Institute for Microelectronics and Microsystems

Silicon carbide (SiC) is the leading wide bandgap semiconductor for high-power and high-temperature electronics, but the high defect density still limits device performance. This study investigates how inclusions, Basal Plane Dislocations (BPDs), and Threading Screw Dislocations (TSDs) in 4H-SiC substrates affect epitaxial defect formation. Twenty 200 mm SiC wafers were analyzed after epitaxial growth in two industrial Chemical Vapor Deposition (CVD) reactors, one using Trichlorosilane/Ethylene (Reactor A) and the other Silane/Propane (Reactor B). Defects were characterized using Candela (KLA), Altair (KLA), XRTmicron LAB (Rigaku), SICA (Lasertec), and Crossbeam (ZEISS) dual-beam SEM system. Statistical correlation showed that the conversion rate of embedded particles decreases with particle depth and increases with particle size. Reactor A exhibited lower propagation rates, indicating better suppression of substrate-related defects. SEM/FIB-EDX analyses suggested that carbon inclusions generate pits while metallic inclusions induce triangular defects. Dislocation analysis confirmed a strong correlation between TSDs and BPDs with carrots and triangular defects. BPD conversion rates were estimated at about 98.3% (Reactor A) and 99.8% (Reactor B). These results emphasize the importance of substrate quality and buffer layer optimization to minimize defect propagation.

Abstract Terahertz (THz) science is widely recognized as the new frontier of applied electromagnetics, bridging the gap between microwave- and photonics-based applications. THz radiation, spanning frequencies over three orders of magnitude, namely from 0.1 THz to 10 THz, combines the advantages of a submillimetric wavelength with a centimeter scale penetration depth while featuring a non-ionizing character. This unique combination cannot be found elsewhere in the frequency spectrum, yet it exactly matches the demand of imaging applications in diverse fields such as material characterization, quality control, authentication, and cultural heritage. In this topical review, we specifically address the progress that THz imaging techniques based on time-domain spectroscopy (TDS) have made in the last three decades in the abovementioned contexts. Emphasis is given in their application to ( i ) the analysis of emerging materials (two-dimensional materials, phase-change materials, etc), ( i i ) industrial applications with high social impact (e.g. food safety, anticounterfeiting, etc), ( i i i ) cultural heritage studies (e.g. image reconstruction, conservation studies, etc). With a careful selection of works in the field, this topical review offers a bird’s eye view on the state of the art of THz-TDS in diverse application-oriented contexts, while addressing the reader towards the most promising research axes in the field of THz science.

A new hybrid nanocomposite for wastewater treatment was developed using hemp shiv fibers coated with ZnO nanolayers. Macro hemp shives were selected for their adsorption capacity and sustainability, while ZnO provided photocatalytic activity. Low-temperature atomic layer deposition (ALD) anchored ZnO nanolayers with controlled thicknesses (30, 70, 90 nm) onto hydroxyl groups on the hemp shives' surface. The effect of the ZnO thickness on adsorption and photocatalytic performance toward water organic pollutants was systematically investigated. Characterization included spectroscopic ellipsometry, scanning electron microscopy (SEM), transmission electron microscopy (TEM) with electron energy loss spectroscopy (EELS) and selected area electron diffraction (SAED), X-ray diffraction (XRD), thermogravimetric analysis (TGA), N 2 adsorption-desorption analysis, and Fourier transform infrared spectroscopy (FTIR). Methylene blue (MB) adsorption kinetics showed ZnO coatings partially shield the intrinsic adsorption aptitude of pure porous fibers' surface, with a shielding increasing with the ZnO thickness. Photocatalytic activity under UV irradiation was evaluated using three emergent water pollutants: MB dye, sodium dodecyl sulfate (SDS), and phenol. Hemp shives coated with a 30 nm-thick ZnO layer exhibited the highest degradation efficiencies for all the tested pollutants (about 70% after 4 h of light irradiation). Recycling tests confirmed material stability, with preserved ZnO coating and crystal structure after repeated use. Scavenger experiments indicated both radicals and photo-generated holes contribute to photocatalytic mechanism. The synergistic combination of adsorption and photocatalysis makes ZnO-coated hemp shives a promising and sustainable material for advanced wastewater treatment. • ZnO nanolayers were deposited on hemp shives via low-temperature ALD. • MB adsorption followed a pseudo-second order model, typical of chemisorption. • MB dye, SDS surfactant and phenol were efficiently degraded under UV irradiation. • Hybrid nanocomposite combined adsorption and photocatalytic pollutant degradation. • Sustainable ZnO/hemp shives offer a stable and eco-friendly solution for wastewater treatment.

ABSTRACT We implement a hybrid scheme that combines time‐dependent density functional theory (TDDFT) with quantum hydrodynamic theory (QHT). Using TDDFT, we capture the transition charge density of a p ‐nitroaniline (PNA) molecule, which translates into a realistic field distribution used to excite the QHT‐treated plasmonic systems. This facilitates the investigation of plasmonic quantum effects and the emitter's spatial extent in plasmon‐emitter interactions. As a result, we compare the emission properties of the PNA and a point dipole (PD) in plasmonic dimer gaps. Significant discrepancies are observed in both the oscillator strengths of the emission rates and the spectral positions of the prominent modes in the PNA‐ and PD‐based models when the dimer gap size is smaller than approximately 3.2 nm. These discrepancies are attributable to the spatial extent of the PNA molecule. The gap at which quantum‐tunneling‐induced emission quenching begins is observed to be three times larger in the PNA‐based system than in the PD‐based one. We study these phenomena by progressively introducing the quantum effects, starting from the local response approximation, moving to the nonlocal Thomas–Fermi hydrodynamic theory, and ultimately extending to the full QHT.

The proliferation of Unmanned Aerial Vehicles (UAVs) equipped with multispectral imaging sensors has revolutionized data collection in precision agriculture. These platforms provide high-resolution, temporally dense data crucial for monitoring crop health, optimizing resource management, and predicting yield. However, the development and validation of robust data-driven algorithms, from vegetation index analysis to complex deep learning models, are contingent upon the availability of high-quality, standardized, and publicly accessible datasets. This review systematically surveys and characterizes the current landscape of available datasets containing multispectral imagery acquired by UAVs in agricultural contexts. Following guidelines for reporting systematic reviews and meta-analyses (PRISMA methodology), 39 studies were selected and analyzed, categorizing them based on key attributes including spectral bands (e.g., RGB, Red Edge, Near-Infrared), spatial and temporal resolution, types of crops studied, presence of complementary ground-truth data (e.g., biomass, nitrogen content, yield maps), and the specific agricultural tasks they support (e.g., disease detection, weed mapping, water stress assessment). However, the review underscores a critical gap in standardization, with significant variability in data formats, annotation quality, and metadata completeness, which hampers reproducibility and comparative analysis. Furthermore, we identify a need for more datasets targeting specific challenges like early-stage disease identification and anomaly detection in complex crop canopies. Finally, we discuss future directions for the creation of more comprehensive, benchmark-ready open datasets that will be instrumental in accelerating research, fostering collaboration, and bridging the gap between algorithmic innovation and practical agricultural deployment. This work serves as a foundational guide for researchers and practitioners seeking suitable data for their work and contributes to the ongoing effort of standardizing open data practices in agricultural remote sensing.

Icy grain mantles play a crucial role in the chemistry of star-forming regions, allowing reactions that contribute to the formation of astrophysically complex organic molecules (COMs), including acetaldehyde (CH3CHO) and formamide (NH2CHO). Both compounds are also revealed in cometary comae. Laboratory experiments allowed us to reveal the formation of acetaldehyde and formamide in ices exposed to energetic sources, suggesting that the exposure of icy mantles and surfaces to Galactic cosmic rays (GCR) and solar charged particles triggers the formation of COMs. In this article, we provide data on the relevance of the initial ice composition on the formation and abundance of acetaldehyde and formamide. Furthermore, we aim to understand the time scales required in young star-forming regions to form both compounds through the ion-bombardment of icy grain mantles. We simulated the exposure of icy grain mantles to energetic charged particles in the laboratory. We produced a large set of icy mixtures comprising various molecules detected toward the solid phase of star-forming regions, including H2O, CO, CH3OH, CH4, NH3, and N2, and we exposed them to 200 keV H+ at 17 K simulating low-energy GCR. We followed the chemical evolution of ices by means of infrared spectroscopy. In the spectra, we looked for absorption features attributed to acetaldehyde (7.40 μm) and formamide (7.20 μm). We also provide estimations of their abundance as a function of the dose in the various investigated mixtures. The analysis revealed that the ice composition plays a primary role in both the destruction of the deposited species and the formation of new compounds. Water–methanol–ammonia mixtures are the most efficient in the formation of both COMs. The time scales required for their formation fall in the typical lifetimes of pre- and protostellar phases and strongly depend on the cosmic-ray ionization rate taken into account. We show that ices exposed to energetic ions can form both acetaldehyde and formamide. Abundances are found to be strongly related to the initial ice composition. We thus suggest that the bombardment of icy grain mantles by GCR is a relevant player in the formation of both compounds in the lifetime of pre- and protostellar objects.

Semitransparent perovskite photovoltaic (sPV) covers offer an attractive route for agrivoltaics, but their spectrally selective transmittance must be validated on plants cultivated under panel or in simulated conditions. Here, an AVA–MAPI perovskite module transmission profile was replicated using a programmable multi-channel LED platform and compared with a Reference McCree-adapted LED spectrum at identical photon flux density. Two lettuce cultivars (Lactuca sativa L.; ‘Canasta’ and ‘Trocadero’) were grown hydroponically in a light-sealed phytotron for 30 days (300 μmol m−2 s−1; 16/8 h photoperiod) under uniform temperature and humidity. Leaf gas exchange was quantified by fitting photosynthetic light-response curves, and plant performance was concurrently evaluated through growth metrics, biomass partitioning, and pigment-related traits (chlorophyll a/b, total carotenoids). The perovskite-emulated spectrum measurably reshaped net CO2 assimilation across the PAR domain—yielding higher AN at selected irradiances in post hoc contrasts—yet these physiological shifts did not translate into differences in leaf area, shoot or root biomass, or pigment concentrations—demonstrating spectral plasticity and agricultural compatibility of field-characterized perovskite transmission spectra. Overall, perovskite-emulated light sustained agronomically equivalent lettuce performance under moderate irradiance, supporting the feasibility of semitransparent perovskite PV covers, while underscoring the need for validation under natural sunlight.

The global incidence of cancer-related diseases and mortality continues to rise, making early and accurate diagnosis crucial for effective treatment. A key step in cancer treatment is the identification and removal of tumorous tissue, which is subsequently analyzed through pathological examinations. However, traditional pathology reports can take several weeks or even months to be processed. To expedite diagnosis, this study employs microwave measurement techniques to distinguish between healthy and cancerous colon tissue samples. The free-space measurement method is selected due to its suitability for evaluating sensitive pathological tissues. Measurements are conducted across 201 points within the 18-26 GHz frequency range, capturing the scattering parameters of various tissue types. Based on these measurements, four distinct datasets are created, incorporating features such as reflection coefficients, transmission coefficients, and frequency values. Three widely used classification algorithms-k-nearest neighbors (KNNs), artificial neural networks (ANNs), and Support Vector Machines (SVMs)-are evaluated for their performance on these datasets. The highest classification accuracy is achieved using the KNN algorithm on the dataset containing both reflection and transmission coefficients, along with measurement frequency. Bioelectromagnetics. 00:00-00, 2025. © 2025 © 2025 Bioelectromagnetics Society.

Earth-abundant zinc phosphide (Zn3P2) holds great promise as a photovoltaic absorber for thin-film applications, owing to its direct bandgap of ∼1.5 eV and its high absorption coefficient in the visible spectrum. Nonetheless, questions remain about the material’s stability in atmospheric environments, given its tendency to react with surrounding water vapor and oxygen. This work presents a comprehensive long-term study to understand how environmental exposure impacts high-quality, monocrystalline epitaxial zinc phosphide. Through a combination of various experimental techniques, such as ellipsometry, Raman spectroscopy, x-ray diffraction measurements, scanning transmission electron microscopy, energy dispersive x-ray spectroscopy, secondary ion mass spectroscopy, and x-ray photoelectron spectroscopy, we reveal that exposure to the atmosphere causes substantial oxidation of the thin film surface, penetrating several tens of nanometers into the bulk material. Finally, we show that degradation can be effectively prevented by applying a thin dielectric layer, such as Si3N4, or by simply storing the unprotected thin films under vacuum. These findings provide valuable guidelines for the proper handling of the material prior to device fabrication.