Search Results (362)

Decarbonizing the steel industry relies on a transition from carbon-intensive blast furnace technology to scrap-based secondary steelmaking using electric arc furnaces. This transition introduces tramp elements and leads to their gradual accumulation, which can significantly influence the functional properties of chemically sensitive steel grades. In this study, the combined impact of several tramp element contents on the phase transformations, microstructure and mechanical properties of a 0.3 wt.% C low-alloyed steel was investigated. To achieve this, a reference alloy was produced using the conventional blast furnace production route. It was then compared with two trial alloys, which contained intentionally elevated levels of tramp elements and were produced through an experimental melting route designed to simulate scrap-based electric arc furnace production. The experimental characterization included light optical and electron microscopy, electron back-scatter diffraction, in situ synchrotron high-energy X-ray diffraction coupled with dilatometry, and Vickers hardness testing. The results revealed the formation of displacive transformation products such as martensite and showed that austenite was retained in the tramp element-enriched trial alloys. The combination of solid solution strengthening and martensitic transformation led to a gradual increase in hardness. These findings underscore the critical role of tramp elements in determining the microstructural and mechanical response of steels produced from scrap-based feedstock. Full article

An analysis was conducted using AERONET Inversion Data at Thessaloniki and Leipzig stations. Aerosol type plays a vital role in determining their ability to act as CCN or INP, as properties such as chemical composition, morphology, and particle size influence their hygroscopic and ice-nucleating behavior. The CALIPSO mission provides global aerosol classification with vertical resolution by using backscatter intensity and depolarization ratio measurements. Aerosol typing from CALIPSO overpasses within 100 km of each selected AERONET station was used. Only pure aerosol cases (dust, polluted continental, smoke) were selected. This study combines AERONET-derived microphysical properties with CALIPSO aerosol classification to estimate particle number concentrations relevant for CCN and INP formation. The aim is to derive improved conversion factors for each aerosol type, enabling their application in future CCN and INP concentration profiles. Full article

Pure copper joints (PCJs) were fabricated using pinless friction stir spot welding (P-FSSW), a solid-state welding technique, to investigate the influence of plunge depth, rotational speed, and dwell time on PCJ performance. Thermal cycles under different welding parameters were recorded, while the microstructure at various locations within the welded zone was characterized using electron backscatter diffraction (EBSD). The microhardness and tensile–shear force (T-SF) of the PCJs were evaluated, and the fracture types together with fracture evolution were analyzed. The experimental results reveal that, under the combined effect of thermal cycles and mechanical stirring, subgrains in the welded zone transformed into recrystallized grains, whereas intense material flow contributed to an increased fraction of deformed grains. At the Hook region and the interface between the upper and lower sheets, grains were tightly bonded, resulting in effective metallurgical joining. Higher microhardness values were observed in the stir zone (SZ), whereas lower values appeared in the heat-affected zone beneath the interface. With increasing plunge depth, rotational speed, and dwell time, the T-SF of the PCJs first increased and then decreased, achieving a relatively high value at a plunge depth of 0.4 mm, a rotational speed of 1500 rpm, and a dwell time of 9 s. The fracture types of the PCJs were shear fracture and plug fracture, with the Hook region identified as the weakest zone. Full article

Optical frequency domain reflectometry (OFDR) is one of the key diagnostic tools for fiber optic components and circuits built on them. A low signal-to-noise ratio, resulting from the low intensity of backscattered signals, prevents the correct quantitative description of the medium parameters. Known methods of signal denoising, such as empirical mode decomposition, frequency filtering, and activation function dynamic averaging, make the signal smoother but introduce errors into its dynamic characteristics, changing the intensity of reflection peaks and distorting the backscattering level. We propose a method to reduce OFDR trace noise using elliptical arc fitting (EAF). The obtained results indicate that this algorithm efficiently processes both areas with and without contrasting back reflections, with zero distortion of Fresnel reflection peaks, and with zero attenuation error in regions without Fresnel reflections. At the same time, other methods distort reflection peaks by 14.2–42.6% and shift the correct level of Rayleigh scattering by 27.2–67.3%. Further work will be aimed at increasing the accuracy of the method and testing it with other types of data. Full article

Linpan ecosystems, distinct to western Sichuan, China, are integral to regional biodiversity and carbon cycling. However, comprehensive biomass estimation for these systems has not been thoroughly investigated. This study seeks to fill this gap by enhancing the accuracy and precision of biomass estimation in these ecologically vital landscapes through the application of multi-source remote sensing techniques, specifically by integrating the strengths of optical and radar remote sensing data. The focus of this research is on the forest biomass of Linpan, encompassing the tree layer, which includes the trunk, branches, leaves, and underground roots. Specifically, the research focused on the Linpan ecosystems in the Wenjiang District of western Sichuan, utilizing an integration of Sentinel-1 SAR, Sentinel-2 multispectral, and GF-2 high-resolution data for multi-source remote sensing-based biomass estimation. Through the preprocessing of these data, Pearson correlation analysis was conducted to identify variables significantly correlated with the forest biomass as determined by field surveys. Ultimately, 19 key modeling factors were selected, including band information, vegetation indices, texture features, and phenological characteristics. Subsequently, three algorithms—multiple stepwise regression (MSR), support vector machine (SVM), and random forest (RF)—were employed to model biomass across mixed-type, deciduous broadleaved, evergreen broadleaved, and bamboo Linpan. The key findings include the following: (1) Sentinel-2 spectral data and Sentinel-1 VH backscatter coefficients during the summer, combined with vegetation indices and texture features, were critical predictors, while phenological indices exhibited unique correlations with biomass. (2) Biomass displayed a marked north–south gradient, characterized by higher values in the south and lower values in the north, with a mean value of 161.97 t ha⁻¹, driven by dominant tree species distribution and management intensity. (3) The RF model demonstrated optimal performance in mixed-type Linpan (R² = 0.768), whereas the SVM was more suitable for bamboo Linpan (R² = 0.892). The research suggests that integrating multi-source remote sensing data significantly enhances Linpan biomass estimation accuracy, offering a robust framework to improve estimation precision. Full article

Streak cameras, essential for ultrahigh temporal resolution diagnostics in laser-driven inertial confinement fusion, underpin the streak tube imaging LiDAR (STIL) system—a flash LiDAR technology offering high spatiotemporal resolution, precise ranging, enhanced sensitivity, and wide field of view. This study establishes a theoretical model of the STIL system, with numerical simulations predicting limits of temporal and spatial resolutions of ~6 ps and 22.8 lp/mm, respectively. Dynamic simulations of laser backscatter signals from targets at varying depths demonstrate an optimal distance reconstruction accuracy of 98%. An experimental STIL platform was developed, with the key parameters calibrated as follows: scanning speed (16.78 ps/pixel), temporal resolution (14.47 ps), and central cathode spatial resolution (20 lp/mm). The system achieved target imaging through streak camera detection of azimuth-resolved intensity profiles, generating raw streak images. Feature extraction and neural network-based three-dimensional (3D) reconstruction algorithms enabled target reconstruction from the time-of-flight data of short laser pulses, achieving a minimum distance reconstruction error of 3.57%. Experimental results validate the capability of the system to detect fast, low-intensity optical signals while acquiring target range information, ultimately achieving high-frame-rate, high-resolution 3D imaging. These advancements position STIL technology as a promising solution for applications that require micron-scale depth discrimination under dynamic conditions. Full article

Peatland is a difficult landscape to map due to its challenging conditions. Remote sensing lends itself to mapping efforts, but can be hampered by common weather conditions in peatland locations. Sentinel-1 Synthetic Aperture Radar technology penetrates prevalent cloud cover. Techniques used to detect water surfaces using Sentinel-1 backscatter intensity have been applied in this study to delineate peatland land cover. This application was then extended with the aim of identifying the relative conditions of peatland within an area of interest. A peatland study site was selected at Winter Hill, near Bolton in Lancashire, UK, where a nationally significant wildfire occurred in 2018. Sentinel-1 imagery captured in the winter after the wildfire quite accurately reflected the fire damage extent. From further examination, it was found that in frozen conditions there are significant statistical differences between peatland surfaces and visually similar land cover, such as fields used for livestock grazing. Using the inter-quartile range of land cover samples to identify suitable backscatter thresholds, a surface map was produced depicting peatland of varying conditions and other land cover categories. This was compared with field visit photographic records to ascertain accuracy of representation. Further analysis detected correlation between backscatter and temperature for peatland surfaces that was not evident for other land cover classes. Steeper terrain can though affect this relationship. Conversely, no significant connection could be found in areas where surface water is most likely to be retained. Aggregating Sentinel-1 backscatter according to sub-catchment zones presented the potential to further delineate by condition within a peatland land cover sample. Therefore, the use of Sentinel-1 imagery in frozen conditions in context with terrain and sub-catchment level hydrological zoning provides the opportunity to aid environmental monitoring by delineating peatland from other land cover, identifying climate-change effects such as wildfires and assessing relative condition at scale. Full article

The effects of trace Ce on the microstructure and texture of non-oriented silicon steel during recrystallization and grain growth were examined using X-ray diffraction and electron backscatter diffraction. Additionally, this study focused on investigating the mechanisms by which trace Ce influences the evolution of the {114} <481> and γ-fiber textures. During the recrystallization process, as the recrystallization fraction of annealed sheets increased, the intensity of α-fiber texture decreased, while the intensities of α*-fiber and γ-fiber textures increased. The {111} <112> grains preferentially nucleated in the deformed γ-grains and their grain-boundary regions and tended to form a colony structure with a large amount of nucleation. In addition, the {100} <012> and {114} <481> grains mainly nucleated near the deformed α-grains, which were evenly distributed but found in relatively small quantities. The hindering effect of trace Ce on dislocation motion in cold-rolled sheets results in a 2–7% lower recrystallization ratio for the annealed sheets, compared to conventional annealed sheets. Trace Ce suppresses the nucleation and growth of γ-grains while creating opportunities for α*-grain nucleation. During grain growth, trace Ce reduces γ-grain-boundary migration rate in annealed sheets, providing growth space for {114} <418> grains. Consequently, the content of the corresponding {114} <481> texture increased by 6.4%, while the γ-fiber texture content decreased by 3.6%. Full article

This study describes a quite special and interesting atmospheric event characterized by the simultaneous presence of fresh and aged smoke layers. These peculiar conditions occurred on 16 July 2024 at the CNR-IMAA atmospheric observatory (CIAO) in Potenza (Italy), and represent an ideal case for the evaluation of the impact of aging and transport mechanisms on both the optical and microphysical properties of biomass burning aerosol. The fresh smoke was originated by a local wildfire about 2 km from the measurement site and observed about one hour after its ignition. The other smoke layer was due to a wide wildfire occurring in Canada that, according to backward trajectory analysis, traveled for about 5–6 days before reaching the observatory. Synergetic use of lidar, ceilometer, radar, and microwave radiometer measurements revealed that particles from the local wildfire, located at about 3 km a.s.l., acted as condensation nuclei for cloud formation as a result of high humidity concentrations at this altitude range. Optical characterization of the fresh smoke layer based on Raman lidar measurements provided lidar ratio (LR) values of 46 ± 4 sr and 34 ± 3 sr, at 355 and 532 nm, respectively. The particle linear depolarization ratio (PLDR) at 532 nm was 0.067 ± 0.002, while backscatter-related Ångström exponent (AEβ) values were 1.21 ± 0.03, 1.23 ± 0.03, and 1.22 ± 0.04 in the spectral ranges of 355–532 nm, 355–1064 nm and 532–1064 nm, respectively. Microphysical inversion caused by these intensive optical parameters indicates a low contribution of black carbon (BC) and, despite their small size, particles remained outside the ultrafine range. Moreover, a combined use of CIAO remote sensing and in situ instrumentation shows that the particle properties are affected by humidity variations, thus suggesting a marked particle hygroscopic behavior. In contrast, the smoke plume from the Canadian wildfire traveled at altitudes between 6 and 8 km a.s.l., remaining unaffected by local humidity. Absorption in this case was higher, and, as observed in other aged wildfires, the LR at 532 nm was larger than that at 355 nm. Specifically, the LR at 355 nm was 55 ± 2 sr, while at 532 nm it was 82 ± 3 sr. The AEβ values were 1.77 ± 0.13 and 1.41 ± 0.07 at 355–532 nm and 532–1064 nm, respectively and the PLDR at 532 nm was 0.040 ± 0.003. Microphysical analysis suggests the presence of larger, yet much more absorbent particles. This analysis indicates that both optical and microphysical properties of smoke can vary significantly depending on its origin, persistence, and transport in the atmosphere. These factors that must be carefully incorporated into future climate models, especially considering the frequent occurrences of fire events worldwide. Full article

Monolayer (ML) molybdenum disulfide (MoS₂) is a typical valleytronic material which has important applications in, for example, polarization optics and information technology. In this study, we examine the effect of continuous wave (CW) laser pumping on the basic optoelectronic properties of ML MoS₂ placed on a sapphire substrate, where the pump photon energy is larger than the bandgap of ML MoS₂. The pump laser source is provided by a compact semiconductor laser with a 445 nm wavelength. Through the measurement of THz time-domain spectroscopy, we obtain the complex optical conductivity for ML MoS₂, which are found to be fitted exceptionally well with the Drude–Smith formula. Therefore, we expect that the reduction in conductivity in ML MoS₂ is mainly due to the effect of electronic backscattering or localization in the presence of the substrate. Meanwhile, one can optically determine the key electronic parameters of ML MoS₂, such as the electron density n_e, the intra-band electronic relaxation time τ, and the photon-induced electronic localization factor c. The dependence of these parameters upon CW laser pump intensity is examined here at room temperature. We find that 445 nm CW laser pumping results in the larger n_e, shorter τ, and stronger c in ML MoS₂ indicating that laser excitation has a significant impact on the optoelectronic properties of ML MoS₂. The origin of the effects obtained is analyzed on the basis of solid-state optics. This study provides a unique and tractable technique for investigating photo-excited carriers in ML MoS₂. Full article

Marine oil spills cause significant environmental damage worldwide. Marine radar imagery is used for oil spill detection. However, the rapid attenuation of backscatter intensity with increasing distance limits detectable coverage. A multi-stage image enhancement framework integrating background clutter fitting subtraction, Multi-Scale Retinex, and Gamma correction is proposed. Experimental results using marine radar images sampled in the oil spill incident in Dalian 2010 are used to demonstrate the significant improvements. Compared to Contrast-Limited Adaptive Histogram Equalization and Partially Overlapped Sub-block Histogram Equalization, the proposed method enhances image contrast by 24.01% and improves the measurement of enhancement by entropy by 17.11%. Quantitative analysis demonstrates 95% oil spill detection accuracy through visual interpretation, while significantly expanding detectable coverage for oil extraction. Full article

High-sensitivity fiber scintillator detectors are the key to achieving high signal-to-noise ratio and high contrast imaging in X-ray Compton backscattering technology. We established a simulation model of wavelength-shifting fiber (WSF) scintillator detectors based on Geant4. The influences of ray source energy, detection area, number of WSFs, and coupling mechanism on detection efficiency were simulated. By using the epoxy resin coupling method, the transmission efficiency between the WSF and scintillator was increased from 4.56% to 19.79%. Based on the simulation data, we developed an X-ray WSFs scintillator detector, built an X-ray backscattering imaging experimental system, obtained high-contrast backscattering images, and verified the performance of the detector. Full article

This study analyzes the potential of optical and radar satellite data to monitor faba bean (Vicia faba L.) phenology over six years (2016–2021) in southwestern France. Using Sentinel-1, Sentinel-2, and Landsat-8 data, temporal variations in NDVI and radar backscatter coefficients (γ⁰_VV, γ⁰_VH, and γ⁰_VH/VV) are examined to assess crop growth, detect anomalies, and evaluate the impact of climatic conditions and sowing strategies. The results show that NDVI and the radar ratio (γ⁰_VH/VV) were suited to monitor faba bean phenology, with distinct growth phases observed annually. NDVI provides a clear seasonal pattern but is affected by cloud cover, while radar backscatter offers continuous monitoring, making their combination highly beneficial. The signal γ⁰_VH/VV exhibits well-marked correlations with NDVI (r = 0.81) and LAI (r = 0.83), particularly in orbit 30, which provides greater sensitivity to vegetation changes. The analysis of individual fields (inter-field approach) reveals variations in sowing strategies, with both autumn and spring plantings detected. Fields sown in autumn show early NDVI (and γ⁰_VH/VV) increases, while spring-sown fields display delayed growth patterns. This study also highlights the impact of climatic factors, such as precipitation and temperature, on inter-annual variability. Moreover, faba beans used as an intercropping species exhibit a shorter and more intense growth cycle, with a rapid NDVI (and γ⁰_VH/VV) increase and an earlier end of the vegetative cycle compared to standard rotations. Double logistic modeling successfully reconstructs temporal trends, achieving high accuracy (r > 0.95 and rRMSE < 9% for γ⁰_VH/VV signals and r > 0.89 and rRMSE < 15% for NDVI). These double logistic functions are capable of reproducing the differences in phenological development observed between fields and years, providing a reference set of functions that can be used to monitor the phenological development of faba beans in real time. Future applications could extend this methodology to other crops and explore alternative radar systems for improved monitoring (such as TerraSAR-X, Cosmos-SkyMed, ALOS-2/PALSAR, NISAR, ROSE-L…). Full article

Accurate and timely flood mapping is critical for informing emergency response and risk mitigation during extreme weather events. This study presents a synthetic aperture radar (SAR)-based approach for rapid flood extent mapping using Sentinel-1 imagery, demonstrated for Tropical Storm Imelda (17–21 September 2019) in southeastern Texas. Dual-polarization Sentinel-1 SAR data (VH and VV) were processed by computing the VH/VV backscatter ratio, and the resulting ratio image was classified using a supervised Random Forest classifier to delineate water and land. All Sentinel-1 images underwent radiometric calibration, speckle noise filtering, and terrain correction to ensure precision in flood delineation. The Random Forest classifier achieved an overall flood mapping accuracy exceeding 94%, with Cohen’s kappa coefficients of approximately 0.75–0.80, demonstrating the approach’s reliability in distinguishing transient floodwaters from permanent water bodies. The spatial distribution of flooding was strongly influenced by topography and land cover. Analysis of Shuttle Radar Topography Mission (SRTM) digital elevation data revealed that low-lying, flat terrain was most vulnerable to inundation; correspondingly, the land cover types most affected were hay/pasture, cultivated land, and emergent wetlands. Additionally, urban areas with low-intensity development experienced extensive flooding, attributed to impervious surfaces exacerbating runoff. A strong, statistically significant correlation (R² = 0.87, p < 0.01) was observed between precipitation and flood extent, indicating that heavier rainfall led to greater inundation; accordingly, the areas with the highest rainfall totals (e.g., Jefferson and Chambers counties) experienced the most extensive flooding, as confirmed by SAR-based change detection. The proposed approach eliminates the need for manual threshold selection, thereby reducing misclassification errors due to speckle noise and land cover heterogeneity. Harnessing globally available Sentinel-1 data with near-real-time processing and a robust classifier, this approach provides a scalable solution for rapid flood monitoring. These findings underscore the potential of SAR-based flood mapping under adverse weather conditions, thereby contributing to improved disaster preparedness and resilience in flood-prone regions. Full article

Floods caused by extreme weather events critically impact human and natural systems. Remote sensing can be a very useful tool in mapping these impacts. However, processing and analyzing satellite imagery covering extensive periods is computationally intensive and time-consuming, especially when data from different sensors need to be integrated, hampering its operational use. To address this issue, the present study focuses on mapping flooded areas and analyzing the impacts of the 2023 Storm Daniel flood in the Thessaly region (Greece), utilizing Earth Observation and GIS methods. The study uses multiple Sentinel-1, Sentinel-2, and Landsat 8/9 satellite images based on backscatter histogram statistics thresholding for SAR and Modified Normalized Difference Water Index (MNDWI) for multispectral images to delineate the extent of flooded areas triggered by the 2023 Storm Daniel in Thessaly region (Greece). Cloud computing on the Google Earth Engine (GEE) platform is utilized to process satellite image acquisitions and track floodwater evolution dynamics until the complete drainage of the area, making the process significantly faster. The study examines the usability and transferability of the approach to evaluate flood impact through land cover, linear infrastructure, buildings, and population-related geospatial datasets. The results highlight the vital role of the proposed approach of integrating remote sensing and geospatial analysis for effective emergency response, disaster management, and recovery planning. Full article