Search Results (2,046)

A three-factor, four-level orthogonal design was employed to optimize the overall forming quality of powder bed fusion with a laser beam (PBF-LB)-fabricated TC4 alloy containing 0.3 wt.% YH₂. Sixteen process-parameter combinations were established, and two specimens were fabricated for each combination. Laser power, scanning speed, and hatch spacing were selected as the investigated variables. Relative density, surface roughness, and Vickers hardness were evaluated using the entropy weight method combined with the weighted-sum method. On this basis, the microstructure of the specimens produced under the optimal process parameters was systematically characterized. The results showed that the influence of the investigated factors on overall forming quality followed the order: hatch spacing > laser power > scanning speed. The optimal process parameters were a laser power of 200 W, a scanning speed of 1100 mm/s, and a hatch spacing of 0.10 mm, under which the specimens exhibited superior overall forming quality. The addition of 0.3 wt.% YH₂ did not significantly alter the dominant phase constitution of the alloy, but promoted α′ martensite refinement and weakened the texture through the in situ formation of Y₂O₃ nano-oxide particles. Full article

The dynamic behavior within the melt pool governs the final quality of components fabricated by laser powder bed fusion (LPBF). To address key technical challenges—rapid keyhole evolution, low absorption contrast from metal vapor, and difficulties in quantifying internal flow fields—this study introduces move contrast X-ray imaging (MCXI), a technique leveraging time-series frequency characteristics. Combined with a multi-scale Horn–Schunck global optical flow method, MCXI enables full-field quantitative extraction of the melt-pool velocity field. Experimental validation across feature points shows a relative deviation of less than 2% compared to independent manual feature-point tracking, confirming consistency with the best available experimental ground truth. Analysis reveals the keyhole tail evolution cycle comprises three distinct dynamic stages: expansion, stratification, and contraction, with its area increasing from 1329 μm² to 6508 μm² before stabilizing. For the first time, pore pinch-off events were quantitatively measured, revealing front and rear wall collision velocities of 7.98 m/s and 8.04 m/s, respectively, consistent with available high-fidelity simulations. Furthermore, analysis of the overall melt-pool momentum field demonstrates a near-equal distribution of positive and negative momentum, providing an internal self-consistency check confirming the absence of systematic directional bias in the extracted velocity field. This study enables quantitative analysis of LPBF melt-pool dynamics, providing a novel tool for process optimization and defect control. Full article

Binder jetting relies on the infiltration of binder droplets into a porous powder bed, where the spatial arrangement of droplets critically influences feature formation and structural integrity. In particular, the role of droplet spacing in regulating infiltration behavior remains insufficiently understood. In this study, droplet infiltration is investigated using a reconstructed three-dimensional powder bed combined with a Volume of Fluid (VOF) model. Both single- and dual-droplet configurations are examined to isolate the effect of droplet spacing on spreading, merging, and capillary-driven penetration. The results show that droplet spacing governs the redistribution of liquid flow between lateral spreading and vertical infiltration. Three distinct regimes are identified as spacing decreases: independent infiltration at large spacing, cooperative merging at intermediate spacing, and over-penetration at small spacing. These regimes reflect a transition from isolated droplet behavior to strongly coupled infiltration within the pore network. An optimal spacing of approximately 150 μm is found to balance spreading and penetration, enabling continuous deposition with controlled infiltration depth. Experimental measurements show good agreement with numerical predictions, with an average deviation of 8.66%. The present study clarifies the mechanism by which droplet spacing controls infiltration behavior and provides practical guidance for parameter selection in binder jetting processes. Full article

6063 aluminum alloy has broad application prospects in aerospace and microelectronic thermal management systems due to its good thermal conductivity and moderate strength. However, its extremely high hot cracking susceptibility during the laser powder bed fusion (LPBF) process limits the direct manufacturing of complex components. This study proposes a strategy combining material composition modification with advanced structural design. By introducing TiH₂ nanoparticles (1.0~4.5 wt.%) to modify the 6063 aluminum alloy powder, Diamond-type porous structures based on triply periodic minimal surfaces (TPMS) were successfully fabricated using LPBF technology. The results show that the introduction of TiH₂ significantly suppresses the solidification cracking of the aluminum alloy. The underlying mechanism is that the L1₂-structured Al₃Ti particles, generated by the in situ decomposition of TiH₂ in the melt pool, provide high-density heterogeneous nucleation sites. This leads to a drastic decrease in the average grain size from 30.46 μm to 0.75 μm (a reduction of 97.5%), achieving a remarkable columnar-to-equiaxed transition (CET). In terms of mechanical properties, the 3.0 wt.% TiH₂ addition group exhibits excellent plateau stress (28.5 MPa) and energy absorption capacity, which is mainly attributed to the synergistic effect of fine-grain strengthening and Orowan dispersion strengthening. Thermal tests reveal that the thermal conductivity of the 3.0 wt.% group reaches 123 W/(m·K) at 100 °C. The healing of cracks reconstructs the macroscopic heat conduction paths, resulting in a significant improvement in thermal conductivity compared with the unmodified group. This work provides a theoretical reference for the development of high-performance, crack-free, and multi-functional integrated aluminum alloy components via additive manufacturing. Full article

This paper investigates the powder spreading process in a Z-direction multi-material fabrication system utilizing a blade. Focusing on 316L stainless steel and CuCrZr, a discrete element model was developed to simulate powder spreading at the heterogeneous material interface. The effects of spreading speed and theoretical layer thickness on the resulting powder bed quality were systematically examined. The results reveal that during spreading over a heterogeneous bed, the underlying powder exhibits an unsteady “forward-surging and rearward-suppressing” motion pattern, with inter-particle force chains displaying significant spatiotemporal fluctuations. Increasing the spreading speed exacerbates the disturbance and removal of the underlying powder, leading to a reduction in the deposited mass of CuCrZr and a deterioration in its distribution uniformity. Conversely, increasing the layer thickness effectively mitigates the mechanical disturbance of the underlying powder by the blade, significantly enhancing both the deposited mass of CuCrZr and its distribution uniformity. Further investigation demonstrates that employing a higher spreading speed in combination with a larger layer thickness can achieve a favorable powder bed quality while maintaining high spreading efficiency, thereby enabling a synergistic optimization of productivity and bed quality. This work elucidates the mesoscopic dynamic mechanisms governing the powder spreading process at Z-direction heterogeneous interfaces and provides a theoretical foundation for process optimization in multi-material laser powder bed fusion. Full article

Developing specialized aluminum alloys for additive processes is a strategic approach to achieve both strength and mass reduction in high-performance products. The prospects of the new metallic powder composition of Al3Ca2La2Mn0.4Zr alloy for laser powder bed fusion (LPBF) have been studied. It has been found that the best printing mode, providing a more than 99.0% density of the specimens, includes substrate heating to 150 °C and printing with a 350 W laser power, a 1500 mm/s printing speed, a 0.08 mm hatch distance and a 0.03 mm layer thickness (energy density 97.2 J/mm²). The optimal printing mode provides for the following strength parameters: UTS 366 ± 5 MPa, yield strength 223 ± 8 MPa, and relative elongation 30 ± 3%. The alloy exhibits high thermal stability for the structure and its properties. Annealing temperatures below 300 °C have no critical effect on the alloy hardness: the hardness decreases by less than 10% of the initial 110 ± 3 HV. At 350 °C, the hardness decreases by 25.5% (82 ± 2 HV); 100 h exposure at 350 °C reduces the UTS to 265 ± 2 MPa and the yield strength to 178 ± 10 MPa, while maintaining the relative elongation of 29 ± 2%. Full article

This study aimed to develop and validate a physics-informed neural network (PINN) framework for data-efficient and physically consistent process optimization in the laser powder bed fusion (LPBF) of Inconel 718 (IN718) superalloy. Laser powder bed fusion (LPBF) is widely adopted for fabricating Inconel 718 (IN718) components in aerospace and energy applications; however, navigating its high-dimensional, nonlinear process parameter space remains a central challenge. High-fidelity finite element simulations are computationally prohibitive for extensive parameter sweeps, whereas purely data-driven machine learning (ML) models are limited by data scarcity and unphysical extrapolation behavior. This study presents a physics-informed neural network (PINN) framework that embeds the transient heat conduction equation and Goldak double-ellipsoidal heat source model directly into the neural network training loss, enforcing thermophysical consistency simultaneously with data fidelity. The model was trained on a curated, multi-source dataset of LPBF IN718 parameter combinations drawn from peer-reviewed experimental studies and validated finite element simulation outputs, spanning the laser power (70–400 W), scan speed (200–2000 mm/s), hatch spacing (50–140 µm), and layer thickness (20–50 µm). The PINN predicted the melt pool width, depth, peak temperature, and relative density with mean absolute percentage errors (MAPE) of 3.8%, 4.7%, 3.1%, and 1.9%, respectively, outperforming a baseline artificial neural network (ANN) with an identical architecture. The framework correctly identified the optimal volumetric energy density (VED) window of 55–105 J/mm³, yielding relative densities ≥99.5%, consistent with the published experimental thresholds for IN718. A data efficiency analysis demonstrated that the PINN with 25% training data achieves a performance equivalent to that of the fully trained ANN with 100% data, confirming an approximately four-fold data efficiency improvement attributable to physics-informed regularization, consistent with theoretical predictions. Sensitivity analysis via automatic differentiation confirmed that laser power and scan speed were the dominant parameters (~85% combined variance), which is in agreement with previous studies. This study provides a computationally efficient, interpretable, and physically consistent ML pathway for the accelerated process qualification of IN718 components for aerospace and energy applications. Full article

This review comprehensively examines the incorporation of nanoparticles (NPs) into biopolymers for 3D printing in biomedical applications, integrating material design, processing strategies, and translational considerations within a unified framework. Different types of NPs are analyzed regarding their effects on mechanical reinforcement, rheological modulation, and structural organization of biopolymeric matrices. The discussion covers principal additive manufacturing technologies, including extrusion-based systems such as fused deposition modeling (FDM) and direct ink writing (DIW), vat photopolymerization, powder-bed fusion (SLS), and emerging in situ nanoparticle formation approaches, emphasizing how nanoparticle loading and surface functionalization govern yield stress, shear-thinning behavior, viscoelastic recovery, and dimensional fidelity while mitigating agglomeration and optimizing interfacial interactions. Comparative evaluation of compressive modulus, strength, toughness, crystallinity, and porosity establishes structure–property–processing relationships directly linked to printability and functional performance. Biomedical applications are addressed in tissue engineering, biosensing, controlled and targeted drug delivery, and bioimaging, highlighting the balance between bioactivity and manufacturability. Finally, critical challenges—including compatibility, reproducibility, biological safety, long-term stability, regulatory adaptation, and environmental impact—are discussed, alongside future perspectives focused on green nanomaterials, AI-driven predictive formulation design, and digital twins for real-time monitoring and quality control in nano-enabled additive manufacturing. Full article

Additive manufacturing (AM) using powder bed fusion (PBF) has been the predominant printing method used over the last decade. The capability of this approach to produce complex parts with high precision has attracted the attention of major industries as a potential tool for replacing traditional manufacturing technologies. 15-5 PH stainless steel is one of the alloys being studied as a candidate for PBF processes. Its superior strength and corrosion resistance have made it a highly attractive option in numerous industries, including the automotive, nuclear, and petrochemical industries. To enhance the properties of 15-5 PH stainless-steel AM parts following printing, one can use a thermal treatment such as age hardening. However, very little research exists regarding the functional properties of AM parts made from this alloy after heat treatment. This study aims to evaluate the effect of H1150M age hardening heat treatment following printing on the properties of 15-5 PH steel, particularly regarding its mechanical properties and environmental behavior. The microstructure was studied using both optical and electron microscopy, along with X-ray diffraction (XRD) analysis. The mechanical properties were examined by tensile testing and fracture toughness assessment. Corrosion behavior was analyzed in terms of potentiodynamic polarization and using impedance spectroscopy. The results obtained have shown that over-aging caused by H1150M heat treatment has a detrimental effect on the mechanical and environmental behavior of the tested alloy. This was primarily attributed to the formation of an austenitic phase within the inherent martensitic matrix, the generation of brittle phases (mainly carbonitrides of Cr and Nb) and a reduction in grain size. Full article

Cracking represents a critical issue in γ’-strengthened Ni-based superalloys processed via laser powder bed fusion. This study systematically investigated the influence of scan speed (800–1200 mm/s) on the crack elimination mechanism, microstructural evolution, and mechanical properties of LPBF-processed IN738LC alloy. Near-defect-free IN738LC parts were successfully produced with a relative density of 99.6% and a crack density of only 0.025%. The results indicate that as the scan speed increased from 800 mm/s to 1100 mm/s, a flatter melt pool (S4) was obtained, which reduced the proportion of high-angle grain boundaries. The cooling rate also increased from 13.68 K/μs to 15.96 K/μs, promoting grain refinement and the dispersion precipitation of MC carbides. The refined grains effectively suppressed stress concentration and inhibited crack propagation along grain boundaries. The optimized process (1100 mm/s) achieved optimal comprehensive mechanical properties. Compared to a scan speed of 800 mm/s, the ultimate tensile strength, yield strength, and elongation at room-temperature increased from 1075 MPa, 820 MPa, and 13.2% to 1179 MPa, 871 MPa, and 21.1%, respectively, while hardness increased from 365 HV_1.0 to 387 HV_1.0. This study demonstrated that the microstructure and mechanical properties of LPBF-processed IN738LC alloy can be tailored via controlling the thermal history of the melt pool, providing a foundation for processing high-crack-sensitivity alloys utilizing laser powder bed fusion. Full article

Heat treatment is essential for In625 fabricated by laser powder bed fusion (L-PBF), as it significantly influences microstructural evolution, defect behavior, and mechanical performance. In this study, the effects of different solution heat treatments on L-PBF-fabricated In625 were systematically investigated. Industrial computed tomography was employed to characterize internal defects before and after heat treatment, while optical microscopy, EBSD, TEM, and EDS were used to analyze microstructural evolution. Room-temperature tensile tests evaluated mechanical properties. The results show that heat treatment at 1090 °C reduces porosity from 0.33% to 0.25%, whereas increasing the temperature to 1150 °C results in a further increase in porosity to 0.45%. This non-monotonic behavior is interpreted as the result of competing mechanisms, including partial closure of small pores at 1090 °C and pore coarsening/enlargement at higher temperatures, with the latter possibly involving the growth of sub-resolution pores into the CT-detectable range. Complete grain equiaxiality occurs after heat treatment at 1090 °C or higher, with average grain sizes below 100 μm, although grain coarsening becomes pronounced at higher temperatures. Samples heat-treated at 1150 °C exhibit reduced mechanical anisotropy, achieving tensile strength above 919 MPa and elongation up to 60%. These results clarify the mechanisms by which heat treatment governs microstructure–defect–property relationships in L-PBF In625, guiding its engineering application. Full article

We report on tool wear and surface roughness for hybrid additive manufacturing of Inconel 718 components. The hybrid additive manufacturing comprises laser powder bed fusion (PBF-LB/M) and an in situ high-speed milling process, i.e., milling is performed within the powderbed, which deteriorates the surface quality by additionally occurring wear mechanisms. Therefore, in this comparative study milling path suction is used to improve tool wear characteristics and thus enhance surface quality. As a result, we quantify the improvement of the maximum tool life according to the flank wear, which is granted by the milling path suction. Additionally, the dominant wear mechanisms are investigated, revealing adherence and abrasion as the main contributing factors to wear. Furthermore, surface analysis shows an improvement of surface quality by the use of the milling path suction. Specifically, a reduction in surface roughness of hybrid manufactured Inconel 718 components down to a minimum of $Ra$ = 0.55 μm is highlighted. Full article

In the 21st century, the desire for improved fuel efficiency of engines, lower fuel prices, and the need to reduce greenhouse gas emissions such as ${\mathrm{C}\mathrm{O}}_2$ and ${\mathrm{N}\mathrm{O}}_{\mathrm{x}}$ are leading the aviation industry to seek hybrid-electric jet engines for commercial aircraft. These aircraft will have greater maintenance challenges due to additional components requiring more reliable materials for the engine’s parts, such as turbine blades. Turbine blades must be composed of materials that have enhanced fatigue performance. Resistance to dynamic loads and high strength will be needed to ensure modern gas turbine blades are as reliable as possible. This review paper examines hybrid-electric engine turbine blades and subsequently introduces additive manufacturing (AM) and multi-principal element alloys (MPEAs) with a focus on laser powder bed fusion (LPBF), high-entropy alloys (HEAs), and medium-entropy alloys (MEAs). The tensile properties of LPBF HEAs range from 5 to 47% elongation and a UTS of 572–1640 MPa, while LPBF MEAs range from 8 to 73.9% and a UTS of 573–1382 MPa. This study focused on dynamic and fatigue properties while acknowledging gaps in high-temperature testing. The combination of mechanical properties with the ability to control internal geometry makes these AM alloys an attractive option for the next generation of gas turbine blades. Full article

Ceramics are widely evaluated for their extreme hardness, high-temperature stability, and corrosion resistance, which enable applications in harsh service environments. However, these same properties, high melting points, brittleness, and low thermal shock resistance, make conventional manufacturing of complex ceramic components difficult and expensive. Traditional processes often require costly diamond tooling or energy-intensive sintering and tend to produce only simple geometries, with significant waste material and risk of defects. Additive manufacturing (AM) has recently emerged as a promising route to fabricate intricate, near-net-shape ceramic parts without these drawbacks. By building components layer by layer, AM reduces the need for extensive machining and enables the fabrication of geometrically complex, near-net-shape ceramic structures with reduced material waste, although challenges such as porosity, interlayer defects, and cracking during post-processing remain. Nonetheless, ceramic AM technologies lag behind their metal and polymer counterparts, and significant challenges remain in achieving fully dense parts with reliable mechanical properties. This review provides an in-depth overview of the state of the art in ceramics and ceramic composite additive manufacturing. We detail the most widely used AM processes (stereolithography, binder jetting, material extrusion, powder bed fusion, inkjet printing, and direct energy deposition) and typical feedstock formulations for each technique. We examine the resulting mechanical properties (strength, toughness, hardness, wear resistance) and functional properties (thermal stability, dielectric behavior, biocompatibility) of additively manufactured ceramics, and discuss their current and potential engineering applications in the aerospace, defense, automotive, biomedical, and energy sectors. Persistent challenges, including porosity, shrinkage and cracking during sintering, achieving uniform microstructures, high process costs, and scalability issues, are analyzed, and we highlight promising future directions such as multi-material grading, integration of machine learning for process optimization, and sustainable manufacturing approaches. Despite significant progress, challenges remain in achieving fully dense structures, improving process reliability, and scaling ceramic AM for industrial applications, highlighting the need for further research in process optimization, material design, and multi-material integration. Full article

Laser-based Powder Bed Fusion (LPBF) enables the fabrication of complex metal components but often results in high porosity and microdefect densities, compromising fatigue performance despite acceptable static properties. Standard fatigue characterisation methods are time-consuming and costly and yield scattered results due to defect-induced brittleness and residual stresses. This study investigates the application of thermographic techniques as a rapid alternative for evaluating the intrinsic fatigue behaviour of tensile coupons fabricated by LPBF employing AISI 316L steel. By monitoring surface temperature during stepwise static monotone and fatigue loading, thermographic methods aim to detect early hints of heat dissipation associated with microdamage initiation. Approaches based on temperature harmonic analysis have been implemented, allowing near-real-time and full-field mapping of stress distribution and damage development. Results show that harmonic metrics correlate with the material state and effectively track the thermoelastic effect-induced temperature changes. Some evidence is found regarding the onset of intrinsic heat dissipation, which needs to be confirmed by more focused and extensive experimental tests. Full article