Search Results (994)

Femtosecond laser surface texturing offers a promising route to tailor the functionality of bio-based wood coatings, yet the interplay between coating composition and laser processing remains poorly understood. In this study, bio-based epoxy coatings with eventual micronized wax additives were textured using a femtosecond laser to investigate the effects of laser processing parameters on pattern formation and resulting hydrophobicity. The epoxy coatings containing PE, PE/PTFE, HDPE, and rice bran waxes at 1, 5, and 7 wt.-% were characterized in terms of morphology, roughness, wettability, and chemical stability, followed by systematic variation of pulse repetition rate and laser power. The results reveal that the ablation threshold strongly depends on intrinsic coating properties. Ablation resistance increases with surface roughness and wax melting enthalpy, reflecting the role of phase transition energy in laser–matter interaction. The wax-filled coatings exhibit a transition from melting-dominated behavior at low energy input to ablation-dominated behavior at a higher energy. Laser texturing enhances hydrophobicity in parallel with theoretical values calculated from the Cassie–Baxter wetting model, with the highest hydrophobicity achieved for coatings combining intrinsic hydrophobicity and stable pattern formation. Chemical analysis confirms limited degradation of the epoxy matrix without significant carbonization, while wax additives provide partial thermal shielding. Overall, this work demonstrates clear options for tailoring surface morphology and wettability of hydrophobic polymer coatings through controlled femtosecond laser processing. Full article

The manuscript deals with the bending behavior of beams with relatively less investigated cellular topologies based on triply periodic minimal surfaces (TPMSs). Three types of sandwich-type specimens (namely Schoen IWP, Fischer–Koch S, and Schoen F-RD) with five different volume fractions of 10, 15, 20, 25, and 35% (±1%) made of aluminum alloy AlSi10Mg by selective laser melting (SLM) technology were investigated. Three-point bending tests were performed at room temperature on a Zwick/Roell 1456 universal testing machine. The force–deflection dependences were plotted, while in addition to nominal stresses, the effective flexural stiffness and energy absorption to failure were evaluated to compare the properties of the investigated cellular beams. In the preparatory phase, critical aspects of possible premature failure of the samples with the smallest and highest selected volume fractions were addressed, while the manufacturability and fracture surfaces of the samples were assessed in order to improve the input conditions of the setup. By comparing the results obtained in the experimental testing in the second phase, it was found that the highest nominal bending stresses were achieved by the Schoen F-RD structure (although not significantly higher than Fischer–Koch S), but in terms of stiffness and amount of absorbed energy, the Fischer–Koch S structure showed the highest values. The improvement of input parameters led to an increase in the achieved nominal bending stresses by at least 100 MPa for all types of investigated structures compared to the first phase. The combined use of preliminary SLM process optimization, bending tests, and fracture surface/EDX analysis made it possible to relate the flexural response of the investigated TPMS topologies to manufacturing-related defects and premature-failure mechanisms in thin-walled AlSi10Mg cellular structures. The presented specimen configuration is intended as a comparative experimental benchmark for flexural performance of sandwich-type TPMS beams under quasi-static loading. Full article

Titanium alloys such as Ti-6Al-4V are widely used in orthopedic implants due to their strength and biocompatibility. Laser Surface Remelting (LSR) offers a promising approach to modify surface properties without altering bulk characteristics. This study investigates the effects of varying melt pool depths (MPDs) from 0 μm to 30 μm in 10 μm steps on the mechanical behavior of Ti-6Al-4V femoral components in Total Knee Replacement (TKR) using a comprehensive computational approach combining Finite Element Analysis (FEA) and computational algorithm-based automated evaluation. A three-dimensional FEA model was developed and tested under four physiological loading conditions: compression, axial distraction, medial bending, and lateral flexion at 1300 N. Results show that increasing MPD from 0 μm to 30 μm increases the maximum von Mises stress by 4.2% under compression but reduces displacement by up to 51.7% under distraction. An MPD of 20 μm reduces displacement by 48% while increasing stress by only 2.7%, representing an optimal balance. The computational algorithm framework identifies 15–25 μm as the optimal range for balancing surface enhancement with mechanical integrity. Experimental validation shows good agreement between simulated and measured results, confirming the reliability of the proposed framework for optimizing surface modification parameters in orthopedic implants. Full article

Aiming at the technical bottleneck that traditional porous structures can hardly achieve mechanical load-bearing and acoustic regulation simultaneously, this study designs and fabricates three implicit surface porous structures (Gyroid, Diamond, Lidinoid) based on the bionic principle of trabecular bone. Experimental characterization and numerical analysis of their mechano-acoustic coupling performance are systematically carried out. Selective Laser Melting (SLM) technology is employed to realize the integrated forming of 316L bionic structures. Quasi-static compression experiments and finite element simulations are conducted to reveal the progressive deformation mechanism and energy absorption characteristics of different topological configurations. The results indicate that the Diamond structure exhibits the optimal comprehensive performance in terms of load-bearing capacity, specific energy absorption and isotropy. On this basis, the sound absorption and sound insulation performances of the structures are evaluated via an acoustic impedance tube test. The results show that the Diamond structure possesses a remarkably higher sound absorption coefficient and sound insulation value in the high-frequency range than other configurations, demonstrating excellent acoustic energy dissipation and sound wave isolation capability. The research indicates that the synergistic optimization of mechanical and acoustic performances can be achieved by regulating the Triply Periodic Minimal Surface (TPMS) topological configuration. Benefiting from its efficient stress transfer paths and intricate sound wave propagation channels, the Diamond structure realizes the coupling of high load-bearing capacity, superior energy absorption and favorable acoustic performance. This work provides a theoretical basis and technical support for the design of bionic porous structures in multifunctional scenarios such as bone implants and protective noise reduction. Full article

Laser Powder Bed Fusion (LPBF) is a complex manufacturing process that depends on precise control of printing parameters and melt pool geometry, which directly influence defect formation and final part quality. This study evaluated the reliability of a simplified thermal conduction-based melt pool model by combining post-process metallographic analysis with in situ dual-wavelength infrared thermal imaging. Experimental data were obtained through single-track printing on 316L, IN625, and CoCr alloys across a wide range of parameters. The simulated melt pool length showed strong agreement with thermal camera measurements (R²_adj > 0.78), while the width showed moderate but consistent correlation (R²_adj > 0.52). For melt pool depth, the model systematically deviated due to its inability to capture keyhole melting, although a strong linear correlation was still observed (R²_adj > 0.86). Cross-validation between metallographic measurements and thermal imaging revealed only a 6–9% discrepancy, confirming the reliability of both methods and the potential of dual-wavelength cameras for industrial process monitoring. Overall, the model proves to be a reliable tool for predicting melt pool surface geometry specifically within the conduction melting regime, while its predictive capability degrades significantly in the keyhole regime, where simulated peak temperatures reach up to 7000 °C and melt pool depth errors escalate due to the disregard of recoil pressure, liquid and vapor dynamics. Full article

The influence of internal substrate geometry on thermal stability during Laser Directed Energy Deposition Repair (DED-R) remains insufficiently understood, particularly for components containing internal cavities and cooling channels. This study investigates the thermal response of solid (Alpha), blind-hole (Bravo), and channeled (Charlie) AISI 316L substrates using dual infrared thermography, transient finite element modeling, and Short-Time Fourier Transform (STFT)-frequency-domain analysis. Despite substantial differences in internal heat-dissipation pathways, all substrate configurations exhibited similar peak surface temperatures (~1700–2100 °C), indicating that conventional temperature monitoring alone is insufficient to distinguish geometry-dependent melt-pool behavior. To address this limitation, a Spectral Entropy Index (SEI) derived from STFT analysis was proposed to quantify thermal stability. The channeled substrate exhibited the lowest entropy value (H_s = 0.172), compared with the solid (H_s = 0.181) and blind-hole (H_s = 0.183) configurations, indicating a more ordered and predictable thermal response. Furthermore, distinct variations in the spectral stability shadow revealed geometry-dependent oscillatory behavior that was not observable from thermal histories. Finite element simulations showed good agreement with experimental measurements in conduction-dominated regions (RMSE ≈ 46 °C), whereas deviations were observed within the melt-pool region (~250–310 °C), highlighting the increasing influence of fluid-flow phenomena not captured by the conduction-based model. The results demonstrate that internal substrate architecture primarily influences melt-pool stability through frequency-domain thermodynamics rather than significant changes in peak temperature. The proposed STFT method provides a quantitative approach for monitoring thermal stability and assessing the feasibility of L-DED repair over complex internal geometries. Full article

Laser powder bed fusion (L-PBF) has emerged as a core metal additive manufacturing technology for high-end sectors, including aerospace and medical device manufacturing. However, melting anomalies that occur during fabrication accumulate layer by layer, leading to degraded surface quality and impaired mechanical performance of as-built components—a critical bottleneck limiting their large-scale industrial adoption. Accurate and robust layer-wise melting quality recognition remains a challenge due to the complex surface morphologies induced by such melting anomalies. This study presents a machine learning-enabled in situ monitoring approach for layer-wise melting quality identification in L-PBF. By systematically varying laser power and scanning speed, 24 parameter combinations were designed to fabricate specimens with three distinct melting states: over-melting (OM), lack of fusion (LOF), and normal melting. A high-resolution complementary meta–oxide–semiconductor (CMOS) camera was used to capture layer-wise surface images of the specimens, and following abnormal layer filtering and manual validation, a high-quality dataset comprising 5110 layer-wise images was constructed. Two mainstream machine learning approaches were systematically evaluated and optimized for melting quality classification: a support vector machine (SVM) model leveraging handcrafted gray-level co-occurrence matrix (GLCM) texture features achieved a classification accuracy of 96.77%, while a convolutional neural network (CNN) model with end-to-end feature learning directly from raw images attained a superior accuracy of 98.14%. In terms of computational efficiency, the CNN model exhibited a faster inference speed with a per-layer inference time of just 0.036 s, nearly half that of the SVM model (0.068 s per layer). Most critically, the CNN model completely eliminated fatal cross-class misclassification between OM and LOF—an error mode common in the SVM model that would trigger erroneous process corrective actions in practical industrial applications. The findings demonstrate that image-based machine learning provides a reliable technical foundation for intelligent in situ monitoring of the L-PBF process. With its high accuracy, strong robustness, and superior computational efficiency, the CNN model can effectively support on-site operational decision-making, reduce material and time losses, and enhance process stability in industrial settings, thus exhibiting significant potential for practical engineering deployment. Full article

Additive manufacturing (AM) introduces surface roughness that is much larger than that in chemically etched printed circuit heat exchanger (PCHE) channels, limiting the applicability of established design correlation. In this study, four selective laser melting (SLM) 3D-printed stainless steel test sections were tested, namely two semicircular and two rounded-edge semicircular channels, at hydraulic diameters of 2 mm and 4 mm. Water was used as the test fluid in the experiment, with a Reynolds number ranging from 500 to 7000 and wall heat flux ranging from 20 to 90 kW/m². Scanning electron microscopy image characterization shows significant material accumulation concentrated at the rounded edges of the as-built channels. The experimental results show that for the entire flow regime, the printed rounded edge increases the friction factor by approximately 9% for 2 mm and 4 mm channels. The filleting design would increase the effective hydraulic roughness in small-diameter AM channels. The SLM 3D-printed rougher channel has a lower transition Reynolds number and higher turbulent friction factors compared to the etching channel. The data were compared with existing smooth PCHE channel data and rough AM mini-channel correlation, and two empirical correlations were developed for SLM 3D-printed mini-channels for transition and turbulent regimes. Full article

Joining dissimilar polymers such as polypropylene (PP) and high-density polyethylene (HDPE) remains a challenge in modern manufacturing due to their incompatible thermal properties and poor interfacial bonding. In this study, a novel hybrid structure was fabricated by laser welding of PP to an HDPE matrix reinforced with 3 wt% carbon nanotubes (CNTs). The CNTs were incorporated via fused filament fabrication (FFF) 3D printing to raise the melting temperature and thermal stability of HDPE, thereby minimizing the thermal mismatch with PP. A pulsed CO₂ laser was used to perform butt welding, and the influences of pulse frequency, welding speed, and laser power on the elastic modulus and tensile properties of the weld samples were thoroughly studied. A response surface design was employed to build predictive models and perform multi-objective optimization. The addition of CNTs, as evidenced by differential scanning calorimetry (DSC), elevated the crystallinity level of HDPE from 48.3% to 53.1% and the melting point from 137.8 to 140.8 °C, making its thermal properties more comparable to those of PP. Observations via scanning electron microscopy (SEM) indicated that when the optimal parameters were applied (pulse frequency: 35 Hz, welding speed: 21 mm/s, and laser power: 49 W), the joint line was defect-free, fully fused, and contained very few voids. At these settings, the model estimated an elastic modulus of 793 MPa and a tensile strength of 49.6 MPa, while confirmation experiments yielded 47.2 MPa and 764.5 MPa, respectively, with relative errors below 5%. The results demonstrate that the combination of CNT-assisted laser welding and RSM-driven optimization effectively resolves the thermal incompatibility of HDPE and PP, thereby facilitating high-quality joining of dissimilar polymers for applications in packaging and automotive fields. Full article

Surface defects in additively manufactured internal channels limit their practical applications. Conventional post-processing methods suffer from limited accessibility and a tendency toward over-polishing, whereas magnetic abrasive finishing (MAF) offers high adaptability and precise process controllability. This study systematically investigates the material removal mechanisms in magnetic abrasive polishing and clarifies the distinctions and transitions between two-body and three-body wear modes. Based on these findings, a rolling removal model grounded in rough surface contact theory and a sliding removal model incorporating correction factors are established. Experiments were conducted on AlSi10Mg internal channels fabricated via selective laser melting (SLM) using a composite magnetic field polishing apparatus. The results verify the accuracy of the proposed models and demonstrate that the process effectively reduces surface defects and surface roughness. Although some deviations arise from model idealization and non-uniform magnetic field distribution, this study establishes a systematic theoretical framework for material removal in additively manufactured complex internal channels. Full article

Al₂O₃ single beads were deposited on a Ti-6Al-4V (Ti64) substrate by laser-directed energy deposition (DED-LB) to establish baseline process conditions for ceramic protective layers and future Ti64/Al₂O₃ functionally graded materials (FGMs). These ceramic-containing surface layers are applicable to titanium components requiring improved oxidation, wear, and thermal resistance in aerospace, automotive, and high-temperature structural applications. Laser power (300–700 W) and scan speed (300–700 mm/min) were varied, and bead geometry was quantified from cross-sectional observations; energy density and dilution ratio were calculated. Melt pool depth increased with higher power and lower speed, indicating increased heat input and substrate melting. Crack formation in the melt zone was more sensitive to laser power than to scan speed. In contrast, bead height showed a non-monotonic response to energy density, which may be associated with possible coupled effects such as recoil pressure-driven melt pool disturbance, powder scattering, and insufficient powder melting at high scan speeds. Dilution-based optimization identified 300 W laser power and 400 mm/min scan speed, with a powder feed rate of 3 g/min, as the most suitable condition within the investigated process window, giving the lowest practical dilution ratio of approximately 40.27%. SEM–EDS and XRD analyses were conducted to examine the interfacial microstructure and phase characteristics under the selected condition. Overall, this study provides fundamental process guidelines and mechanistic insight into bead formation, dilution behavior, and interface formation, supporting the future application of DED-LB-based ceramic protective or graded layers on Ti64 surfaces. Full article

The present work compares the corrosion performance of additively manufactured (AM) Ti-6Al-4V ELI (Extra-Low Interstitials) alloy manufactured by Laser-Powder Bed Fusion (L-PBF) using virgin powder (Cycle 1/C1 sample) and reused powder feedstock after up to 34 cycles (Cycle 34/C34 sample) of manufacturing. The effect of powder reuse is also evaluated for anodizing and Flash-PEO-coated specimens in Harrison’s (25 °C) and Hanks’ solutions (37 °C), representing simulated atmospheric precipitation and physiological conditions, respectively. Specimens were characterized using common metallographic techniques, X-ray diffraction, scanning electron microscopy and optical profilometry. Corrosion resistance was evaluated using cyclic potentiodynamic polarization (PDP) tests. The oxygen content in the Ti-6Al-4V reaches 0.14 wt.% after 34 cycles (C34) of powder reuse, enhancing its passivity in both Harrison’s and Hanks’ solutions. Both virgin and reused powder builds are susceptible to localized corrosion in Hanks’ solution at potentials above 1.75 V. Melt pool borders are thought to be the preferential sites for localized corrosion, as indicated by Volta potential measurements (ΔV = 100 mV). The number of cycles does not significantly affect the current–voltage responses for anodizing and flash-Plasma Electrolytic Oxidation (Flash-PEO) treatments, although anodizing is slightly more responsive to variations in surface roughness (i.e., real specimen area). Anodizing and Flash-PEO reduce the passive current density by nearly two orders of magnitude. Even after surface treatment, the alloy printed with reused powder revealed better passivity. Flash-PEO coatings yielded significant protection against localized corrosion. This unlocks Flash-PEO processing as a successful protection approach for AM biomedical components. Full article

Wire laser cladding (WLC) of bronze on stainless steel offers a promising approach for combining the structural strength of steel with the superior tribological and corrosion properties of copper alloys. In this study, the influence of key process parameters, including wire preheating current, deposition speed, laser power, and wire feed speed on melt pool temperature and clad geometry was investigated using response surface methodology (RSM). Experiments were performed using a robot-assisted coaxial wire feeding laser cladding system, and real-time thermal monitoring was conducted using an infrared camera. The results showed that defect-free bronze clads with good metallurgical bonding and limited dilution were achieved across the investigated parameter range. Statistical analysis revealed that melt pool temperature is primarily governed by laser power and deposition speed, with a significant interaction between these parameters. Clad height was mainly influenced by wire feed speed and deposition speed, whereas clad width was controlled by laser power and deposition speed. The side angle was affected by deposition speed, laser power, and wire feed speed, reflecting the balance between vertical buildup and lateral spreading. Overall, the study demonstrates that stable and high-quality clads can be achieved by properly balancing energy input and material supply. The developed models provide valuable insight for optimizing process parameters in wire laser cladding of bronze on stainless steel. Full article

This study addresses a persistent challenge in polymer joining: the laser welding of two incompatible thermoplastics, polypropylene (PP) and high-density polyethylene (HDPE). The key innovation lies in modifying HDPE with 3 wt% graphene nanoplatelets (GNPs) via material extrusion (MEX), which raises its melting temperature from 136.8 °C to 138.8 °C and increases crystallinity from 46.9% to 51.4%, as confirmed by differential scanning calorimetry (DSC). This thermal adjustment brings HDPE closer to PP’s melting behavior, enabling effective laser butt welding using a pulsed CO₂ laser. A Box–Behnken design within response surface methodology (RSM) was employed to model the individual and interactive effects of laser power (30–50 W), welding speed (15–25 mm/s), and pulse frequency (25–35 Hz) on the flexural and impact strength of the welded joints. Scanning electron microscopy (SEM) revealed that optimal welding conditions—laser power of 49 W, welding speed of 20 mm/s, and pulse frequency of 35 Hz—produce a defect-free interface with complete polymer chain interdiffusion. Under these optimized conditions, the regression models predicted a flexural strength of 69.7 MPa and an impact strength of 21.9 kJ/m². Confirmation experiments yielded 68.2 MPa and 22.6 kJ/m², with relative errors below 4%, validating the predictive capability of the models. This work demonstrates that GNP-mediated thermal property modification, coupled with statistical process optimization, offers a viable pathway for manufacturing high-performance dissimilar polymer joints for lightweight structural applications. Full article

Selective laser melting (SLM) offers significant potential for fabricating lightweight 316L stainless steel lattice structures (LSs), while forming defects and microstructural heterogeneity remain challenging, especially in fine struts. In this study, response surface methodology (RSM) and analysis of variance (ANOVA) were employed to quantify the coupled effects of geometric parameters (forming angle, FA; rod diameter, RD) and processing parameters (laser power, LP; scanning speed, SS; hatch spacing, HS) on the mass deviation (MD) of fine struts. The results show that FA and RD are the dominant factors affecting MD within the investigated parameter range, whereas LP and SS exhibit comparatively weaker effects. Representative samples with different FA and RD were further characterized by SEM, XRD, and EBSD to examine the associated microstructural evolution. The observations indicate that changes in FA and RD are accompanied by variations in solidification morphology, defect distribution, crystallographic texture, and GND density. Higher FA is associated with lower MD and stronger texture alignment along the building direction, whereas larger RD tends to promote columnar growth and enhanced texture intensity. These results suggest that geometric parameters can serve as effective design variables for tailoring forming deviation and representative microstructural characteristics of fine struts in SLM-fabricated 316L lattice structures. Full article