Moreover, an OME-adapted and optimized combustion process offers the opportunity to improve engine efficiency while simultaneously reducing NOx emissions, thus addressing the existing efficiency-NOx trade-off. Realizing this potential necessitates tailoring the mixture preparation and combustion process to the unique characteristics of OME. This study explores the optimization of piston geometry, injector nozzle design, and injection strategies to leverage OME’s unique properties for improved engine performance. Using 3D-CFD simulations with the CONVERGE software, key parameters such as nozzle diameter, spray angle, and piston bowl shape are analyzed for their impact on efficiency and emissions. The results highlight that wider piston bowl geometries enhance indicated efficiency, while larger nozzle diameters improve combustion efficiency due to reduced combustion durations. Smaller spray angles effectively lower NOx emissions but introduce challenges such as piston wetting and localized temperature peaks. The study also confirms that pilot injection does not benefit OME operation, simplifying injection system requirements. These findings underline the need for tailored engine designs to fully exploit OME’s potential as a sustainable fuel. The proposed configurations pave the way for further experimental validation and practical implementation in internal combustion engines, contributing to the global transition toward low-carbon transport systems. UR - https://doi.org/10.1016/j.fuel.2025.136995 Y1 - 2025 UR - https://doi.org/10.1016/j.fuel.2025.136995 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63407 SN - 1873-7153 VL - 406 IS - Part B PB - Elsevier CY - New York ER - TY - JOUR A1 - Hinder, Markus A1 - Madesh, Nandhini A1 - Hartl, Dominik A1 - Schuhmacher, Alexander T1 - The Role of Data Monitoring Committees in drug research JF - Drug Discovery Today UR - https://doi.org/10.1016/j.drudis.2025.104474 Y1 - 2025 UR - https://doi.org/10.1016/j.drudis.2025.104474 SN - 1878-5832 VL - 30 IS - 10 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Beutenmüller, Frank A1 - Brostek, Lukas A1 - Doberstein, Christian A1 - Han, Longfei A1 - Kefferpütz, Klaus A1 - Obstbaum, Martin A1 - Pawlowski, Antonia A1 - Rössert, Christian A1 - Sas-Brunschier, Lucas A1 - Schön, Thilo A1 - Sichermann, Jörg T1 - DISRUPT - Decentralized Intelligent System for Road User Prediction and Tracking JF - SAE Technical Paper UR - https://doi.org/10.4271/2025-01-0294 Y1 - 2025 UR - https://doi.org/10.4271/2025-01-0294 SN - 0148-7191 SN - 2688-3627 PB - SAE CY - Warrendale ER - TY - JOUR A1 - Haiden, Michael A1 - Richter, Florian T1 - Autonomous weapons: considering the rights and interests of soldiers JF - Ethics and Information Technology N2 - The development of autonomous weapons systems (AWSs), which would make decisions on the battlefield without direct input from humans, has the potential to dramatically change the nature of war. Due to the revolutionary potential of these technologies, it is essential to discuss their moral implications. While the academic literature often highlights their morally problematic nature, with some proposing outright banning them, this paper highlights an important benefit of AWSs: protecting the lives, as well as the mental and physical health of soldiers. If militaries can avoid sending humans into dangerous situations or relieve drone operators from tasks that lead to lifelong trauma, this obviously appears morally desirable – especially in a world where many soldiers are still drafted against their will. Nonetheless, there are many arguments against AWSs. However, we show that although AWSs are potentially dangerous, criticisms apply equally to human soldiers and weapons steered by them. The combination of both claims makes a strong case against a ban on AWSs where it is possible. Instead, researchers should focus on mitigating their drawbacks and refining their benefits. UR - https://doi.org/10.1007/s10676-025-09859-w Y1 - 2025 UR - https://doi.org/10.1007/s10676-025-09859-w UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63280 SN - 1388-1957 SN - 1572-8439 VL - 27 IS - 4 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Graf, Michael A1 - Steinhauser, Dagmar A1 - Vaculin, Ondrej A1 - Brandmeier, Thomas T1 - Impact of Adverse Weather on Road Safety: A Survey of Test Methods for Enhancing Safety of Automated Vehicles and Sensor Robustness in Challenging Environmental Conditions JF - IEEE Access N2 - Adverse weather conditions can significantly affect environmental sensors and reduce the ability of automated vehicles to interpret the environment. This can lead to the failure of driving and safety functions. To validate and increase the robustness of these, several adverse weather test methods have been introduced in recent years. The survey first gives an overview of the current traffic and accident analysis with a focus on adverse weather influences to assess the most relevant weather phenomena. Overall, rain and glare are the statistically most important adverse weather phenomena in terms of accidents. Heavy fog is rare but can cause very serious accidents. In a second step, meteorological knowledge is incorporated and the key environmental indicators for the respective weather conditions are determined, particularly taking the environmental sensor characteristics into account. Both sets of information are then utilized to provide a qualified overview of simulative and physical test methods used to reproduce critical adverse weather situations. These methods are employed to investigate the disturbance effects of inclement weather on sensors and to test the robustness of automated vehicles. The paper reveals that various approaches are used to reproduce weather effects and that test methods, each with different advantages and disadvantages, have been developed to varying degrees depending on the type of the weather phenomena. Overall, this review integrates perspectives from road safety research, meteorology, and testing methodologies to provide new insights into the validation of automated driving systems in challenging weather conditions. UR - https://doi.org/10.1109/ACCESS.2025.3622501 Y1 - 2025 UR - https://doi.org/10.1109/ACCESS.2025.3622501 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63190 SN - 2169-3536 VL - 13 SP - 179817 EP - 179838 PB - IEEE CY - New York ER - TY - JOUR A1 - Kiran, Iqra A1 - Azzam, Mohamed A1 - Endisch, Christian A1 - Butt, Nauman Zafar A1 - Lewerenz, Meinert T1 - Evaluation of Calendar Aging in Cells with Graphite: Silicon Anode Using Float Current Analysis Under the Influence of Voltage Hysteresis JF - Journal of The Electrochemical Society N2 - This study investigates the calendar aging of lithium-ion batteries with graphite-silicon anodes using float current analysis. While float current analysis is already a proven method for assessing aging in cells with graphite-based anodes, the presence of silicon introduces additional complexities due to its voltage hysteresis. We address this by comparing the results for the scaling factor separately for charge and discharge. The scaling factor is initially derived from charge and discharge GITT measurements on fresh cells, including an aging-induced shift among both electrode curves. This approach enables quantification of SEI growth ISEI growth, and cathode lithiation current ICL bridging measured results for float currents with capacity loss rate. As a result, the scaling factor during charge delivered the most meaningful results regarding fitted aging currents. By extending the estimation method based on the Arrhenius equation across temperatures from 5 °C to 50 °C, our model is validated against measured float currents, improving the predictive accuracy of long-term aging trends in silicon-containing anodes. Electrochemical impedance spectroscopy provided further insights into degradation mechanisms, revealing a strong correlation between cathode lithiation by salt decomposition and resistance increase at high voltages (⩾4.15 V), confirmed by pulse tests at 100% SOC showing a sharp resistance increase at elevated voltages. UR - https://doi.org/10.1149/1945-7111/ae0fe8 Y1 - 2025 UR - https://doi.org/10.1149/1945-7111/ae0fe8 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63053 SN - 1945-7111 VL - 172 IS - 10 PB - IOP Publishing CY - Bristol ER - TY - JOUR A1 - Morales Torricos, Pablo A1 - Gallenberger, Andreas A1 - Droese, Dominik A1 - Kowal, Julia A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Analyzing the Impact of Electrolyte Motion Induced Salt Inhomogeneity Effect on Apparent Aging: Role of Current Rates and Temperature Effects in Accelerated Cyclic Aging Tests in Li-Ion Batteries JF - Batteries & Supercaps N2 - Accurate and rapid assessment of lithium-ion battery lifetime is essential for predicting remaining lifespan, enabling the selection of appropriate cells for specific applications and determining suitability for second-life use. However, accelerated cyclic aging tests may underestimate a cell's total lifespan due to exaggerated capacity fade that does not occur under real-world conditions. This increased capacity fade is primarily driven by electrolyte motion induced salt inhomogeneity (EMSI) and loss of homogeneity of lithium distribution (HLD). This study investigates the impact of varying charge and discharge currents on capacity loss during accelerated testing in compressed NMC-Gr pouch cells. Most of the capacity loss observed during cycling is fully recoverable after a resting period, with some cells regaining up to 81% of their lost capacity. Contrary to expectations, cells subjected to the highest cycling currents do not exhibit the greatest recoverable capacity loss. This phenomenon can be attributed to the interplay between current and temperature: While higher cycling currents exacerbate EMSI and HLD loss, they simultaneously elevate cell temperature, which mitigates EMSI by weakening polarization, enhancing electrolyte salt diffusion and homogenizing lithium distribution in the anode. Consequently, higher temperatures counteract HLD and EMSI-effect and therefore reduce apparent capacity loss. UR - https://doi.org/10.1002/batt.202500559 Y1 - 2025 UR - https://doi.org/10.1002/batt.202500559 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-62944 SN - 2566-6223 VL - 9 IS - 4 PB - Wiley CY - Weinheim ER - TY - JOUR A1 - Mieruch, Sebastian A1 - Kreps, Gastón A1 - Chouai, Mohamed A1 - Reimers, Felix A1 - Vredenborg, Myriel A1 - Rabe, Benjamin A1 - Tippenhauer, Sandra A1 - Behrendt, Axel T1 - SalaciaML-2-Arctic - a deep learning quality control algorithm for Arctic Ocean temperature and salinity data JF - Frontiers in Marine Science N2 - We have extended a classical quality control (QC) algorithm by integrating a deep learning neural network, resulting in SalaciaML-2-Arctic , a tool for automated QC of Arctic Ocean temperature and salinity profile data. The neural network component was trained on the Unified Database for Arctic and Subarctic Hydrography (UDASH), which has been quality-controlled and labeled by expert oceanographers. SalaciaML-2-Arctic successfully reproduces human expertise by correcting misclassifications made by the classical algorithm, reducing False Negatives (samples incorrectly classified as “bad”) by 96% for temperature and 99% for salinity. When used in combination with a visual post-QC by human experts, it achieves a workload reduction of approximately 60% for temperature and 85% for salinity. All code and data required to reproduce the analysis or apply the method to other datasets are openly available via PANGAEA and GitHub. Moreover, SalaciaML-2-Arctic is accessible as a browser-based application at https://mvre.autoqc.cloud.awi.de, enabling its use without software installation or programming knowledge. UR - https://doi.org/10.3389/fmars.2025.1661208 Y1 - 2025 UR - https://doi.org/10.3389/fmars.2025.1661208 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-62935 SN - 2296-7745 VL - 12 PB - Frontiers Media CY - Lausanne ER - TY - JOUR A1 - Mehta, Kedar A1 - Zörner, Wilfried T1 - Crop selection in Agri-PV: international review based strategic decision-making model JF - Solar Compass N2 - Agri-Photovoltaics (Agri-PV) is well known for its dual land use, integrating solar energy generation with agricultural production. This not only optimizes land use but also enhances food and energy security. Since Agri-PV is closely linked with crop cultivation, it is not solely about energy generation but also requires careful consideration of crop suitability within Agri-PV installations. Despite its significance, there is limited information available to guide decision-making for crop selection in Agri-PV systems. Selecting suitable crops remains a complex challenge, as factors such as shading tolerance, water requirements, and economic viability vary across different geographical and climatic conditions. This study develops a novel, review-based decision support model for crop selection in Agri-PV systems, synthesizing international research and case studies to provide a structured framework for decision-making. The model is based on 12 main crop typologies and key parameters such as water use, shading adaptability, crop yield/economic potential, and space requirements, derived from 117 research articles and case studies from 25 countries. By leveraging insights from successful international implementations, the model provides a practical framework for policymakers, farmers, and energy planners to enhance the sustainability and efficiency of Agri-PV projects. Findings suggest that crop selection strategies must align with regional climate conditions and PV system design to maximize synergies between energy and food production. High-value crops that require less space and have higher shade tolerance are more suitable for small-scale or decentralized Agri-PV systems. Future research should focus on advanced modeling techniques, AI-driven optimization, and real-world pilot studies to further refine decision-making in Agri-PV deployment. This study contributes to the growing body of knowledge on Agri-PV systems by providing a novel crop suitability matrix for effective decision-making. UR - https://doi.org/10.1016/j.solcom.2025.100143 Y1 - 2025 UR - https://doi.org/10.1016/j.solcom.2025.100143 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-62476 SN - 2772-9400 VL - 2025 IS - 16 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Prüfer, Kevin A1 - Weisser, Eduard A1 - Glushych, Viktor A1 - Tröber, Philipp A1 - Hartmann, Christoph A1 - Volk, Wolfram T1 - Seebeck Coefficient Modification via Extreme High-Speed Laser Material Deposition for Tool Materials JF - Procedia CIRP N2 - During blanking and cold forming of metals, thermoelectricity almost always occurs. While thermoelectric voltages can be used for temperature measurement via a tool-workpiece thermocouple, currents significantly influence adhesion formation. In both cases, the thermoelectric behavior of tool and workpiece materials, characterized by the Seebeck coefficient, plays a decisive role. While a large difference in coefficients increases the accuracy of temperature measurement, similar coefficients improve wear behavior. Currently, there is no method to adjust the Seebeck coefficient of materials without experimental procedures, which restricts the selection of tool materials based on their Seebeck coefficient. This study presents a novel approach for adjusting the Seebeck coefficient of tool steels using tailored coatings applied by extreme high-speed laser material deposition (EHLA). Therefore, an analysis was conducted to investigate the effects of chemical composition, substrate material and its heat treatment on the thermoelectric and mechanical behavior of the coating. The results demonstrate that targeted modification via tailored EHLA coatings is possible. UR - https://doi.org/10.1016/j.procir.2025.02.265 Y1 - 2025 UR - https://doi.org/10.1016/j.procir.2025.02.265 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-62460 SN - 2212-8271 VL - 2025 IS - 137 SP - 265 EP - 270 PB - Elsevier CY - Amsterdam ER -