Search Results (423)

TC4 alloy samples were fabricated via selective laser melting (SLM) under different process parameters. The effects of scanning speed and build orientation on the microstructure and corrosion behavior were systematically investigated using optical microscopy (OM), scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), X-ray diffraction (XRD), and electrochemical measurements. The results show that when increasing scan speed, TC4 alloy consists primarily of α/α’ phases with a minor amount of β phase, along with grain refinement and a higher fraction of low-angle grain boundaries. In 3.5% NaCl solution, the XOY-oriented sample processed at 1000 mm s⁻¹ exhibited higher impedance and formed a stable, highly protective passive film. In simulated body fluid, the XOY orientation at 1200 mm s⁻¹ displayed a larger capacitive arc, indicating superior corrosion resistance. These findings demonstrate that the corrosion performance of SLM-processed TC4 alloy can be optimized for specific service environments by tailoring both process parameters and build orientation. Full article

This paper provides a comprehensive overview of the progress in fiber-optic gyroscope technology, covering 260 key studies of the last ten years. A critical comparative analysis of fiber-optic gyroscope with alternative inertial sensors (Micro-Electro-Mechanical Systems, Hemispherical Resonator Gyroscope, Ring Laser Gyroscope) has been carried out. Confirming the unique advantages of fiber-optic gyroscope for autonomous navigation. Fundamental limitations of accuracy are considered in detail: temperature drifts, polarization noise, and Rayleigh backscattering. Modern hardware methods for suppressing these errors, including the use of photonic crystal and hollow fibers (Air-Core/Hollow-Core), are also considered in this work. The central place in the review is occupied by the analysis of the technological paradigm shift from bulky discrete circuits to hybrid integrated photonics (Indium Phosphide, Silicon Nitride, Lithium Niobate) and hybrid architectures to reduce weight and size characteristics. The role of artificial intelligence (Deep Learning, Long Short-Term Memory) methods in nonlinear drift compensation and calibration is discussed. The usage of the Brillouin effect and optomechanics promising areas are outlined, necessary to create a new generation of navigation systems operating in the absence of Global Navigation Satellite Systems signals. Full article

Reliable quantification of microplastics in water remains challenging because most Raman-based methods require filtration, drying, or complex flow systems, which can lead to particle loss and signal instability. Here, we propose a simple dual-laser Raman strategy for the direct, real-time quantification of microplastics in water without pretreatment. By simultaneously integrating backscattering and transmission geometries using two identical 532 nm lasers, spatial variations in Raman scattering cross-sections, arising from particle motion and focal depth fluctuations, are effectively mitigated. The dual-laser configuration enhances Raman intensity by approximately 1.5-fold compared with backscattering and threefold compared with transmission alone (p < 0.001), enabling robust real-time detection with a temporal resolution of 0.1 s. Accurate particle counting is demonstrated using polystyrene (PS) standard beads and further validated for polyamide 6 (PA6) and polyvinyl chloride (PVC) particles with irregular morphologies and broad size distributions, with no false-positive events observed. By prioritizing simplicity and quantitative reliability over ultimate size resolution, the proposed strategy provides a practical approach for routine monitoring of microplastics in drinking water and industrial aqueous systems. Full article

In order to verify the feasibility of in situ repair of underwater local dry laser welding (ULDLW) on nuclear power reactor components, this work investigates the microstructure and mechanical properties of 304L austenitic stainless steel repaired by ULDLW using ER308L filler metal. Comprehensive comparison would be made between the ULDLW and conventional in-air laser welding to evaluate their applicability. The results demonstrate that the rapid cooling rate inherent to the underwater environment significantly influences solidification behavior and microstructural evolution. The weld metal (WM) solidifies in the ferritic–austenitic (FA) mode, with an increased proportion of lathy δ-ferrite at the expense of skeletal morphology compared to the in-air welds. Electron backscatter diffraction (EBSD) analysis reveals the substantial grain refinement in underwater welds, with average grain sizes of 39.4 μm versus 47.3 μm for in-air weld bead, accompanied by a higher fraction of low-angle grain boundaries (LAGBs). These microstructural modifications yield superior mechanical properties: underwater weld bead exhibits ultimate tensile strength (UTS) of 685.6 MPa, elongation of 57.5%, and impact toughness of 22.6 J, significantly exceeding the corresponding values for in-air welds (663.9 MPa, 51.8%, and 18.6 J, respectively). Fractographic analysis confirms ductile fracture mechanisms in both conditions. The enhanced performance is attributed to grain refinement strengthening via the Hall–Petch relationship and the increased LAGBs fraction, which impedes dislocation motion and crack propagation. Full article

Targeting the long-term goal of synchronous acquisition of underwater terrain and material composition information, this study establishes a radiative transfer model for underwater hyperspectral LiDAR (UDHSL) and systematically verifies the effects of target reflectance, detection distance, and laser wavelength on backscattering echo intensity through controlled laboratory experiments. A wavelength-dependent water attenuation correction term incorporating absorption and scattering was introduced into the conventional LiDAR equation to derive a hyperspectral LiDAR radiative transfer equation applicable to underwater environments, and a normalized echo intensity processing method using window glass reflection as a reference was proposed. This study uses a custom-built UDHSL system (wavelength range: 450; detection range approximately 5–6 m). The echo intensity exhibits pronounced wavelength selectivity, peaking at 450–550 nm in clear water and shifting to 530–570 nm in turbid water. These experimental results are consistent with theoretical predictions of the radiative transfer model, validating its fundamental correctness and providing an experimental basis for radiometric calibration and underwater target reflectance retrieval of UDHSL systems. Full article

This study compares the microstructural evolution and mechanical properties of TC4 (Ti-6Al-4V) titanium alloy joints welded by Tungsten Inert Gas (TIG) and laser processes, following a post-weld annealing treatment at 650 °C for 2 h. Distinct microstructures were obtained: the TIG-welded joint developed a heterogeneous mixture of short-rod α and lamellar β, while the laser-welded joint formed a more homogeneous equiaxed α structure with uniformly distributed β-phase nanoparticles. Electron backscatter diffraction (EBSD) results confirmed that the annealing treatment significantly weakened the strong welding-induced texture and disrupted the epitaxial growth mode of columnar grains. Mechanical testing demonstrated that annealing improved the strength-toughness balance, but the extent and mechanism differed between the two processes. For the TIG-welded joint, the ultimate tensile strength slightly decreased, while elongation and impact toughness increased by 18% and 10.4%, respectively. In contrast, the laser-welded joint maintained its original strength while achieving greater improvements in ductility and toughness, with elongation and impact toughness increasing by 20% and 15.2%, respectively. This divergence is attributed to insufficient recrystallization and the persistence of residual coarse grains, limiting the TIG joint’s performance. However, in the laser-welded joint, the pinning effect of β-phase nanoparticles and associated grain refinement enhanced ductility without compromising strength. Full article

In this work, we demonstrate a functional and previously insufficiently explored route for converting cyclic olefin copolymer (COC) TOPAS^® thin films into antibacterial hybrid materials through a combination of solvent casting, plasma activation, noble-metal sputtering, and subsequent thermal or laser treatment. While COC is already well-known as a transparent, chemically resistant material for pharmaceutical and optical applications, its coupling with post-treated noble-metal nanostructures for antibacterial functionality has not been systematically described. The main contribution of this study lies in showing that COC can serve not only as a passive packaging substrate, but also as an active platform for the formation of biologically relevant surface nanostructures. Compared with previously reported metal/polymer systems, the present work provides clear evidence that noble-metal layers on COC undergo substantial structural evolution after thermal and excimer-laser treatment, resulting in regular nanoclustered morphologies. A particularly important finding is the detection of Au particle implantation below the COC surface during sputtering, as revealed by Rutherford backscattering spectrometry, which distinguishes this system from conventional surface-only metal coatings. Furthermore, we show that laser and thermal processing do not merely reshape the deposited layer, but significantly influence the final biological response of the material. Ag-based structures showed strong bactericidal behavior against both Gram-negative Escherichia coli and Gram-positive Staphylococcus aureus. The prepared samples were comprehensively characterized by AFM, DSC, RBS, SEM, and TGA, and their roughness and wettability were also evaluated, enabling direct correlation between physicochemical changes and antibacterial performance. These results introduce a new strategy for upgrading conventionally used pharmaceutical COC materials into multifunctional surfaces with added antibacterial value. Full article

FeCrMnNi-based alloys, derived from the well-known Cantor high-entropy alloy, have attracted increasing attention due to their excellent strength–ductility balance. Additively manufactured FeCrMnNi variants are characterized by superior hardness compared to their conventionally processed counterparts. In the present study an optimized composition of the FeCrMnNi medium-entropy alloy was additively manufactured via laser-based powder bed fusion and subsequently subjected to systematic heat treatments. CALPHAD simulations were applied to select the specific composition and post-processing heat treatment conditions, where the latter aimed at promoting the evolution of a dual-phase microstructure. Experimental characterization included X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy, and electron backscatter diffraction, as well as Vickers hardness and tensile testing. A microstructure could be established dominated by a face-centered cubic (FCC) phase with minor fractions of a secondary phase in the non-treated condition. The evolution of an additional body-centered cubic (BCC) phase upon heat treatment at and above 700 °C was observed. The emerging BCC phase as well as increasing fractions of the secondary phase were accompanied by significantly increased hardness and strength, surpassing the literature values of similar compositions. However, a heat treatment at 1000 °C resulted in recrystallization and an increase in grain size, while the decreasing fraction of the secondary phase eventually led to a reduction in strength. These findings underscore the combined potential of composition optimization and targeted post-processing to enhance the mechanical performance of additively manufactured FeCrMnNi alloys. Full article

A Cu-containing FeCrMnNiAl multi-principal element alloy was processed by laser-based and electron beam-based powder bed fusion (PBF-LB/M and PBF-EB/M) to investigate processing–microstructure–property relationships. In focus were alloy variants with a relatively high Cu content. Two PBF-LB/M scan strategies, employing a Gaussian beam with and without a re-scan with a laser featuring a flat-top profile, were compared to PBF-EB/M processing, followed by heat-treatments between 300 °C and 1000 °C. The phase constitution, elemental partitioning and grain boundary characteristics were analyzed by X-ray diffraction, electron backscatter diffraction and energy-dispersive X-ray spectroscopy. Mechanical behavior was assessed by hardness and tensile testing. Both manufacturing routes promoted the evolution of stable multi-phase microstructures composed of face-centered-cubic (FCC)- and body-centered-cubic (BCC)-type phases across all heat-treatment conditions. PBF-LB/M processing resulted in finer, dendritic microstructures and suppressed formation of a Cu-rich FCC phase due to higher cooling rates, whereas PBF-EB/M promoted the evolution of Cu-rich FCC segregates and equiaxed grain morphologies. Heat-treatment above 700 °C led to recrystallization, accompanied by an increase of the FCC phase fraction, grain coarsening, and recovery. At lower heat-treatment temperatures, the changes in microstructure are different. Here, it is assumed that small, non-clustered Cu-rich precipitates formed at the grain and sub-grain boundaries, although this assumption is only based on the assessment of the mechanical properties. The size of these precipitates is below the resolution limit of the techniques applied for analysis in the present work. Additional structures seen within the Cu-rich areas of PBF-EB/M-manufactured samples treated at lower temperatures also seem to have an influence on the hardness and yield strength. All of the conditions investigated exhibited pronounced brittleness, limiting reliable tensile property evaluation and indicating the need for further optimization of processing strategies and microstructural control for high-Cu-fraction-containing multi-principal element alloys. Full article

Beyond supporting ultra-high-capacity data transmission, metropolitan and access networks are expected to enable real-time infrastructure monitoring, driving the emergence of integrated sensing and communication (ISAC). Distributed acoustic sensing (DAS) has proven to be well-suited to urban sensing application requirements, yet its seamless integration into ISAC remains challenging—conventional high-peak-power sensing pulses in DAS induce nonlinear crosstalk in communication channels. DAS inherently suffers from interference fading due to single-frequency laser sources, which limits sensitivity. Here, we propose an ISAC architecture based on an electro-optic (EO) comb and a 7-core fiber, achieving nonlinearity-suppressed self-homodyne transmission and fading-suppressed DAS. Unmodulated comb lines and sensing pulses are polarization-multiplexed into orthogonal polarization states within the central core to minimize nonlinear crosstalk while delivering local oscillators (LOs) for wavelength division multiplexing (WDM) coherent transmission within six outer cores—achieving 10.56 Tbit/s capacity. In addition to supporting WDM transmission, the EO comb’s wavelength diversity is also exploited to enhance DAS performance. Specifically, a dual-pulse probe loaded onto four comb lines yields a 6 dB signal-to-noise ratio gain and a 64% reduction in fading occurrences, achieving a sensitivity of 1.72 $p\epsilon /\sqrt{\mathrm{Hz}}$ with 8 m spatial resolution. Moreover, our system supports simultaneous multi-wavelength backscatter detection in sensing and simplified digital signal processing in self-homodyne communication, reducing receiver complexity and cost. Our work presents a scalable, energy-efficient ISAC framework that unifies high-capacity communication with high-sensitivity sensing, providing a blueprint for future intelligent optical networks. Full article

Distributed fiber optic sensing (DFOS) has emerged as a critical technology for structural health monitoring of large-scale infrastructure, offering unique advantages in terms of coverage and environmental adaptability. This review presents a comprehensive analysis of the two dominant technical routes: fully distributed sensing based on intrinsic backscattering and massive-capacity sensing based on ultra-weak fiber Bragg grating (UWFBG) networks. For backscattering-based systems—encompassing Raman, Brillouin, and Rayleigh scattering—the inherent trade-offs among signal-to-noise ratio (SNR), spatial resolution, and sensing range constitute major performance bottlenecks. This review systematically summarizes advanced demodulation and signal processing strategies designed to overcome these physical barriers, including pulse coding sequences, chaotic laser compressed correlation, and deep learning-enhanced noise reduction algorithms. In parallel, for UWFBG-based technologies, the evolution from traditional multiple-point fiber Bragg grating (FBG) array to quasi-distributed and fully distributed UWFBG network is discussed. This review highlights key breakthroughs in achieving high spatial resolution and high-speed interrogation through hybrid multiplexing, aliased spectrum reconstruction, and dispersion-based demodulation techniques. By synthesizing recent advances in modulation schemes, detection hardware, and algorithmic processing, this paper outlines the trajectory of DFOS technologies toward high-precision, long-distance, and real-time sensing networking. Full article

High residual stresses significantly impact component performance during laser powder bed fusion (L-PBF) of GH3536 alloy. This study systematically investigates the effects of five scanning strategies (X-Scan, XY-Scan, R67, CB90, CB67) on residual stresses and deformation behavior in laser powder bed fusion-formed GH3536 high-temperature alloy. This is achieved by establishing a thermomechanically coupled mesoscale finite element model and combining it with experimental validation. The model was developed on the ANSYS APDL platform using a sequential coupling algorithm. It comprehensively considered melting latent heat, material nonlinearity, and dead-body element technology. While ensuring computational accuracy, significant computational efficiency gains were achieved through geometric scaling and reasonable simplifications (e.g., neglecting evaporation effects and assuming material isotropy). Results indicate that the 67° interlayer rotational scanning (R67) significantly reduces residual stresses, attributed to the breaking of thermal accumulation symmetry by asymmetric scanning. Component deformation is primarily governed by thermal stresses, with simulation results showing less than 10% deviation from experimental measurements. Despite the model’s medium-to-small scale and omission of size effects, its predicted trends highly correlate with X-ray diffraction measurements, validating its reliability for scan strategy optimization. Electron backscatter diffraction (EBSD) analysis further examined grain size and orientation differences at the microstructural level under the R67 strategy, revealing a more refined grain structure and KAM values. This provides theoretical support for L-PBF forming of nickel-based high-temperature alloys. Full article

Distributed acoustic sensing sends laser pulses along a fiber optic cable and analyzes the backscattered light to identify acoustic signals along the entire fiber. Liquid slugs were produced in a 427 m vertical test well using surface-controlled gas lift valves. To enhance DAS monitoring, pressure pulses were induced by multiple acoustic shots from a fluid level gun. Visualization of the responses through frequency band energy plots and unfiltered phase shift measurements permitted tracking slug movement and estimating parameters such as velocity, location, and body length. The results demonstrate that DAS stimulated with acoustic pulses can effectively track liquid slugs in real-time. We observe that relying solely on flow-induced noise in multiphase flow environments may not provide sufficient signal strength for slug detection. Applications include real-time detection of liquid slugs for improved well monitoring and flow management. Full article

Lidar measurements of green laser light traveling inside snow can be modeled using Monte Carlo simulations. These simulations generate databases that link snow properties (such as snow depth and scattering mean free path) with lidar backscatter vertical profile measurements. In this study, these simulated datasets are used to train neural networks to explore the potential for estimating snow properties from ICESat-2 lidar measurements. The networks use simulated snow backscatter profiles as inputs and corresponding snow properties as outputs. Our results indicate that the near-surface portion of the snow backscatter signal contains information relevant to snow depth and scattering mean free path, demonstrating the feasibility of using machine learning frameworks for efficient analysis of spaceborne lidar observations. These findings are presented as a proof-of-concept, with comprehensive external validation and uncertainty quantification identified as future work. Full article

We present a theoretical and numerical investigation of a far-field super-resolution dark-field microscopy technique based on longitudinal nano-optical field excitation and detection. This method is implemented by integrating vector optical field modulation into a back-scattering confocal laser scanning microscope. A complete forward theoretical imaging framework that rigorously accounts for light–matter interactions is adopted and validated. The weak interaction model and general model are both considered. For the weak interaction model, e.g., multiple discrete dipole sources with a uniform or modulated responding intensity are utilized to fundamentally demonstrate the relationship between the sample and the imaging information. For continuous nanostructures, the finite-difference time-domain simulation results of the interaction-induced optical fields in the imaging model show that the captured image information is not determined solely by system resolution and sample geometry, but also arises from a combination of sample-dependent factors, including material composition, the local density of optical states, and intrinsic physical properties such as the complex refractive index. Unlike existing studies, which predominantly focus on system design or rely on simplified assumptions of weak interactions, this paper achieves quantitative characterization and precise regulation of nanoscale vector optical fields and samples under strong interactions through a comprehensive analytical–numerical imaging model based on rigorous vector diffraction theory and strong near-field coupling interactions, thereby overcoming the limitations of traditional methods. Full article