Search Results (4,049)

Snow plays a crucial role in global climate regulation, hydrological processes, and environmental change, making the accurate acquisition of snow depth data highly significant. In this study, we used Sentinel-1 radar data and employed a simulated annealing algorithm to select the optimal influencing factors from radar backscatter characteristics and spatiotemporal geographical parameters within the study area. Snow depth retrieval was subsequently performed using both random forest (RF) and Support Vector Machine (SVM) models. The retrieval results were validated against in situ measurements and compared with the long-term daily snow depth dataset of China for the period 2017–2019. The results indicate that the RF model achieves better agreement with the measured data than existing snow depth products. Specifically, in the Xinjiang region, the RF model demonstrates superior performance, with an R² of 0.92, a root mean square error (RMSE) of 2.61 cm, and a mean absolute error (MAE) of 1.42 cm. In contrast, the SVM regression model shows weaker agreement with the observations, with an R² lower than that of the existing snow depth product (0.51) in Xinjiang, and it performs poorly in other regions as well. Overall, the SVM model exhibits deficiencies in both predictive accuracy and spatial stability. This study provides a valuable reference for snow depth retrieval research based on active microwave remote sensing techniques. Full article

Lidar technology is a key sensor for autonomous driving due to its precise environmental perception. However, adverse weather and atmospheric conditions involving fog, rain, snow, dust, and smog can impair lidar performance, leading to potential safety risks. This paper introduces a comprehensive methodology to simulate lidar systems under such conditions and validate the results against real-world experiments. Existing empirical models for the extinction and backscattering of laser beams are analyzed, and new models are proposed for dust storms and smog, derived using Mie theory. These models are implemented in the CARLA simulator and evaluated using Robot Operating System 2 (ROS 2). The simulation methodology introduced allowed the authors to set up test experiments replicating real-world conditions, to validate the models against real-world data available in the literature, and to predict the performance of the lidar system in all weather conditions. This approach enables the development of virtual test scenarios for corner cases representing rare weather conditions to improve robustness and safety in autonomous systems. Full article

This study aims to address the challenges posed by uneven energy amplitude and a low signal-to-noise ratio (SNR) in the total focus imaging of coarse-crystalline elastic anisotropic materials. A novel method for acoustic field correction vector-coherent total focus imaging, based on the materials’ properties, is proposed. To demonstrate the effectiveness of this method, a test specimen, an austenitic stainless steel nozzle weld, was employed. Seven side-drilled hole defects located at varying positions and depths, each with a diameter of 2 mm, were examined. An ultrasound simulation model was developed based on material backscatter diffraction results, and the scattering attenuation compensation factor was optimized. The acoustic field correction function was derived by combining acoustic field directivity with diffusion attenuation compensation. The phase coherence weighting coefficients were calculated, followed by image reconstruction. The results show that the proposed method significantly improves imaging amplitude uniformity and reduces the structural noise caused by the coarse crystal structure of austenitic stainless steel. Compared to conventional total focus imaging, the detection SNR of the seven defects increased by 2.34 dB to 10.95 dB. Additionally, the defect localization error was reduced from 0.1 mm to 0.05 mm, with a range of 0.70 mm to 0.88 mm. Full article

Terahertz (THz) communications and simultaneous wireless information and power transfer (SWIPT) hold the potential to energize battery-less Internet-of-Things (IoT) devices while enabling multi-gigabit data transmission. However, severe path loss, blockages, and rectifier nonlinearity significantly hinder both throughput and harvested energy. Additionally, high-power THz beams pose safety concerns by potentially exceeding specific absorption rate (SAR) limits. We propose a sensing-adaptive power-focusing (APF) framework in which a reconfigurable intelligent surface (RIS) embeds low-rate THz sensors. Real-time backscatter measurements construct a spatial map used for the joint optimisation of (i) RIS phase configurations, (ii) multi-tone SWIPT waveforms, and (iii) nonlinear power-splitting ratios. A weighted MMSE inner loop maximizes the data rate, while an outer alternating optimisation applies semidefinite relaxation to enforce passive-element constraints and SAR compliance. Full-stack simulations at 0.3 THz with 20 GHz bandwidth and up to 256 RIS elements show that APF (i) improves the rate–energy Pareto frontier by 30–75% over recent adaptive baselines; (ii) achieves a 150% gain in harvested energy and a 440 Mbps peak per-user rate; (iii) reduces energy-efficiency variance by half while maintaining a Jain fairness index of 0.999;; and (iv) caps SAR at 1.6 W/kg, which is 20% below the IEEE C95.1 safety threshold. The algorithm converges in seven iterations and executes within <3 ms on a Cortex-A78 processor, ensuring compliance with real-time 6G control budgets. The proposed architecture supports sustainable THz-powered networks for smart factories, digital-twin logistics, wire-free extended reality (XR), and low-maintenance structural health monitors, combining high-capacity communication, safe wireless power transfer, and carbon-aware operation for future 6G cyber–physical systems. 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

Additive manufacturing (AM), particularly laser powder bed fusion (L-PBF), provides unmatched design flexibility for creating intricate steel structures with minimal post-processing. However, adopting L-PBF for high-performance applications is difficult due to the challenge of predicting microstructure evolution. This is because the process is sensitive to many parameters and has a complex thermal history. Thin-walled geometries present an added challenge because their dimensions often approach the scale of individual grains. Thus, microstructure becomes a critical factor in the overall integrity of the component. This study focuses on applying cellular automata (CA) modeling to establish robust and efficient process–structure relationships in L-PBF of 316L stainless steel. The CA framework simulates solidification-driven grain evolution and texture development across various processing conditions. Model predictions are evaluated against experimental electron backscatter diffraction (EBSD) data, with additional quantitative comparisons based on texture and morphology metrics. The results demonstrate that CA simulations calibrated with relevant process parameters can effectively reproduce key microstructural features, including grain size distributions, aspect ratios, and texture components, observed in thin-walled L-PBF structures. This work highlights the strengths and limitations of CA-based modeling and supports its role in reliably designing and optimizing complex L-PBF components. Full article

Two-dimensional (2D) materials have been proposed for use in a multitude of applications, with graphene being one of the most well-known 2D materials. Despite their potential to contribute to innovative solutions, the fabrication of such devices still faces significant challenges. One of the key challenges is the fabrication at a wafer-level scale, a fundamental step for allowing reliable and reproducible fabrication of a large volume of devices with predictable properties. Overcoming this barrier will allow further integration with sensors and actuators, as well as enabling the fabrication of complex circuits based on 2D materials. This work presents the fabrication steps for a process that allows the on-wafer fabrication of active and passive radiofrequency (RF) devices enabled by graphene. Two fabrication processes are presented. In the first one, graphene is transferred to a back gate surface using critical point drying to prevent cracks in the graphene. In the second process, graphene is transferred to a flat surface planarized by ion milling, with the gate being buried beneath the graphene. The fabrication employs a damascene-like process, ensuring a flat surface that preserves the graphene lattice. RF transistors, passive RF components, and antennas designed for backscatter applications are fabricated and measured, illustrating the versatility and potential of the proposed method for 2D material-based RF devices. The integration of graphene on devices is also demonstrated in an antenna. This aimed to demonstrate that graphene can also be used as a passive device. Through this device, it is possible to measure different backscatter responses according to the applied graphene gating voltage, demonstrating the possibility of wireless sensor development. With the proposed fabrication processes, a flat graphene with good quality is achieved, leading to the fabrication of RF active devices (graphene transistors) with intrinsic f_T and f_max of 14 GHz and 80 GHz, respectively. Excellent yield and reproducibility are achieved through these methods. Furthermore, since the graphene membranes are grown by Chemical Vapor Deposition (CVD), it is expected that this process can also be applied to other 2D materials. Full article

The transport properties of one-dimensional van der Waals nanodevices composed of carbon nanotubes (CNTs), hexagonal boron nitride (hBN) nanotubes, and molybdenum dichalcogenide (MoX₂) nanotubes were investigated within the framework of density functional theory (DFT). It was found that in nanodevices based on MoS₂(24,24) and MoTe₂(24,24), the effect of resonant tunneling is suppressed due to electron–phonon scattering. This suppression arises from the fact that these materials are semiconductors with an indirect band gap, where phonon participation is required to conserve momentum during transitions between the valence and conduction bands. In contrast, nanodevices incorporating MoSe₂(24,24), which possesses a direct band gap, exhibit resonant tunneling, as quasiparticles can tunnel between the valence and conduction bands without a change in momentum. It was demonstrated that the presence of vacancy defects in the CNT segment significantly degrades quasiparticle transport compared to Stone–Wales (SW) defects. Furthermore, it was revealed that resonant interactions between SW defects in MoTe₂(24,24)–hBN(27,27)–CNT(24,24) nanodevices can enhance the differential conductance under certain voltages. These findings may be beneficial for the design and development of nanoscale diodes, back nanodiodes, and tunneling nanodiodes. Full article

This study investigates the influence of plastic deformation and temperature on the formation of mechanically induced martensite and the associated changes in hardness in AISI 304 austenitic stainless steel. Cold rolling was performed at three temperatures (20 °C, 0 °C, and −196 °C) and various degrees of deformation (10–70%). Microstructural changes, including the formation of ε and α′ martensite, were characterized using X-ray diffraction (XRD) and electron backscatter diffraction (EBSD). The results confirm that martensitic transformation proceeds via the γ → ε → α′ sequence, with transformation rates and martensite fractions increasing at lower temperatures and higher strains. The stacking fault energy of 25.9 mJ/m² favors this transformation pathway. Transformation rates of α′ martensite fractions significantly increased at lower temperatures and higher strains, 91.8% α′ martensite was observed at just 30% deformation at −196 °C. Hardness measurements revealed a strong correlation with martensite content: strain hardening dominated at lower deformations, while martensite formation became the primary hardening mechanism at higher deformations, especially at cryogenic temperatures. The highest hardness (551 HV) was observed in samples deformed to 70% at −196 °C. The findings provide insights into optimizing the mechanical properties of AISI 304 stainless steel through controlled deformation and temperature conditions. Full article

Background/Objectives: The work presented herein focused on the development and characterization of a transdermal caffeine platform fabricated from ultrathin micro- and submicron fibers produced via electrospinning. Methods: The formulations incorporated caffeine encapsulated in a polyethylene oxide (PEO) matrix, combined with various permeation enhancers. A backing layer made of annealed electrospun polycaprolactone (PCL) facilitated the lamination of the two layers to form the final multilayer patch. Comprehensive characterization was conducted, utilizing scanning electron microscopy (SEM) to assess the fiber morphology, attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) for chemical detection and to assess the stability of the caffeine, and differential scanning calorimetry (DSC) along with wide-angle X-ray scattering (WAXS) to analyze the physical state of the caffeine within the fibers of the active layer. Additionally, Franz cell permeation studies were performed using both synthetic membranes (Strat-M) and ex vivo human stratum corneum (SC) to evaluate and model the permeation kinetics. Results: These experiments demonstrated the significant role of enhancers in modulating the caffeine permeation rates provided by the patch, achieving permeation rates of up to 0.73 mg/cm² within 24 h. Conclusions: This work highlights the potential of using electro-hydrodynamic processing technology to develop innovative transdermal delivery systems for drugs, offering a promising strategy for enhancing efficacy and innovative therapeutic direct plasma administration. Full article

S355NL structural steel is extensively employed in bridges, ships, and power station equipment owing to its excellent tensile strength, weldability, and low-temperature toughness. However, pronounced fluctuations in its Charpy impact energy at low temperatures significantly compromise the reliability and service life of critical components. In this study, vacuum-induction-melted ingots of S355NL steel containing 0–0.086 wt.% rare earth cerium were prepared. The effects of Ce on microstructures, inclusions, and impact toughness were systematically investigated using optical microscopy (OM), scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and Charpy V-notch testing. The results indicate that appropriate Ce additions (0.0011–0.0049 wt.%) refine the average grain size from 5.27 μm to 4.88 μm, reduce the pearlite interlamellar spacing from 204 nm to 169 nm, and promote the transformation of large-size Al₂O₃-MnS composite inclusions into fine, spherical, Ce-rich oxysulfides. Charpy V-notch tests at –50 °C reveal that 0.0011 wt.% Ce enhances both longitudinal (269.7 J) and transverse (257.4 J) absorbed energies while minimizing anisotropy (E_t/E_l  =  1.01). Conversely, excessive Ce addition (0.086 wt.%) leads to coarse inclusions and deteriorates impact performance. These findings establish an optimal Ce window (0.0011–0.0049 wt.%) for microstructural and inclusion engineering to enhance the low-temperature impact toughness of S355NL steel. Full article

The lack of new materials with desired processability and functional characteristics remains a challenge for metal additive manufacturing (AM). Therefore, in this work, a new promising AISI 316L-based alloy with better performance compared to the commercially available one is developed via the laser powder bed fusion (L-PBF) process. Moreover, establishing process–structure–properties linkages is a critical point that should be evaluated carefully before adding newly developed alloys into the AM market. Hence, the current study investigates the influences of various process parameters on the as-built quality and microstructure of the newly developed alloy. The results revealed that increasing laser energy density led to reduced porosity and surface roughness, likely due to enhanced melting and solidification. Microstructural analysis revealed a uniform distribution of copper within the austenite phase without forming any agglomeration or secondary phases. Electron backscatter diffraction analysis indicated a strong texture along the build direction with a gradual increase in Goss texture at higher energy densities. Grain boundary regions exhibited higher local misorientation and dislocation density. These findings suggest that changing the process parameters of the L-PBF process is a promising method for developing tailored microstructures and chemical compositions of commercially available AISI 316L stainless steel. Full article

The inhibition of recrystallization in high-strain nickel-based single-crystal superalloys remains a critical challenge for advanced turbine blade applications. This study investigates the evolution of the primary γ’ phase and dislocation during annealing in a third-generation Re-containing single-crystal superalloy (WZ30) subjected to 5% compressive deformation. Isochronal annealing (700 to 1200 °C, 1 min) combined with scanning electron microscopy (SEM) and an electron backscatter diffraction (EBSD) analysis revealed a nonlinear variation of the geometrically necessary dislocation (GND) density, which reached a minimum of 1000 °C with 62.7% of the primary γ’ phase retained. Prolonged recovery annealing at 1000 °C for 10 h effectively inhibited recrystallization during subsequent solution heat treatment. This result provides a practical strategy for inhibiting recrystallization in single-crystal superalloys. 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

The application of additive manufacturing technology in the field of nuclear power is becoming increasingly promising. The low-cycle fatigue behavior of Z2CN19-10 controlled-nitrogen-content stainless steel (SS) was investigated by fatigue equipment, scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM), including additive manufactured (AM) and forged materials. The results showed that the microstructure of the AM material exhibited anisotropy for the X, Y, and Z directions. The tensile and impact properties of the X, Y, and Z directions in AM material were similar. The fatigue life (N_f) of X- and Y-direction specimens was better than that of Z-direction specimens. The tensile, impact, and fatigue properties of all AM materials were lower than those of the forged specimens. The Z direction specimens of AM material showed the best plastic strain by the highest transition fatigue life (N_T) during the fatigue strain amplitude at 0.3% to 0.6%. The forged specimens showed the best fatigue properties under the plastic strain amplitude control mode. Fatigue fracture surfaces of AM and forged materials exhibited multi- and single-fatigue crack initiation sites, respectively. This could be attributed to the presence of incompletely melted particles and manufacturing defects inside the AM specimens. The dislocation morphology of AM and forged fatigue specimens was observed to study the low-cycle fatigue behaviors in depth. Full article