Search Results (106)

Optimizing phosphor-converted light-emitting diodes is challenging due to the complex interplay of absorption, elastic scattering and luminescence. Unlike previous studies that focused on characterizing optical parameters, this work isolates their individual contributions in order to derive fundamental design limits. We present a comprehensive analysis using a GPU-accelerated Monte Carlo framework that solves the luminescent radiative transfer equation, including the full luminescence cascade. We systematically investigate the influence of the absorption (${\mu }_a$) and scattering (${\mu }_s$) coefficients by varying them over a range of 0.1 to 10 times the reference values of a standard phosphor (0.8 wt%). We found that transmitted luminescence saturates when absorption exceeds approximately three times the reference value (${\mu }_a\approx 1.2{\mathrm{mm}}^{-1}$) and peaks at an optimal ${\mu }_s$ before backscattering losses dominate. In high-concentration regimes, mirror-assisted geometries are shown to enhance backward emission by a factor of 2.1 compared to open boundaries. Our findings provide model-based predictions for luminescence transport in phosphor–polymer composites. Full article

Existing macroscopic finite element models for electron beam welding (EBW) typically assume isotropic material behavior, often failing to accurately predict residual stresses induced by strong crystallographic textures. To address this limitation, this study established a sequential dual-scale coupled numerical model bridging micro-texture to macro-mechanics by combining the crystal plasticity finite element method (CPFEM) with thermal-elastic-plastic theory. Representative volume elements (RVEs) incorporating α and β dual-phase characteristics were constructed based on electron backscatter diffraction (EBSD) data from the TA15 weld cross-section. Through simulated tensile and shear calculations on the RVEs, homogenized orthotropic stiffness matrices and Hill yield constitutive parameters were derived and mapped onto the macroscopic model. Simulation results indicate that the proposed model maintains the prediction error for molten pool morphology within 16.3%, while effectively correcting the stress overestimation inherent in isotropic models. Specifically, it adjusts the peak longitudinal residual stress at the weld center from 800 MPa to approximately 350 MPa, significantly reducing the anomalous “M-shaped” stress distribution. By successfully capturing shear stress components, this work provides a high-fidelity computational approach for predicting complex stress states in welded joints, offering critical insights for structural integrity assessment. Full article

The surface properties and electrical behavior of carbon-based materials can be effectively modified by energetic ion irradiation. In the present study, graphene oxide (GO) and cyclic olefin copolymer foils (COC, Topas 112 and 011, respectively) were irradiated with 1 MeV Au ions using a 3 MV Tandetron accelerator at fluences of 1 × 10¹⁴, 1 × 10¹⁵, and 2.5 × 10¹⁵ cm⁻². The irradiation induced systematic modifications in surface chemistry, morphology, wettability, and electrical properties. Composition changes were investigated using Rutherford backscattering spectrometry (RBS) and elastic recoil detection analysis (ERDA), while surface morphology and roughness were characterized by atomic force microscopy (AFM). This revealed a clear fluence-dependent evolution of nanoscale topography. The vibrational characteristics were assessed through Raman spectroscopy, and the chemical composition of the surface layers was analyzed by X-ray photoelectron spectroscopy (XPS). The surface wettability was evaluated by static contact angle measurements, and surface free energy was determined using the Owens–Wendt–Rabel–Kaelble (OWRK) method. These measurements showed a consistent decrease in water contact angle and an increase in surface free energy with increasing ion fluence in the COC substrates, whereas GO exhibited a distinct response. Electrical characterization demonstrated a pronounced fluence-dependent decrease in sheet resistivity in polymers. The results show that 1 MeV Au ion irradiation enables systematic and fluence-dependent modification of both surface and electrical properties. Full article

Elastic wave scattering in polycrystalline materials has been a long-lasting topic in seismology and physical acoustics. Numerous analytical scattering models have been reported for polycrystals with random grain orientations. However, the elastic wave scattering in polycrystals with a preferred grain orientation (crystallographic texture) has not been well studied. This study develops a general ultrasonic scattering model that correlates the scattering coefficients and attenuation coefficients with orientation distribution coefficients (ODCs) for polycrystalline materials with a crystallographic texture. These models are valid for aggregates of triclinic grains with arbitrary texture symmetry. Since different terminologies for orientation distribution functions (ODFs) are adopted in quantitative texture analysis, the relations between different terminologies are also summarized in this study. Furthermore, for two special cases—hexagonal polycrystalline materials with a fiber texture and cubic polycrystalline materials with orthotropic texture symmetry—explicit expressions for the ultrasonic backscattering coefficient through ODCs are derived. The explicit relationship between ultrasonic backscattering and ODCs not only manifests how the individual texture coefficients impact ultrasonic scattering but also makes it possible to determine ODCs up to the eighth order experimentally from ultrasonic scattering measurements. This type of forward model also can be applied to the microstructure characterization of textured polycrystals. Full article

Laser-based remote sensing (lidar) is a proven technique for detecting atmospheric features such as clouds and aerosols as well as for determining their vertical distribution with high accuracy. Even simple elastic backscatter lidars can distinguish clouds from aerosols, and accurate knowledge of their vertical location is essential for air quality assessment, hazard avoidance, and operational decision-making. However, daytime lidar measurements suffer from reduced signal-to-noise ratio (SNR) due to solar background contamination. Conventional processing approaches mitigate this by applying horizontal and vertical averaging, which improves SNR at the expense of spatial resolution and feature detectability. This work presents a deep learning-based framework that enhances lidar SNR at native resolution and performs fast layer detection and cloud–aerosol discrimination. We apply this approach to ICESat-2 532 nm photon-counting data, using artificially noised nighttime profiles to generate simulated daytime observations for training and evaluation. Relative to the simulated daytime data, our method improves peak SNR by more than a factor of three while preserving structural similarity with true nighttime profiles. After recalibration, the denoised photon counts yield an order-of-magnitude reduction in mean absolute percentage error in calibrated attenuated backscatter compared with the simulated daytime data, when validated against real nighttime measurements. We further apply the trained model to a full month of real daytime ICESat-2 observations (April 2023) and demonstrate effective layer detection and cloud–aerosol discrimination, maintaining high recall for both clouds and aerosols and showing qualitative improvement relative to the standard ATL09 data products. As an alternative to traditional averaging-based workflows, this deep learning approach offers accurate, near real-time data processing at native resolution. A key implication is the potential to enable smaller, lower-power spaceborne lidar systems that perform as well as larger instruments. Full article

The significant advancement in additive technologies has made it possible to manufacture metal components in diverse shapes and sizes. Despite this progress, numerous processes and phenomena, along with the implications of producing components layer by layer on their performance under stress, remain inadequately explored. These factors not only affect microstructure but subsequently also the mechanical properties. The positioning of objects within the 3D printer’s workspace can thus significantly play a crucial role in their operational functionality, reliability, and safety of the equipment in an application. This article studies anisotropic properties and the influence of the printing orientation of aluminum alloy (AlSi10Mg) cylindrical tensile samples fabricated through an additive approach on their mechanical properties under tensile loading. Tensile testing of specimens covering seven different spatial orientations in the workspace of a 3D printing machine was performed according to ISO 6892-1 international standard. Minimum and maximum tensile properties (yield and ultimate tensile strength) have been observed in Y-sample and X-sample series, respectively. In contrast, elastic modulus of the 3D printed specimens was minimal for X-sample series, and maximal for Y-sample series. Fracture surfaces of the samples in seven basic spatial orientations were evaluated in synergy with the mechanical testing results determined by optical, electron microscopy, and electron backscatter diffraction (EBSD) textural analysis to find correlation between the strength of the samples and the orientation of grains, their size and morphology. Furthermore, thermodynamic and Scheil–Gulliver simulation has been employed in order to explain the formation of intermetallic phases during additive manufacturing and further justifying observations in microstructure and mechanical properties. The disparity in texture intensity between these regions for samples Y(3) is likely responsible for localized mechanical incompatibilities and strain heterogeneity, resulting in preferential crack paths and reduced mechanical strength compared to the sample Z(3), which presented a more randomized orientation distribution with less distinguishable texture zones, enabling better strain accommodation and more uniform plastic deformation, which correlates with its higher tensile and yield strength. 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

This paper employs in situ Electron Backscatter Diffraction (EBSD) tensile technology to thoroughly consider the evolution of microstructure, grain size, grain boundary characteristics, orientation differences, and dislocation density of H13 steel during the elastic and plastic stages of room temperature tensile testing. The study unveils the deformation mechanisms of inclusions, carbides, and the matrix in H13 steel during the various stages, providing a comprehensive explanation for the slightly superior tensile properties of H13 steel when refined by Vacuum Induction Melting combined with Vacuum Arc Remelting (VIM + VAR) over those when refined by Electroslag Remelting (ESR). This discrepancy is primarily attributed to the differences in inclusions and carbides present in the two refining processes. The quantity and size of inclusions and carbides are closely related to material fracture. Large-sized carbides and inclusions were shown to be more likely to cause dislocation pile-ups and stress concentration. This, in turn, leads to faster crack initiation and propagation during plastic deformation. Conversely, the formation of micro-pores within these fine inclusions and the matrix is contingent on greater plastic deformation, resulting in a gradual and incremental linkage of these micro-pores to form dimples beneath the influence of slip. Full article

Improving the surface quality and controlling the microstructure evolution of difficult-to-cut materials are always challenges in high-speed machining (HSM). In this paper, surface topography, defects and roughness are assessed to characterize the surface features of 7050 aluminum alloy (Al 7050) under HSM conditions characterized by high temperature, strain and strain rate. Based on multi-physical field coupling, the mechanism of microstructure evolution of Al 7050 is investigated in HSM. The results indicate that the surface morphology and roughness of Al7050 during HSM are optimal at f_z = 0.025 mm/z, and the formation of surface defects (adherent chips, cavities, microcracks, material compression and tearing) in HSM is mainly affected by thermo-mechanical coupling. Significant differences are observed in the microstructure of different machined subsurfaces by electron backscatter diffraction (EBSD) technology, and high cutting speeds and high feed rates contributed to recrystallization. The crystallographic texture types on machined subsurface are mainly {110}<112> Brass texture, {001}<100> Cube texture, {123}<634> S texture and {124}<112> R texture, and the crystallographic texture type and intensity are significantly affected by multi-physical field coupling. The elastic–plastic deformation and microstructural evolution of Al7050 alloy during the HSM process are mainly influenced by the coupling effects of multiple physical fields (stress–strain field and thermo-mechanical coupling field). This study reveals the internal mechanism of multi-physical field coupling in HSM and provides valuable enlightenment for the control of microstructure evolution of difficult-to-cut materials in HSM. Full article

Fast nanoindentation technology is a new method used to generate performance maps showing the hardness and elastic modulus distribution of each position, and it has become a research focus. In this paper, nanoindentation combined with scanning electron backscatter diffraction (EBSD) is used to analyze the micro-regional properties of single-phase interstitial-free (IF) steel. Hardness, elastic modulus and the orientation of a 200 μm × 200 μm area were characterized in situ. The relationships between hardness, elastic modulus and orientation were analyzed. The experimental results showed that the hardness varied from 1.25 GPa to 2.57 GPa, while the modulus varied from 122 GPa to 227 GPa with different crystallographic orientations. The hardness value of the (111) crystal plane was particularly high, with an average hardness of about 1.84 GPa, which is due to its higher work hardening rate. This result is consistent with the EBSD kernel average misorientation (KAM) micrograph. The harder locations with greater misorientation are more difficult to deform compared to locations with small hardness regions, for example, the (001) crystal plane. However, there seems to be no obvious strong relationship between modulus and orientation. The modulus of the regions with lower hardness seems to be smaller. The results of the KAM diagram are consistent with those of hardness mapping. Full article

Additive manufacturing (AM) methods like powder bed fusion–laser beam (PBF-LB) enable complex geometry production. However, understanding and predicting the microstructural properties of AM parts remain challenging due to the inherent non-homogeneity introduced during the manufacturing process. This study demonstrates a novel approach for 3D microstructure representation and virtual testing of non-homogeneous AM materials using 2d electron backscatter diffraction (EBSD) data. By employing the representative volume element (RVE) method, we reconstruct the 3D microstructure from 2D EBSD datasets, effectively capturing the grain morphological characteristics of PBF-LB-produced Hastelloy X. Using validated RVE data, we artificially generate combinations of two grain textures to gain deeper insight into locally affected areas, particularly the stress distribution within the interfaces, as well as global material behavior, exploring non-homogeneity. Computational homogenization (CH) utilizing a crystal elasticity finite element (CEFE) method is used to virtually test and predict directional elastic properties, offering insights into relationships between microstructure evolution and property correlation. The experimentally validated results show a strong correlation, with only 0.5–3.5% correlation error for the selected grain tessellation method. This consistency and reliability of the methodology provide high confidence for additional virtual tests predicting the properties of non-homogeneous, artificially generated combined-grain structures. Full article

In-depth quality assessment of 3D-printed parts is vital in determining their overall characteristics. This study focuses on the use of 2D X-Ray diffraction (2D-XRD) and X-Ray micro-computed tomography (micro-CT) techniques to evaluate the crystallography and internal defects of 316L SS parts fabricated by the powder-based direct energy deposition (DED) technique. The test samples were printed in a controlled argon environment with variable laser power and print speeds, using a customized deposition pattern to achieve a high-density print (>99%). Multiple features, including hardness, elastic modulus, porosity, crystallographic orientation, and grain morphology and size were evaluated as a function of print parameters. Micro-CT was used for in-depth internal defect analysis, revealing lack-of-fusion and gas-induced (keyhole) pores and no observable micro-cracks or inclusions in most of the printed body. Some porosity was found mostly concentrated in the initial layers of print and decreased along the build direction. 2D-XRD was used for phase analysis and grain size determination. The phase analysis revealed single phase γ-austenitic FCC phase without any detectable presence of the δ-ferrite phase. A close correlation was found between Electron Backscatter Diffraction (EBSD) and 2D-XRD results on the average size distribution and the crystallographic orientation of grains in the sample. This work demonstrates the fast and reliable as-printed crystallography analysis using 2D-XRD compared to the EBSD technique, with potential for in-line integration. Full article

An enhancement in fatigue life for ferrite–pearlite low-carbon steel (LCS) at high temperature (HT) has been discovered, where it increased from 190,873 cycles at room temperature (RT) to 10,000,000 cycles at 400 °C under the same stress conditions. To understand the mechanism behind this phenomenon, the evolution of microstructure and dislocation density during fatigue tests was comprehensively investigated. High-power X-ray diffraction (XRD) was employed to analyze the evolution of total dislocation density, while Electron Backscatter Diffraction (EBSD) and High-Resolution EBSD (HR-EBSD) were conducted to reveal the evolutions of kernel average misorientation (KAM), geometrically necessary dislocations (GND) and elastic strains. Results indicate that the enhancement was attributed to the dynamic strain aging (DSA) effect above the upper temperature limit, where serration and jerky flow disappeared but hindrance of dislocations persisted. Due to the DSA effect, periods of increase and decrease in the total dislocations were observed during HT fatigue tests, and the fraction of screw dislocations increased continuously, caused by viscous movement of the screw dislocations. Furthermore, the increased fraction of screw dislocations resulted in a lower energy configuration, reducing slip traces on sample surfaces and preventing fatigue-crack initiation. Full article

Elastic peak electron spectroscopy (EPES) analyzes the line shape of the elastic peak. The reduction in energy of the elastic peak electrons is the result of energy transfer to the target atoms, a phenomenon known as recoil energy. EPES differs from other electron spectroscopies in its unique ability to identify hydrogen in polymers and hydrogenated carbon-based materials. This feature is particularly noteworthy as lighter elements exhibit stronger energy shifts. The energy difference between the positions of the elastic peak of carbon and the elastic peak of hydrogen tends to increase as the kinetic energy of the incident electrons increases. During electron irradiation of an insulating polymer, if the number of secondary electrons emitted from the surface is less than the number of electrons absorbed in the sample, the surface floats energetically until it stabilizes at a potential energy $e{V}_s$. As a result, the interaction energy changes and modifies the energy difference between the elastic peaks of hydrogen and carbon. In this study, the charge effects are evaluated using the Monte Carlo method to simulate the EPES spectra of electrons interacting with polystyrene and polyethylene. Full article

Using traditional algorithms to identify persistent scatterer (PS) points is challenging during bridge construction because of short-term changes at construction sites, such as earthworks, as well as the erection and dismantling of temporary structures. To address this issue, this study proposes a PS point selection method based on statistical theory and Gaussian Mixture Model-Expectation Maximization (GMM-EM) algorithm. This method adopts amplitude information as an incoherence evaluation indicator. Furthermore, the statistical median of the amplitude dispersion index and amplitude mean is screened twice to extract a set of candidate points, including PS points that exhibit stable backscattering over long durations. Temporal coherence is simultaneously used as the coherence evaluation indicator. Another candidate point set is obtained by extracting high-coherence PS points using the GMM-EM algorithm. These sets of candidate points are then combined to obtain a final PS points set. In the experiment, the deformation monitoring of the under-construction Shenzhen-Zhongshan Cross-Sea Bridge in China was selected as a case study, with 28 Sentinel-1A images used as the data source for PS selection and deformation information extraction. The results show that the proposed method enhanced the density and quality of PS points on the under-construction cross-sea bridge compared to existing PS selection methods, thus offering higher reliability. Deformation analysis further revealed fluctuating deformation trends at characteristic points of the Shenzhen-Zhongshan Cross-Sea Bridge, indicating the occurrence of elastic deformation during its construction. Full article