In this study, based on the saturation magnetic flux density experimental values (Bs) of 622 Fe-based bulk metallic glasses (BMGs), regression models were applied to predict Bs using artificial neural networks (ANN), and prediction performance was evaluated. Model performance evaluation was investigated by using the F1 score together with the coefficient of determination (R2 score), which is mainly used in regression models. The coefficient of determination can be used as a performance indicator, since it shows the predicted results of the saturation magnetic flux density of full material datasets in a balanced way. However, the BMG alloy contains iron and requires a high saturation magnetic flux density to have excellent applicability as a soft magnetic material, and in this study F1 score was used as a performance indicator to better predict Bs above the threshold value of Bs (1.4 T). After obtaining two ANN models optimized for the R2 and F1 score conditions, respectively, their prediction performance was compared for the test data. As a case study to evaluate the prediction performance, new Fe-based BMG datasets that were not included in the training and test datasets were predicted using the two ANN models. The results showed that the model with an excellent F1 score achieved a more accurate prediction for a material with a high saturation magnetic flux density.

The method of evaluating the forming limit of sheet metal is using the forming limit diagram(FLD), and the test method for measuring forming limit curve(FLC) is ISO standardized. On the other hand, in the case of metal bulk materials, it was confirmed that the forming limit was defined by using various predictive models based on the ductile fracture theory. However it did not show a constant forming limit (limit damage value) depending on the shape of the specimen. Therefore, a study was conducted on the derivation of the triaxial stress curve to predict the fracture of the material for various stress triaxiality, not the existing limit damage value.

A bulk-type Ta material is fabricated using the kinetic spray process and its microstructure and physical properties are investigated. Ta powder with an angular size in the range 9-37 μm (purity 99.95%) is sprayed on a Cu plate to form a coating layer. As a result, ~7 mm-sized bulk-type high-density material capable of being used as a sputter material is fabricated. In order to assess the physical properties of the thick coating layer at different locations, the coating material is observed at three different locations (surface, center, and interface). Furthermore, a vacuum heat treatment is applied to the coating material to reduce the variation of physical properties at different locations of the coating material and improve the density. OM, Vickers hardness test, SEM, XRD, and EBSD are implemented for analyzing the microstructure and physical properties. The fabricated Ta coating material produces porosity of 0.11~0.12%, hardness of 311~327 Hv, and minor variations at different locations. In addition, a decrease in the porosity and hardness is observed at different locations upon heat treatment.

본고에서는 고유한 원자구조에 기인한 우수한 특성으로 인해 구조재료 및 기능재료로서 그 활용이 기대되고 있는 벌크 아몰퍼스 소재에 있어 온간압출, 온간압연, 방전 플라즈마 소결(Spark Plasma Sintering)등 과냉각액체온도구간에서의 점성유동을 이용한 고화성형 공정의 최근 기술동향에 대해 간략히 소개했다.