Search Results (32,314)

In this work, Laser Powder Bed Fusion (LPBF), an additive manufacturing (AM) process, was optimised to produce pure magnesium components. The focus of the presented work is on the prediction of the relative product density using the machine learning model XGBoost to improve the production process and thus the usability of the material for practical use. Experimental tests with different parameters, laser power, scanning speed and layer thickness, and fixed parameters, track overlapping and hatching distance, were analysed and resulted in relative material densities between 89.29% and 99.975%. The XGBoost model showed high predictive power, achieving an R² test result of 0.835, a mean absolute error (MAE) of 0.728 and a root mean square error (RMSE) of 0.982. Feature importance analysis showed that the interaction of laser power and scanning speed had the largest influence on the predictions at 35.9%, followed by laser power × layer thickness at 29.0%. The individual contributions were laser power (11.8%), scanning speed (10.7%), scanning speed × layer thickness (9.0%) and layer thickness (3.6%). These results provide a data-based method for LPBF parameter settings that improve manufacturing efficiency and component performance in the aerospace, automotive and biomedical industries and identify optimal parameter regions for a high density, serving as a pre-optimisation stage. Full article

Due to the limitations of high speed and short time in plasma-spraying experiments, this study established a simulation model of Y₂O₃ multi-particle deposition to discuss the influence of laser loading on coating-deposition behavior and performance. According to the simulation results, the temperature of coating particles under laser loading displays a gradient distribution, with the surface having the highest temperature. The particles deposit on the substrate to form uniform pits of a certain depth. Plastic deformation causes maximum stress to occur at the edges of the pits and maximum strain to occur on the sidewall of the pits. The deposition region had both compressive and tensile stresses, and laser loading greatly reduced the tensile stresses’ magnitude while having less of an impact on the particle strains. Laser assistance promotes further melting of particles, reduces coating thickness, lowers coating porosity to 3.94%, increases hardness to 488 MPa, reduces maximum pore size from 68 µm to 32 µm, and causes particle sputtering to gradually evolve from being disc-shaped to being finger-shaped, creating cavities at the coating edges. The comparison between the surface morphology and the cross-section pores of the experimentally prepared coating verified the rationality and viability of the simulation work. Full article

Accurate melt pool geometry prediction is essential for ensuring quality and reliability in Laser Powder Bed Fusion (L-PBF). However, small experimental datasets and limited physical interpretability often restrict the effectiveness of traditional machine learning (ML) models. This study proposes a hybrid framework that integrates an explicit thermal model with ML algorithms to improve prediction under sparse data conditions. The explicit model—calibrated for variable penetration depth and absorptivity—generates synthetic melt pool data, augmenting 36 experimental samples across conduction, transition, and keyhole regimes for 316 L stainless steel. Three ML methods—Multilayer Perceptron (MLP), Random Forest, and XGBoost—are trained using fivefold cross-validation. The hybrid approach significantly improves prediction accuracy, especially in unstable transition regions (D/W ≈ 0.5–1.2), where morphological fluctuations hinder experimental sampling. The best-performing model (MLP) achieves R² > 0.98, with notable reductions in MAE and RMSE. The results highlight the benefit of incorporating physically consistent, nonlinearly distributed synthetic data to enhance generalization and robustness. This physics-augmented learning strategy not only demonstrates scientific novelty by integrating mechanistic modeling into data-driven learning, but also provides a scalable solution for intelligent process optimization, in situ monitoring, and digital twin development in metal additive manufacturing. Full article

To investigate the effect of liquid-phase laser ablation on the hardness of WC-Co cemented carbide, this study performed hardness testing, elemental distribution analysis, and XRD phase analysis. The influence of ablation times on the hardness, elemental distribution, and phase composition of WC-Co cemented carbide was examined, and a model describing the hardness evolution mechanism under liquid-phase laser ablation was proposed. The results demonstrated that the hardness of WC-Co cemented carbide increased with the number of ablations. After 14 ablation times, the maximum hardness reached 2800 HV, representing an increase of 51%–56% compared to the matrix hardness. As the number of ablations increased, the content of ditungsten carbide (W₂C) and tungsten carbide (WC) in the cemented carbide increased, the WC grain size decreased, the dislocation density increased, and the distribution became more uniform. The refinement of WC grains and the elevated dislocation density facilitated stronger intergranular bonding, thereby significantly enhancing the material’s hardness. This study provides theoretical guidance for improving the surface mechanical properties of WC-Co cemented carbide tools through liquid-phase laser ablation. Full article

In this paper, SiC and Si/SiC ceramics were fabricated using direct laser powder bed fusion with chemical vapor infiltration. Their microstructure, mechanical properties and the impacts of silicon addition were analyzed. The incorporation of silicon led to an increase in the relative density of the silicon carbide ceramics from 76.4% to 78.3% and the compression strength increased from 39 ± 13 MPa to 90 ± 8 MPa after laser powder bed fusion with chemical vapor infiltration. The melting and re-solidification of silicon allows the silicon to encapsulate the silicon carbide grains, changing the microstructure and the failure mechanism of the silicon carbide ceramics, resulting in a small amount of silicon residue. In the LPBF-CVI SiC ceramic specimen, the LPBF-formed SiC exhibits a microhardness of 24.2 ± 1.0 GPa. In LPBF-CVI Si/SiC, the spherical dual-phase structure displays a moderately increased hardness (25.9 ± 4.4 GPa), and the CVI-formed SiC exhibits a hardness of 55.3 ± 9.3 GPa. Full article

Lotus (Nelumbo nucifera Gaertn.) is a quintessential medicinal and edible plant, exhibiting marked differences in therapeutic effects among its various parts. The lotus seed constitutes a key component of this plant. Notably, the entire seed and the plumule display distinct medicinal properties. To investigate the “homologous plants with different effects” phenomenon in traditional Chinese medicine, this study established a Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) method. This study employed immature lotus seeds as the experimental material, diverging from the mature seeds conventionally used. Conductive double-sided tape was employed for sample preparation, and complete longitudinal sections of the seeds were obtained, followed by MALDI-MSI analysis to identify and visualize the spatial distribution of characteristic secondary metabolites within the entire seeds. The results unveiled the diversity of metabolites in lotus seeds and their differential distribution across tissues, with pronounced distinctions in the plumule. A total of 152 metabolites spanning 13 categories were identified in lotus seeds, with 134, 89, 51, and 98 metabolites discerned in the pericarp, seed coat, cotyledon, and plumule, respectively. Strikingly, young lotus seeds were devoid of liensinine/isoliensinine and neferine, the dominant alkaloids of mature lotus seed plumule, revealing an early-stage alkaloid profile that sharply contrasts with the well-documented abundance found in mature seeds and has rarely been reported. We further propose a biosynthetic pathway to explain the presence of the detected benzylisoquinoline and the absence of the undetected bisbenzylisoquinoline alkaloids in this study. These findings present the first comprehensive metabolic atlas of immature lotus seeds, systematically exposing the pronounced chemical divergence from their mature counterparts, and thus lays a metabolomic foundation for dissecting the spatiotemporal mechanisms underlying the nutritional and medicinal value of lotus seeds. Full article

This study synthesizes and comparatively investigates two squaric acid-based phthalocyanine-like dyes, SNF and its long-chain alkylated derivative LNF, to systematically elucidate the influence of peripheral hydrophobic groups on their third-order nonlinear optical (NLO) properties. The NLO characteristics were comprehensively characterized using femtosecond Z-scan and I-scan techniques at both 800 nm and 900 nm. Both dyes exhibited strong saturable absorption (SA), confirming their potential as saturable absorbers. Critically, the comparative analysis revealed that SNF exhibits a significantly greater nonlinear absorption coefficient (β) compared to LNF under identical conditions. For instance, at 800 nm, the β of SNF was approximately 3–5 times larger than that of LNF. This result conclusively demonstrates that the introduction of long hydrophobic alkyl chains attenuates the NLO response. Furthermore, I-scan measurements revealed excellent SA performance, with high modulation depths (e.g., LNF: 43.0% at 900 nm) and low saturation intensities. This work not only clarifies the structure–property relationship in these D-A-D dyes but also presents a clear strategy for modulating the NLO properties of organic chromophores for applications in near-infrared pulsed lasers. Full article

Stress fields imparted with an ultrafast laser can correct low spatial frequency surface figure error of mirrors through ultrafast laser stress figuring (ULSF): the formation of nanograting structures within the bulk substrate generates localized stress, creating bending moments that equilibrize via wafer deformation. For ULSF to be used as an optical figuring process, the ultrafast laser generated stress must be effectively permanent or risk unwanted figure drift. Two isochronal annealing experiments were performed to measure ultrafast laser-generated stress stability in fused silica and Corning ultra-low expansion (ULE) wafers. The first experiment tracked changes to induced astigmatism up to 1000 °C on 25.4 mm-diameter wafers. Only small changes were measured after each thermal cycle up to 500 °C for both materials, but significant changes were observed at higher temperatures. The second experiment tracked stress changes in fused silica and ULE up to 500 °C but with 4 to 16× higher signal-to-noise ratio. Change in trefoil on 100 mm-diameter wafers was measured, and the induced stress in fused silica and ULE was found to be stable after thermal cycling up to 300 °C and 200 °C, respectively, with larger changes at higher temperatures. Full article

Image processing has been widely adopted as an effective technology for analyzing weld forming quality which is greatly affected by the welding process parameters. In this paper, an L₂₅(5³) orthogonal experiment is designed to investigate the effects of welding process parameters on the weld forming quality in laser welding of aluminum alloy. The weld characteristics including the weld width (WW), weld penetration (PD), weld area (WA) and weld porosity (WP) under the conditions of the different welding process parameters consisting of the laser power (LP), welding speed (WS) and defocus distance (DD) are extracted from the laser welding experiment based on image processing. The effectiveness of the weld characteristics extraction method is verified by comparing the extracted results with the measured results. It is found that the WW, PD and WA are all significantly influenced by the LP among the three welding process parameters while the influences of the three process parameters on the WP are insignificant. The DD has a significant influence on the PD and the WS has a significant influence on the WA. The corresponding significance of influence is lower than the significance of influence of LP. The analysis results are conducive to the optimization of laser welding process parameters and improvement of welding quality. Full article

Carbon deposits on the crown of engine pistons can markedly reduce combustion efficiency and shorten service life. Conventional cleaning techniques often fail to simultaneously ensure a high carbon removal efficiency and maintain optimal surface integrity. To enable efficient and precise carbon removal, this study proposes the application of hybrid laser cleaning—combining continuous-wave (CW) and pulsed lasers—to piston carbon deposit removal, and employs response surface methodology (RSM) for multi-objective process optimization. Using the N52B30 engine piston as the experimental substrate, this study systematically investigates the combined effects of key process parameters—including CW laser power, pulsed laser power, cleaning speed, and pulse repetition frequency—on surface roughness (Sa) and carbon residue rate (RC). Plackett–Burman design was employed to identify significant factors, the method of the steepest ascent was utilized to approximate the optimal region, and a quadratic regression model was constructed using Box–Behnken response surface methodology. The results reveal that the Y-direction cleaning speed and pulsed laser power exert the most pronounced influence on surface roughness (F-values of 112.58 and 34.85, respectively), whereas CW laser power has the strongest effect on the carbon residue rate (F-value of 57.74). The optimized process parameters are as follows: CW laser power set at 625.8 W, pulsed laser power at 250.08 W, Y-direction cleaning speed of 15.00 mm/s, and pulse repetition frequency of 31.54 kHz. Under these conditions, the surface roughness (Sa) is reduced to 0.947 μm, and the carbon residue rate (RC) is lowered to 3.67%, thereby satisfying the service performance requirements for engine pistons. This study offers technical insights into the precise control of the hybrid laser cleaning process and its practical application in engine maintenance and the remanufacturing of end-of-life components. Full article

In this study, a novel direct laser beam turning (DLBT) approach is proposed for the precision machining of AISI 308L austenitic stainless steel, which eliminates the need for cutting tools and thereby eradicates tool wear and vibration-induced surface irregularities. A nanosecond-pulsed Nd:YAG fiber laser (λ = 1064 nm, spot size = 0.05 mm) was used, and Ø1.6 mm × 20 mm cylindrical rods were processed under ambient conditions without auxiliary cooling. The experimental framework systematically evaluated the influence of scanning speed, pulse frequency, and the number of laser passes on dimensional accuracy and material removal efficiency. The results indicate that a maximum diameter reduction of 0.271 mm was achieved at a scanning speed of 3200 mm/s and 50 kHz, whereas 0.195 mm was attained at 6400 mm/s and 200 kHz. A robust second-order polynomial correlation (R² = 0.99) was established between diameter reduction and the number of passes, revealing the high predictability of the process. Crucially, when the scanning speed was doubled, the effective fluence was halved, considerably influencing the ablation characteristics. Despite the low fluence, evidence of material evaporation at elevated frequencies due to the incubation effect underscores the complex photothermal dynamics governing the process. This work constitutes the first comprehensive quantification of pass-dependent diameter modulation in DLBT and introduces a transformative, noncontact micromachining strategy for hard-to-machine alloys. The demonstrated precision, repeatability, and thermal control position DLBT as a promising candidate for next-generation manufacturing of high-performance miniaturized components. Full article

This article provides a comprehensive overview of recent studies concerning laser heat treatment (LHT) of structural and tool steels, with particular attention to the 21NiCrMo2 steel used for carburized gear wheels. Analysis includes the influence of critical laser processing conditions—including power output, motion speed, spot size, and focusing distance—on surface microhardness, hardening depth, and microstructure development. The findings indicate that the energy density is the dominant factor that affects the outcomes of LHT. Optimal results, in the form of a high surface microhardness and a sufficient depth of hardening, were achieved within the energy density range of 80–130 J/mm², allowing for martensitic transformation while avoiding defects such as melting or cracking. At densities below 50 J/mm², incomplete hardening occurred with minimal microhardness improvement. On the contrary, densities exceeding 150–180 J/mm² caused surface overheating and degradation. For carburized 21NiCrMo2 steel, the most effective parameters included 450–1050 W laser power, 1.7–2.5 mm/s scanning speed, and 2.0–2.3 mm beam diameter. The review confirms that process control through energy-based parameters allows for reliable prediction and optimization of LHT for industrial applications, particularly in components exposed to cyclic loads. Full article

Quantum sensing based on NV-centers in diamonds has been demonstrated many times in multiple publications. The majority of publications use lasers in free space or lasers with fiber optics, expensive optical components such as dichroic mirrors, or beam splitters with dichroic filters and expensive detectors, such as Avalanche photodiodes or single photon detectors, overall, leading to custom and expensive setups. In order to provide an inexpensive NV-based magnetometer setup for educational use in schools, to teach the three topics, fluorescence, optically detected magnetic resonance, and Zeeman splitting, inexpensive, miniaturized, off-the-shelf components with high reliability have to be used. The cheaper such a setup, the more setups a school can afford. Hence, in this work, we investigated LEDs as light sources, considered different diamonds for our setup, tested different color filters, proposed an inexpensive microwave resonator, and used a cheap photodiode with an appropriate transimpedance amplifier as the basis for our quantum magnetometer. As a result, we identified cheap and functional components and present a setup and show that it can demonstrate the three topics mentioned at a hardware cost <EUR 100. Full article

Over three decades of research has been undertaken on point cloud registration algorithms, resulting in mature theoretical frameworks and methodologies. However, among the numerous registration techniques used, the impact of point cloud scanning quality on registration outcomes has rarely been addressed. In most engineering and industrial measurement applications, the accuracy and density of LiDAR point clouds are highly dependent on laser scanners, leading to significant variability that critically affects registration quality. Key factors influencing point cloud accuracy include scanning distance, incidence angle, and the surface characteristics of the target. Notably, in short-range scanning scenarios, incidence angle emerges as the dominant error source. Building on this insight, this study systematically investigates the relationship between scanning incidence angles and point cloud quality. We propose an incident-angle-dependent weighting function for point cloud observations, and further develop an improved weighted Iterative Closest Point (ICP) registration algorithm. Experimental results demonstrate that the proposed method achieves approximately 30% higher registration accuracy compared to traditional ICP algorithms and a 10% improvement over Faro SCENE’s proprietary solution. Full article

Background: Previous research has demonstrated that 20 kHz probe or 37 kHz bath sonication of poloxamers comprising polypropylene glycol (PPG) and polyethylene glycol (PEG) blocks can generate degradation byproducts that are toxic to mammalian cells and organisms. Herein, an investigation of a PEGylated phospholipid micelle was undertaken to identify low-molecular-weight sonolytic degradation byproducts that could be cytotoxic. The concern here lies with the fact that sonication is a frequently employed step in drug delivery manufacturing processes, during which PEGylated phospholipids can be subjected to shear forces and other extreme oxidative and thermal conditions. Methods: Control and 20 kHz-sonicated micelles of DSPE-mPEG2000 were analyzed using dynamic light scattering (DLS) and zeta potential analyses to study colloidal properties, matrix-assisted laser desorption/ionization–time of flight (MALDI-TOF) mass spectroscopy (MS) and proton nuclear magnetic resonance (¹H-NMR) spectroscopy to study the structural integrity of DSPE-mPEG2000, and ¹H-NMR spectroscopy and high-performance liquid chromatography (HPLC) with ultraviolet (UV) detection to quantitate the formation of low-molecular-weight degradation byproducts. Results: MALDI-TOF-MS analyses of 20 kHz-sonicated DSPE-mPEG2000 revealed the loss of ethylene glycol moieties in accordance with depolymerization of the PEG chain; ¹H-NMR spectroscopy showed the presence of formate, a known oxidative/thermal degradation product of PEG; and HPLC-UV showed that the generation of formate was dependent on 20 kHz probe sonication time between 5 and 60 min. Conclusions: It was found that 20 kHz sonication can degrade the PEG chain of DSPE-mPEG2000, altering the micelle’s PEG corona and generating formate, a known ocular toxicant. Full article