The development of high-performance metal filters is essential for maintaining ultra-clean environments in semiconductor manufacturing. In this study, cross-sealed honeycomb filters were fabricated using STS316L powder via material extrusion additive manufacturing (MEAM) for semiconductor gas filtration. The effects of filter geometry (4 or 9 channels) and sintering temperature (850°C, 950°C, or 1,050°C) on performance were examined. First, 4-channel and 9-channel filters sintered at the same temperature (950°C) exhibited similar porosities of 50.08% and 50.57%, but the 9-channel filter showed a higher pressure-drop (0.26 bar) and better filtration-efficiency (3.55 LRV) than the 4-channel filter (0.19 bar and 3.25 LRV, respectively). Second, for filters with the same geometry (4-channel) increasing the sintering temperature reduced porosity from 64.52% to 40.33%, while the pressure-drop increased from 0.13 bar to 0.22 bar and filtration-efficiency improved from 2.53 LRV to 3.51 LRV. These findings demonstrate that filter geometry and sintering temperature are key factors governing the trade-off between air permeability, pressure-drop, and filtration efficiency. This work provides insights and data for optimizing MEAM-based high-performance metal powder filter design.
This study investigated the effects of Fe and Cr contents on ω phase formation and transformation during solution treatment and the subsequent aging process, for which four model alloys with varying Fe and Cr contents but keeping Mo equivalent of ~ 12.6 were prepared by plasma arc melting and fabricated into plates by hot forging followed by hot-rolling. The atherrmal ω phase was observed in all Ti alloys after solution treatment followed by water quenching through XRD and TEM analysis. The largest volume fraction of athermal ω phase is formed in Ti alloy with only Fe 4 wt.% among all Ti alloys, leading to the highest Vickers value due to hardening effect ω phase. It was found that not only Mo equivalent but also each characteristic of β stabilizing elements should be considered to understand a microstructure evolution and mechanical properties.
This study presents a cost-effective approach to fabricating near β-Ti alloys via in-situ alloying during laser powder bed fusion (L-PBF). A blend of non-spherical pure Ti, 3 wt.% Fe, and 0.1 wt.% SiO2 nanoparticles was used to induce β-phase stabilization and improve flowability. Twenty-five process conditions were evaluated across a volumetric energy density range of 31.75-214.30 J/mm3, achieving a maximum relative density of 99.21% at 89.29 J/mm3. X-ray diffraction analysis revealed that the β-Ti phase was partially retained at room temperature, accompanied by lattice contraction in the α’-Ti structure, indicating successful Fe incorporation. Elemental mapping confirmed that the Fe distribution was homogeneous, without significant segregation. Compared to pure Ti, the Ti-3Fe sample exhibited a 49.2% increase in Vickers hardness and notable improvements in yield and ultimate tensile strengths. These results demonstrate the feasibility of in-situ alloying with low-cost elemental powders to produce high-performance near β-Ti alloys using L-PBF.
This study compares pure Ni coatings deposited on type 316H stainless steel using high-velocity oxy-fuel (HVOF) and directed energy deposition (DED) processes. Microstructural analysis showed that DED produced more uniform claddings with fewer pores, while HVOF resulted in incomplete melting and cracks. Elemental diffusion of Cr and Fe from the substrate into the cladding was evident in DED samples, especially at higher laser power, but minimal in HVOF due to low heat input. Vickers hardness testing revealed that DED claddings had higher hardness near the interface, which was attributed to solid solution strengthening and reduced porosity. Although HVOF better suppressed diffusion, it exhibited inferior mechanical properties due to internal defects. Overall, the DED process demonstrated superior coating quality and mechanical performance, suggesting its suitability for corrosion-resistant applications requiring both structural integrity and thermal stability, such as molten salt reactors.
The recent development of small modular reactors (SMRs) and the adoption of higher-enrichment fuels have intensified the need for advanced burnable absorbers to ensure effective reactivity control and extended fuel cycles. Among various designs, UO2 fuels with high Gd2O3 (gadolinium oxide) content provide notable benefits; in particular, they are compatible with established fabrication methods for burnable absorber fuels. However, achieving a homogeneous dispersion of Gd2O3 at high loading levels remains challenging, and the frequent occurrence of phase segregation and non-uniform microstructures can limit fuel reliability and performance. Overcoming these limitations requires an understanding of the powder characteristics and mixing behaviors during fabrication. In this study, we investigate the effects of the initial particle size and mixing method of UO2 and Gd2O3 powders on the microstructure and mixing homogeneity of high-Gd2O3-content fuels. The findings indicate that both the mixing method and the preparation state of the starting powders significantly affect the resulting microstructure and mixing uniformity.
Co-Cr alloys are widely used in cutting tools and turbine components due to their high strength and resistance against wear and corrosion. However, scrap generated during hardfacing is often discarded due to impurities and oxidation, and research on its recycling remains limited. This study aimed to optimize the recycling process of Stellite 6 scrap to reduce waste and minimize costs while maintaining material quality. Melting, casting, and powdering processes were designed using HSC Chemistry, FactSage, and COMSOL Multiphysics, with optimization of key parameters such as the crucible material and temperature control. The recycled alloy and powder were analyzed using X-ray fluorescence analysis, inductively coupled plasma optical emission spectroscopy, and X-ray diffractometry, showing mechanical and chemical properties comparable to commercial Stellite 6. The Co and Cr contents were maintained, with a slight increase in Fe. These findings demonstrate the potential for producing high-quality recycled Stellite 6 materials, contributing to the sustainable utilization of metal resources in high-performance applications.
This study investigated the effects of oxidative firing parameters and raw material characteristics on the pelletization of Australian and Minh Son (Vietnam) iron ore concentrates. The influence of firing temperature (1050°C–1150°C) and holding time (15–120 min) on pellet compressive strength was examined, focusing on microstructural changes during consolidation. Green pellets were prepared using controlled particle size distributions and bentonite as a binder. Scanning electron microscopy and energy-dispersive X-ray spectroscopy analyses revealed that grain boundary diffusion, liquid phase formation, and densification significantly improved mechanical strength. X-ray diffraction confirmed the complete oxidation of magnetite to hematite at elevated temperatures, a critical transformation for metallurgical performance. Optimal firing conditions for both single and blended ore compositions yielded compressive strengths above 250 kgf/pellet, satisfying the requirements for blast furnace applications. These results provide valuable guidance for improving pellet production, promoting the efficient utilization of diverse ore types, and enhancing the overall performance of ironmaking operations.
This study examined process–structure relationships in laser powder bed fusion of Al₀.₁CoCrFeNi + Cu composites, focusing on densification, elemental distribution, and solidification cracking. Mechanically mixed Al₀.₁CoCrFeNi and Cu powders were processed across a range of laser powers (100–250 W) and scan speeds (200–800 mm/s). Increased volumetric energy density (VED) improved densification, with a plateau near 200 J/mm³ yielding ~96% relative density; however, this value was still below application-grade thresholds. At low VED, insufficient thermal input and short melt pool residence times promoted Cu segregation, while higher VED facilitated improved elemental mixing. Elemental mapping showed partial co-segregation of Ni with Cu at low energies. Solidification cracks were observed across all processing conditions. In high VED regimes, cracking exhibited a minimal correlation with segregation behavior and was primarily attributed to steep thermal gradients, solidification shrinkage, and residual stress accumulation. In contrast, at low VED, pronounced Cu segregation appeared to exacerbate cracking through localized thermal and mechanical mismatch.
Ni-based superalloys are widely used for critical components in aerospace, defense, industrial power generation systems, and other applications. Clean superalloy powders and manufacturing processes, such as compaction and hot isostatic pressing, are essential for producing superalloy discs used in turbine engines, which operate under cyclic rotating loads and high-temperature conditions. In this study, the plasma rotating electrode process (PREP), one of the most promising methods for producing clean metallic powders, is employed to fabricate Ni-based superalloy powders. PREP leads to a larger powder size and narrower distribution compared to powders produced by vacuum induction melt gas atomization. An important finding is that highly spheroidized powders almost free of satellites, fractured, and deformed particles can be obtained by PREP, with significantly low oxygen content (approximately 50 ppm). Additionally, large grain size and surface inclusions should be further controlled during the PREP process to produce high-quality powder metallurgy parts.
Lithium (Li) metal is a promising anode for next-generation batteries due to its high capacity, low redox potential, and low density. However, dendrite growth and interfacial instability limit its use. In this study, an artificial solid electrolyte interphase layer of LiF and Li-Sn (LiF@Li-Sn) was fabricated by spray-coating SnF2 onto Li. The LiF@Li-Sn anode exhibited improved air stability and electrochemical performance. Electrochemical impedance spectroscopy indicated a charge transfer resistance of 25.2 Ω after the first cycle. In symmetric cells, it maintained a low overpotential of 27 mV after 250 cycles at 2 mA/cm2, outperforming bare Li. In situ microscopy confirmed dendrite suppression during plating. Full cells with NMC622 cathodes and LiF@Li-Sn anodes delivered 130.8 mAh/g with 79.4% retention after 300 cycles at 1 C and 98.8% coulombic efficiency. This coating effectively stabilized the interface and suppressed dendrites, with promising implications for practical lithium metal batteries.
In this study, we analyzed the structural and mechanical properties of aluminum foams fabricated using aluminum powders of varying sizes and mixtures. The effects of sintering and pore structure at each size on the integrity and mechanical properties of the foams were investigated. Structural characteristics were examined using scanning electron microscopy and micro–computed tomography, while mechanical properties were evaluated through compression testing. The experimental results demonstrated that smaller powder sizes improved foam integrity, reduced porosity and pore size, and resulted in thinner cell walls. In combination, these effects increased compressive strength as the powder size decreased. The findings of this study contribute to the understanding and improvement of the mechanical properties of aluminum foams and highlight their potential for use in a wide range of applications.
The present study introduces a machine learning approach for designing new aluminum alloys tailored for directed energy deposition additive manufacturing, achieving an optimal balance between hardness and conductivity. Utilizing a comprehensive database of powder compositions, process parameters, and material properties, predictive models—including an artificial neural network and a gradient boosting regression model, were developed. Additionally, a variational autoencoder was employed to model input data distributions and generate novel process data for aluminum-based powders. The similarity between the generated data and the experimental data was evaluated using K-nearest neighbor classification and t-distributed stochastic neighbor embedding, with accuracy and the F1-score as metrics. The results demonstrated a close alignment, with nearly 90% accuracy, in numerical metrics and data distribution patterns. This work highlights the potential of machine learning to extend beyond multi-property prediction, enabling the generation of innovative process data for material design.
High-entropy alloys (HEAs) exhibit complex phase formation behavior, challenging conventional predictive methods. This study presents a machine learning (ML) framework for phase prediction in HEAs, using a curated dataset of 648 experimentally characterized compositions and features derived from thermodynamic and electronic descriptors. Three classifiers—random forest, gradient boosting, and CatBoost—were trained and validated through cross-validation and testing. Gradient boosting achieved the highest accuracy, and valence electron concentration (VEC), atomic size mismatch (δ), and enthalpy of mixing (ΔHmix) were identified as the most influential features. The model predictions were experimentally verified using a non-equiatomic Al₃₀Cu₁₇.₅Fe₁₇.₅Cr₁₇.₅Mn₁₇.₅ alloy and the equiatomic Cantor alloy (CoCrFeMnNi), both of which showed strong agreement with predicted phase structures. The results demonstrate that combining physically informed feature engineering with ML enables accurate and generalizable phase prediction, supporting accelerated HEA design.
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Preparation and Arc Erosion Behavior of Cu-Based Contact Materials Reinforced with High Entropy Particles CuCrNiCoFe Jiacheng Tong, Jun Wang, Huimin Zhang, Haoran Liu, Youchang Sun, Zhiguo Li, Wenyi Zhang, Zhe Wang, Yanli Chang, Zhao Yuan, Henry Hu Metallurgical and Materials Transactions B.2025;[Epub] CrossRef
Recent progresses on high entropy alloy development using machine learning: A review Abhishek Kumar, Nilay Krishna Mukhopadhyay, Thakur Prasad Yadav Computational Materials Today.2025; : 100038. CrossRef
Area-selective atomic layer deposition (AS-ALD) is a bottom-up process that selectively deposits thin films onto specific areas of a wafer surface. The surface reactions of AS-ALD are controlled by blocking the adsorption of precursors using inhibitors such as self-assembled monolayers (SAMs) or small molecule inhibitors. To increase selectivity during the AS-ALD process, the design of both the inhibitor and the precursor is crucial. Both inhibitors and precursors vary in reactivity and size, and surface reactions are blocked through interactions between precursor molecules and surface functional groups. However, challenges in the conventional SAM-based AS-ALD method include thermal instability and potential damage to substrates during the removal of residual SAMs after the process. To address these issues, recent studies have proposed alternative inhibitors and process design strategies.
Ti-6Al-4V alloy is widely utilized in aerospace and medical sectors due to its high specific strength, corrosion resistance, and biocompatibility. However, its low machinability makes it difficult to manufacture complex-shaped products. Advancements in additive manufacturing have focused on producing high-performance, complex components using the laser powder bed fusion (LPBF) process, which is a specialized technique for customized geometries. The LPBF process exposes materials to extreme thermal conditions and rapid cooling rates, leading to residual stresses within the parts. These stresses are intensified by variations in the thermal history across regions of the component. These variations result in differences in microstructure and mechanical properties, causing distortion. Although support structure design has been researched to minimize residual stress, few studies have conducted quantitative analyses of stress variations due to different support designs. This study investigated changes in the residual stress and mechanical properties of Ti-6Al-4V alloy fabricated using LPBF, focusing on support structure design.