• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2005.11a
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• pp.33-33
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• 2005

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2004.11a
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• pp.9-10
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• 2004

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2004.11a
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• pp.30-31
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• 2004

• Journal of Korea Foundry Society
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• v.26 no.2
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• pp.77-84
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• 2006

The effect of alloy composition on the glass forming ability (GFA) of the Ca-rich Ca-Mg-Zn alloys has been investigated in $Ca_{65}Mg_{5+x}Zn_{30-x}$ and $Ca_{55+x}Mg_{15}Zn_{30-x}$ (x=0, 5, 10, 15, 20) alloys. In a wide composition range of 15-25% Zn and 10-20% Mg bulk metallic glass (BMG) samples with the diameter larger than 6 mm are fabricated by conventional copper mold casting method in air atmosphere. Among the alloys investigated, the $Ca_{65}Mg_{15}Zn_{20}$ alloy exhibits the highest GFA enabling to form BMG sample with the diameter of at least 15 mm. The crystalline phase formed during solidification of $Ca_{65}Mg_{15}Zn_{20}$ ($D_{max}=15\;mm$) could be identified as a mixture of $Ca_3Zn$ and $CaMg_2$ cause by the redistribution of the constituent elements on long-range scale. The compressive fracture strength and fracture elongation of the $Ca_{65}Mg_{15}Zn_{20}$ BMG are 602 MPa and 2.08% respectively. The ${\sigma}$ parameter which has been recently proposed for evaluating GFA exhibits better correlation with GFA of Ca-Mg-Zn alloys than other parameters suggested so far such as ${\Delta}T_x$, $T_{rg}$, K, ${\gamma}$, and ${\Delta}T^*$ parameters.

• Journal of Welding and Joining
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• v.27 no.6
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• pp.43-48
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• 2009

In this study, Cu-based bulk metallic glass (BMG) coatings were deposited by atmospheric plasma spraying (APS) process with different process conditions (with- and without hydrogen gas). As adding the hydrogen gas, thermal energy in the plasma flame increased and induced difference in the melting state of the Cu-based BMG particles. The microstructure and mechanical properties of the coatings were analyzed using a scanning electron microscope (SEM) with an energy dispersive spectroscopy (EDS) and nano-indentation tester in the light of phase analysis. It was elucidated by the nano-indentation tests that un-melted region was a mainly amorphous phase which showed discrete plasticity observed as the flow serrations on the load.displacement (P - h) curves, and the curves of solidified region showed lower flow serrations as amorphous phase mingled with crystalline phase. Oxides produced during the spraying process had the highest hardness value among the phases and were well mixed with other phases resulted from the increase in melting degree.

• Korean Journal of Materials Research
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• v.34 no.7
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• pp.363-369
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• 2024

In this study, the magnetocaloric effect and transition temperature of bulk metallic glass, an amorphous material, were predicted through machine learning based on the composition features. From the Python module 'Matminer', 174 compositional features were obtained, and prediction performance was compared while reducing the composition features to prevent overfitting. After optimization using RandomForest, an ensemble model, changes in prediction performance were analyzed according to the number of compositional features. The R2 score was used as a performance metric in the regression prediction, and the best prediction performance was found using only 90 features predicting transition temperature, and 20 features predicting magnetocaloric effects. The most important feature when predicting magnetocaloric effects was the 'Fe' compositional ratio. The feature importance method provided by 'scikit-learn' was applied to sort compositional features. The feature importance method was found to be appropriate by comparing the prediction performance of the Fe-contained dataset with the full dataset.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2005.11a
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• pp.31-32
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• 2005

• Journal of Surface Science and Engineering
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• v.41 no.6
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• pp.301-307
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• 2008

In this paper, nanocrystallization of CuNiTiZr bulk metallic glass (BMG) subjecting to a kinetic spraying, dependent on impact velocity, was investigated by numerical and experimental approaches. The crystallization fraction and nucleation activation energy of initial feedstock and as-deposited coating were estimated by DSC and Kissinger method, respectively. The results of numerical modeling and experiment showed that the crystalline fraction and nucleation activation energy in BMG coatings were depended on kinetic energy of incident particle. Upon impact, the conversion of particle kinetic energy leads to not only decreasing free energy barrier but also increasing the driving force for an amorphous to crystalline phase transformation. The nanocrystallization of BMGs is associated with the strain energy delivered by a plastic deformation with a high strain rate.

• Korean Journal of Materials Research
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• v.33 no.7
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• pp.273-278
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• 2023

In this study, based on the saturation magnetic flux density experimental values (B_s) of 622 Fe-based bulk metallic glasses (BMGs), regression models were applied to predict B_s 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 B_s above the threshold value of B_s (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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.5743-5747
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• 2015

In this study, Fe-based bulk amorphous alloy powder manufactured using gas atomization fabrication was used for laser welding. the fracture behavior of welding layer were analyzed. Tensile test results show that the destruction occurred immediately after the elastic deformation, After plastic deformation of the substrate, the destruction occurred. The actual maximum tensile strength of the welding layer and the substrate are 959.9MPa and 220.4MPa. welding layer were each $485.5{\pm}21$ and $197.4{\pm}14$ to the substrate and the actual microhardness, The welding layer has very high hardness. The welding layer showed a very weak fine acicular structure. The base material was shown in the micro structure appear a coarse grain. SEM observations of the fracture after the tensile test. Fracture morphology of the base metal and the welding layer showed ductile fracture and brittle fracture, respectively.