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Numerical Analysis of Radar-Plasma-Signatures of a Sphere in a Mach 10 Hypersonic Wind Tunnel Flow
No full text8689The radar signature of Reentry Vehicles (RV) changes substantially during the atmospheric reentry. This alteration is caused by the existence of plasma. The prediction of the plasma state is complex and requires some critical assumptions which must be validated. This validation is usually performed by an iteration between Computational Fluid Dynamics (CFD) and wind tunnel experiments. This paper presents a feasibility study for radar measurements of reentry plasmas reproduced in hypersonic wind tunnels based on a combination of CFD and Electromagnetic (EM) Finite Difference Time Domain (FDTD) simulations
Packaging technologies and challenges towards 5G Integration of mm-wave components and silicon ICs
No full text7185A critical part of 5G communication systems design is the packaging technology, especially of front-end components, which has to support the high-frequency and high-power requirements. This technology plays a crucial role in enabling the miniaturization, integration, and reliability of the components. In this context, this article aims to provide a workflow of the packaging technology design for 5G communication systems within the BEYOND5 project, including its key components, integration challenges, and electromagnetic simulations. The design process of an interposer begins with the selection of material, which is determined by the tolerable losses at high frequencies. After choosing the material, the bump pitch on the front-end chip and the routing complexity on the interposer determines which stack-up will be used. Thermal management is also an important step in the design process, necessary for reliable power dissipation. Furthermore, RF simulations on the selected material are to evaluate the RF performance capabilities of the interposer. As a result, the critical signal traces on the interposer are well matched at 50 Í2 and arranged in order to offer low loss and reduced crosstalk (below -15 dB)
PowderMEMS - Generic Integration of Functional Three-Dimensional Microstructures on Wafer Level
No full text1825The novel ability to precisely integrate three-dimensional microstructures on substrate level with a thickness of up to several hundred micrometers from a wide range of materials and with custom geometries enables new possibilities for the design and manufacture of MEMS. However, fabrication of such voluminous microstructures on wafer level is challenging if not impossible with standard semiconductor processes. For this reason, a generic powder-based micromanufacturing technique called PowderMEMS was proposed earlier. This work presents recent advances of PowderMEMS for the wafer-level integration of micromagnets, porous membranes and structures with high mass density. The structures are discussed along their application in energy harvesting, magnetic field sensors, integrated inductors, and wafer-level chip-scale packaging
Unveiling the Synergy of Photocatalytic, Electrochemical, and Machine Learning Studies in CO2 Conversion to Renewable Fuels by the Z-Schemed MIL-53(Cr)/Ag2O/Bi2O3 Nanocomposite
No full text2332323341This study presents the development of a ternary composite based on metal–organic framework (MOF) MIL-53(Cr) co-doped with Ag2O and Bi2O3 to enhance photocatalytic CO2 reduction efficiency. The co-doping strategy improves light absorption, charge-carrier separation, and redox performance. Structural and morphological characterizations using SEM-EDS and PXRD confirm a uniform dopant distribution and successful composite formation. FTIR spectroscopy verifies the retention of functional groups, while UV-vis absorption and Tauc’s plot analysis indicate a band gap reduction from 3.66 to 3.29 eV. BET analysis reveals increased porosity and surface area, facilitating higher CO2 adsorption. Electrochemical studies, including LSV, CV, capacitance, ECSA, EIS, and Mott-Schottky analysis, demonstrate enhanced charge mobility and reduced interfacial resistance in the co-doped systems. The MIL-53(Cr)/Ag2O/Bi2O3 composite achieved a methanol production rate of 0.86 ± 0.03 mmol gcat-1; three replicates are studied under UV irradiation. Improved photocatalytic activity is attributed to a Z-scheme mechanism that promotes efficient electron-hole separation. In parallel, machine learning (ML) models developed using experimental data predict methanol yield, with Bayesian Ridge Regression showing the highest predictive accuracy (R2 = 0.800; RMSE = 1.27 × 10-7). SHAP analysis identifies the preparation temperature, band gap, CO2 inlet pressure, and dopant loading as key factors influencing yield. Statistical validation through boxplot and autocorrelation analyses confirms data consistency and independence. This integrated experimental and ML based approach offers a comprehensive understanding of structure-activity relationships and demonstrates the potential for AI-driven design of next-generation photocatalysts for sustainable CO2 capture and conversion.644
OpenMath-RDF: RDF encodings for OpenMath objects and Content Dictionaries
No full textThis paper presents RDF encodings for OpenMath objects and Content Dictionaries that allow mathematical objects and symbol definitions to be first-class citizens on the Web of Data
A double-layer MEMS actuator based on ferroelectric polarization inversion in AlScN Ein auf ferroelektrischer Polarisationsinversion in AlScN basierender Doppellagen MEMS-Aktuator
No full text426429This paper presents a piezoelectric double-layer stack based on permanent polarization inversion in ferroelectric Aluminum-Scandium-Nitride solid solution (AlScN). AlScN double layers with a high ScN content of 35% were produced via reactive co-sputtering. The effect of different structuring techniques (Wet vs. Dry) and deposition temperature were investigated in order to combine good reliability with high Sc content double layer systems that yield large piezoelectric displacement and force output. The resulting structure is compared to an AlScN single layer, Aluminum-Nitride and Lead-Zirconate-Titanate (PZT)
Diffusion MRI anomaly detection in glioma patients
No full textDiffusion-MRI (dMRI) measures molecular diffusion, which allows to characterize microstructural properties of the human brain. Gliomas strongly alter these microstructural properties. Delineation of brain tumors currently mainly relies on conventional MRI-techniques, which are, however, known to underestimate tumor volumes in diffusely infiltrating glioma. We hypothesized that dMRI is well suited for tumor delineation, and developed two different deep-learning approaches. The first diffusion-anomaly detection architecture is a denoising autoencoder, the second consists of a reconstruction and a discrimination network. Each model was exclusively trained on non-annotated dMRI of healthy subjects, and then applied on glioma patients’ data. To validate these models, a state-of-the-art supervised tumor segmentation network was modified to generate groundtruth tumor volumes based on structural MRI. Compared to groundtruth segmentations, a dice score of 0.67 ± 0.2 was obtained. Further inspecting mismatches between diffusion-anomalous regions and groundtruth segmentations revealed, that these colocalized with lesions delineated only later on in structural MRI follow-up data, which were not visible at the initial time of recording. Anomaly-detection methods are suitable for tumor delineation in dMRI acquisitions, and may further enhance brain-imaging analysis by detection of occult tumor infiltration in glioma patients, which could improve prognostication of disease evolution and tumor treatment strategies.13
Nonlinear Dynamics in Optical Waveguides with CVD-Grown 2D-Material Coating
No full textWe report a nonlinear photonics platform possessing a substantial second-order susceptibility and demonstrate the enhancement of second-harmonic generation in resonance with excitons. Here, exposed-core fibers, functionalized with MoS2 monolayers provide a long light-matter interaction scheme