To predict mechanical properties of secondary hardening martensitic steels, a machine learning ensemble model was established. Based on ANN(Artificial Neural Network) architecture, some kinds of methods was considered to optimize the model. In particular, interaction features, which can reflect interactions between chemical compositions and processing conditions of real alloy system, was considered by means of feature engineering, and then K-Fold cross validation coupled with bagging ensemble were investigated to reduce R2_score and a factor indicating average learning errors owing to biased experimental database.

In this study, damping capacities were comparatively investigated for Mg-9%Al alloy with as-cast (AC) and fully discontinuous precipitates (DPs) microstructures, respectively. The DPs microstructure was obtained by solution treatment at 678 K for 24 h, followed by furnace cooling to RT. The AC microstructure was typically characterized by partially divorced eutectic β(Mg₁₇Al₁₂) phase particles distributed along the α-(Mg) matrix cell boundaries. The DPs microstructure showed lamellar morphology consisting of α and β thin layers with various interlamellar spacings. The DPs microstructure had better damping capacity than the AC microstructure in the strain-amplitude independent region, while in the strain-amplitude dependent region, the damping behavior was reversed. In view of the microstructural features of AC and DPs, the lower concentration of Al in the α-(Mg) phase for the DPs microstructure and the lower β phase number density for the AC microstructure would be responsible for the higher damping capacities in the strain-amplitude independent and strain-amplitude dependent regions, respectively.

The relationship between precipitation and coefficient of thermal expansion of Al-6%Si-0.4%Mg-0.9%Cu-(Ti) alloy (in wt.%) after various heat treatments were studied by the thermodynamic analyzer (TMA) and differential scanning calorimetry (DSC). Solution heat treatment of the alloy was carried out at 535℃ for 6 h followed by water quenching, and the samples were artificially aged in the air at 180℃ and 220℃ for 5 h. The coefficient of thermal expansion (CTE) curve showed some residual strain and decreased with increasing aging temperature. The CTE curves changed sharply in the temperature range of 200℃ to 400℃, and the corresponding peak shifted for the aged samples due to the change in the precipitation behavior of the secondary phase. These transformation peaks in the aged sample are related to the volume of the precipitation of the Si phase as determined by DSC analysis. The change in CTE is mainly caused by the precipitation of the Si phase in the Al-Si alloy, and the size of the change occurs simultaneously with the size of the precipitate.

The mechanical, anti-tarnishing, and corrosion characteristics of Yuggi (Cu-22wt%Sn) alloy are greatly affected by fraction of constituent phases according to heat treatment method. The Yuggi heat-treated at 750℃ has a β1' phase of 98% or more, which is a high-temperature disordered beta phase, on the other hand, cast Yuggi that Sn is solid-solutioned into Cu consists with α-phase over 60v/o. This difference of constituent phases of Yuggi may cause a difference in dissolution of Cu under antimicrobial test condition. Nonetheless, few studies have been conducted on the effect of fraction of constituent phases and constituent phases in antimicrobial activity. In addition, few studies have also been conducted on the suitable method measuring the antimicrobial activity of Yuggi. Hence, the purpose of this study is to provide an optimum measurement method of antimicrobial activity, and to evaluate quantitatively the effect of constituent phases on antimicrobial activity.

Following Silicon Carbide, single crystal diamond continues to attract attention as a next-generation semiconductor substrate material. In addition to excellent physical properties, large area and productivity are very important for semiconductor substrate materials. Research on the increase in area and productivity of single crystal diamonds has been carried out using various devices such as HPHT (High Pressure High Temperature) and MPECVD (Microwave Plasma Enhanced Chemical Vapor Deposition). We hit the limits of growth rate and internal defects. However, HFCVD (Hot Filament Chemical Vapor Deposition) can be replaced due to the previous problem. In this study, HFCVD confirmed the distance between the substrate and the filament, the accompanying growth rate, the surface shape, and the Raman shift of the substrate after vapor deposition according to the vapor deposition temperature change. As a result, it was confirmed that the difference in the growth rate of the single crystal substrate due to the change in the vapor deposition temperature was gained up to 5 times, and that as the vapor deposition temperature increased, a large amount of polycrystalline diamond tended to be generated on the surface.