간행물

한국분말재료학회지(구 한국분말야금학회지) KCI 등재 Journal of Powder Materials

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Vol.32 No.3 (2025년 6월) 8

1.
2025.06 구독 인증기관 무료, 개인회원 유료
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.
4,300원
2.
2025.06 구독 인증기관 무료, 개인회원 유료
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.
4,200원
3.
2025.06 구독 인증기관 무료, 개인회원 유료
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.
4,000원
4.
2025.06 구독 인증기관 무료, 개인회원 유료
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.
4,000원
5.
2025.06 구독 인증기관 무료, 개인회원 유료
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.
4,000원
6.
2025.06 구독 인증기관 무료, 개인회원 유료
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.
4,300원
7.
2025.06 구독 인증기관 무료, 개인회원 유료
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.
4,000원
8.
2025.06 구독 인증기관 무료, 개인회원 유료
High-entropy alloys (HEAs) incorporating low-melting-point elements (Mg and Al) and high-melting-point elements (Ti, Cr, and V) were fabricated via mechanical alloying and spark plasma sintering. Sintering temperatures were varied to investigate phase behavior and microstructural evolution. X-ray diffraction was used to identify phase structures, scanning electron microscopy to analyze microstructures, X-ray fluorescence to determine elemental composition, and a gas pycnometer to measure density. Micro-Vickers hardness testing was conducted to evaluate mechanical properties. Mechanical-alloyed HEAs exhibited a body-centered cubic (BCC) phase and lamellar structures with element-enriched regions. Sintering introduced additional BCC and Laves phases, while higher temperatures promoted Mg liquid-phase sintering, increasing density and hardness. This study highlights the effects of sintering on HEAs containing elements with differing melting points to optimize their properties.
4,000원