Interactions in Titanium Matrix Composites Reinforced by Titanium Compounds by Conventional PM Route

Romero,F.,Amigo,V.,Salvador,M.D.,Vicente,A. 한국분말재료학회(구 한국분말야금학회) 2006 한국분말야금학회 학술대회논문집 Vol.2006 No.1

텅스텐의 제련과 리사이클링 현황

손호상,Sohn, Ho-Sang 한국분말재료학회 (*구 분말야금학회) 2021 한국분말재료학회지 (KPMI) Vol.28 No.4

Because of its unique properties, tungsten is a strategic and rare metal used in various industrial applications. However, the world's annual production of tungsten is only 84000 t. Ammonium paratungstate (APT), which is used as the main intermediate in industrial tungsten production, is usually obtained from tungsten concentrates of wolframite and scheelite by hydrometallurgical treatment. Intermediates such as tungsten trioxide, tungsten blue oxide, tungstic acid, and ammonium metatungstate can be derived from APT by thermal decomposition or chemical attack. Tungsten metal powder is produced through the hydrogen reduction of high-purity tungsten oxides, and tungsten carbide powder is produced by the reaction of tungsten powder and carbon black powder at 1300-1700℃ in a hydrogen atmosphere. Tungsten scrap can be divided into hard and soft scrap based on shape (bulk or powder). It can also be divided into new scrap generated during the production of tungsten-bearing goods and old scrap collected at the end of life. Recycling technologies for tungsten can be divided into four main groups: direct, chemical, and semi-direct recycling, and melting metallurgy. In this review, the current status of tungsten smelting and recycling technologies is discussed.

원자층 증착법을 이용한 열전 소재 연구 동향

이승혁,박태주,김성근 한국분말재료학회 2022 한국분말재료학회지 (KPMI) Vol.29 No.1

Atomic layer deposition (ALD) is a promising technology for the uniform deposition of thin films. ALD is based on a self-limiting mechanism, which can effectively deposit thin films on the surfaces of powders of various sizes. Numerous studies are underway to improve the performance of thermoelectric materials by forming core-shell structures in which various materials are deposited on the powder surface using ALD. Thermoelectric materials are especially relevant as clean energy storage materials due to their ability to interconvert between thermal and electrical energy by the Seebeck and Peltier effects. Herein, we introduce a surface and interface modification strategy based on ALD to control the performance of thermoelectric materials. We also discuss the properties of the interface between various deposition materials and thermoelectric materials.

Ag/WC 소결 전기 접점 소재의 미세조직, 기계적 및 전기적 특성에 미치는 WC 입자 크기의 영향

김수빈,박소연,임종빈,권순호,이기안 한국분말재료학회 2023 한국분말재료학회지 (KPMI) Vol.30 No.3

The Ag/WC electrical contacts were prepared via powder metallurgy using 60 wt% Ag, 40 wt% WC, and small amounts of Co3O4 with varying WC particle sizes. After the fabrication of the contact materials, microstructure observations confirmed that WC-1 had an average grain size (AGS) of 0.27 μm, and WC-2 had an AGS of 0.35 μm. The Ag matrix in WC-1 formed fine grains, whereas a significantly larger and continuous growth of the Ag matrix was observed in WC-2. This indicates the different flow behaviors of liquid Ag during the sintering process owing to the different WC sizes. The electrical conductivities of WC-1 and WC-2 were 47.8% and 60.4%, respectively, and had a significant influence on the Ag matrix. In particular, WC-2 exhibited extremely high electrical conductivity owing to its large and continuous Ag-grain matrix. The yield strengths of WC-1 and WC-2 after compression tests were 349.9 MPa and 280.7 MPa, respectively. The high yield strength of WC-1 can be attributed to the Hall–Petch effect, whereas the low yield strength of WC-2 can be explained by the high fraction of high-angle boundaries (HAB) between the WC grains. Furthermore, the relationships between the microstructure, electrical/mechanical properties, and deformation mechanisms were evaluated.

인슐레이터용 알루미나의 치밀화에 미치는 MgO의 함량과 소결 온도의 영향

김리주,정한결,손예지,고상기,홍현선 한국분말재료학회 2023 한국분말재료학회지 (KPMI) Vol.30 No.3

The influence of MgO addition on the densification and microstructure of alumina (Al2O3) was studied. Compacted alumina specimens were manufactured using ball-milling and one-directional pressing followed by sintering at temperatures below 1700oC. Relative density, shrinkage, hardness, and microstructure were investigated using analytical tools such as FE-SEM, EDS, and XRD. When the MgO was added up to 5.0 wt% and sintered at 1500oC and 1600oC, the relative density exhibited an average value of 97% or more at both temperatures. The maximum density of 99.2% was with the addition of 0.5 wt% MgO at 1500oC. Meanwhile, the specimens showed significantly lower density values when sintered at 1400oC than at 1500oC and 1600oC owing to the relatively low sintering temperature. The hardness and shrinkage data also showed a similar trend in the change in density, implying that the addition of approximately 0.5 wt% MgO can promote the densification of Al2O3. Studying the microstructure confirmed the uniformity of the sintered alumina. These results can be used as basic compositional data for the development of MgOcontaining alumina as high-dielectric insulators.

반응표면모델을 통한 적층제조된 ZrH2 접종제 첨가AA7075 합금의 균열 밀도 예측

이정아,최중호,김형섭 한국분말재료학회 2023 한국분말재료학회지 (KPMI) Vol.30 No.3

Aluminum alloy-based additive manufacturing (AM) has emerged as a popular manufacturing process for the fabrication of complex parts in the automotive and aerospace industries. The addition of an inoculant to aluminum alloy powder has been demonstrated to effectively reduce cracking by promoting the formation of equiaxed grains. However, the optimization of the AM process parameters remains challenging owing to their variability. In this study, the response surface methodology (RSM) was used to predict the crack density of AM-processed Al alloy samples. RSM was performed by setting the process parameters and equiaxed grain ratio, which influence crack propagation, as independent variables and designating crack density as a response variable. The RSM-based quadratic polynomial models for crack-density prediction were found to be highly accurate. The relationship among the process parameters, crack density, and equiaxed grain fraction was also investigated using RSM. The findings of this study highlight the efficacy of RSM as a reliable approach for optimizing the properties of AM-processed parts with limited experimental data. These results can contribute to the development of robust AM processing strategies for the fabrication of highquality Al alloy components for various applications.

생체모방 모세관 현상을 이용한 PDMS 구조체 기반 증산발전기 제조기술 연구

이승환,윤정재,백소현,권용범,송요셉,김범성,좌용호,정다운 한국분말재료학회 2023 한국분말재료학회지 (KPMI) Vol.30 No.3

The demand for energy is steadily rising because of rapid population growth and improvements in living standards. Consequently, extensive research is being conducted worldwide to enhance the energy supply. Transpiration power generation technology utilizes the vast availability of water, which encompasses more than 70% of the Earth's surface, offering the unique advantage of minimal temporal and spatial constraints over other forms of power generation. Various principles are involved in water-based energy harvesting. In this study, we focused on explaining the generation of energy through the streaming potential within the generator component. The generator was fabricated using sugar cubes, PDMS, carbon black, CTAB, and DI water. In addition, a straightforward and rapid manufacturing method for the generator was proposed. The PDMS generator developed in this study exhibits high performance with a voltage of 29.6 mV and a current of 8.29 μA and can generate power for over 40h. This study contributes to the future development of generators that can achieve high performance and long-term power generation.

Multi-feeder 3차원 적층제조 기반 조합실험을 활용한 알루미늄 합금탐색

박수원,송용욱,여지윤,한송윤,최현주 한국분말재료학회 2023 한국분말재료학회지 (KPMI) Vol.30 No.3

Aluminum alloys are widely utilized in diverse industries, such as automobiles, aerospace, and architecture, owing to their high specific strength and resistance to oxidation. However, to meet the increasing demands of the industry, it is necessary to design new aluminum alloys with excellent properties. Thus, a new method is required to efficiently test additively manufactured aluminum alloys with various compositions within a short period during the alloy design process. In this study, a combinatory approach using a direct energy deposition system for metal 3D printing process with a dual feeder was employed. Two types of aluminum alloy powders, namely Al6061 and Al-12Cu, were utilized for the combinatory test conducted through 3D printing. Twelve types of Al-Si-Cu-Mg alloys were manufactured during this combinatory test, and the relationship between their microstructures and properties was investigated.

레이저 분말 베드 용융법으로 제조된 AlSi10Mg 합금의 경도 예측을 위한 설명 가능한 인공지능 활용

전준협,서남혁,김민수,손승배,정재길,이석재 한국분말재료학회 2023 한국분말재료학회지 (KPMI) Vol.30 No.3

In this study, machine learning models are proposed to predict the Vickers hardness of AlSi10Mg alloys fabricated by laser powder bed fusion (LPBF). A total of 113 utilizable datasets were collected from the literature. The hyperparameters of the machine-learning models were adjusted to select an accurate predictive model. The random forest regression (RFR) model showed the best performance compared to support vector regression, artificial neural networks, and k-nearest neighbors. The variable importance and prediction mechanisms of the RFR were discussed by Shapley additive explanation (SHAP). Aging time had the greatest influence on the Vickers hardness, followed by solution time, solution temperature, layer thickness, scan speed, power, aging temperature, average particle size, and hatching distance. Detailed prediction mechanisms for RFR are analyzed using SHAP dependence plots.

고강도 Nb기 초내열 합금 설계를 위한 기계학습 기반 데이터 분석

마은호,박수원,최현주,황병철,변종민 한국분말재료학회 2023 한국분말재료학회지 (KPMI) Vol.30 No.3

Machine learning-based data analysis approaches have been employed to overcome the limitations in accurately analyzing data and to predict the results of the design of Nb-based superalloys. In this study, a database containing the composition of the alloying elements and their room-temperature tensile strengths was prepared based on a previous study. After computing the correlation between the tensile strength at room temperature and the composition, a material science analysis was conducted on the elements with high correlation coefficients. These alloying elements were found to have a significant effect on the variation in the tensile strength of Nb-based alloys at room temperature. Through this process, a model was derived to predict the properties using four machine learning algorithms. The Bayesian ridge regression algorithm proved to be the optimal model when Y, Sc, W, Cr, Mo, Sn, and Ti were used as input features. This study demonstrates the successful application of machine learning techniques to effectively analyze data and predict outcomes, thereby providing valuable insights into the design of Nb-based superalloys.