• Journal of Powder Materials
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• v.30 no.3
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• pp.210-216
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• 2023

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.

• Progress in Superconductivity and Cryogenics
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• v.26 no.2
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• pp.24-30
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• 2024

Metal 3D printing is utilized in various industrial fields due to its advantages, such as fewer restrictions on production shape and reduced production time and cost. Existing research on 3D printing metal materials focused on changes in material properties depending on manufacturing conditions and was mainly conducted in a room temperature environment. In order to apply metal 3D printing products to cryogenic applications, research on the properties of materials in cryogenic environments is necessary but still insufficient. In this study, we evaluate the properties of stainless steel (STS) 316L and CuCr1Zr manufactured by Laser Powder Bed Fusion (LPBF) in a cryogenic environment. CuCr1Zr is a precipitation hardening alloy, and changes in material properties were compared by applying various heat treatment conditions. The mechanical properties of materials manufactured using the LBPF method are evaluated through tensile tests at room temperature and cryogenic temperature (77 K), and the thermal properties are evaluated by deriving the thermal conductivity of CuCr1Zr according to various heat treatment conditions. In a cryogenic environment, the mechanical strength of STS 316L and CuCr1Zr increased by about 150% compared to room temperature, and the thermal conductivity of CuCr1Zr after heat treatment increased by about 6 to 10 times compared to before heat treatment at 40 K.

• Journal of Powder Materials
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• v.31 no.5
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• pp.422-430
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• 2024

This study investigated the optimal process conditions and mechanical properties of Cu-10Sn alloys produced by the powder bed fusion (PBF) method. The optimal PBF conditions were explored by producing samples with various laser scanning speeds and laser power. It was found that under optimized conditions, samples with a density close to the theoretical density could be fabricated using PBF without any serious defects. The microstructure and mechanical properties of samples produced under optimized conditions were investigated and compared with a commercial alloy produced by the conventional method. The hardness, maximum tensile strength, and elongation of the samples were significantly higher than those of the commercially available cast alloy with the same chemical composition. Based on these results, it is expected to be possible to use the PBF technique to manufacture Cu-10Sn products with complex 3D shapes that could not be made using the conventional manufacturing method.