Abstract
Theoretical prediction of glass forming ability (GFA) of metallic alloys is a key process in exploring metallic alloy compositions with excellent GFA and thus with the ability to form a large-sized bulk metallic glass. Molecular dynamics (MD) simulation is a promising tool to achieve a theoretical prediction. However, direct MD prediction continues to be challenging due to the time-scale limitation of MD. With respect to practical bulk metallic glass alloys, the time necessary for quenching at a typical cooling rate is five or more orders of magnitude higher than that at the MD time-scale. To overcome the time-scale issue, this study proposes a combined method of classical nucleation theory and MD simulations. The method actually allows to depict the time-temperature-transformation (TTT) diagram of the bulk metallic glass alloys. The TTT directly provides a prediction of the critical cooling rate and GFA. Although the method assumes conventional classical nucleation theory, all the material parameters appearing in the theory were determined by MD simulations using realistic interatomic potentials. The method is used to compute the TTT diagrams and critical cooling rates of two Cu-Zr alloy compositions (Cu50Zr50 and Cu20Zr80). The results indicate that the proposed method reasonably predicts the critical cooling rate based on the computed TTT.
Highlights
Metallic glasses possess brilliant properties as structural materials including high elastic limit[1], high toughness[2], and high corrosion resistance[3]
It is necessary to establish a method to predicting the TTT diagram as it can lead to a computational high-throughput screening of alloy composition to obtain a larger bulk metallic glass sample
Molecular dynamics (MD) simulation is the best tool available for the computation of the incubation time because the critical crystal nucleus typically corresponds to the nanometer range[6], and it is necessary for the crystal nucleation process to consist of atomic scale events
Summary
Two alloy compositions possessing different GFA, such as Cu50Zr50 and Cu20Zr80, are examined in the study to demonstrate the proposed method. The atomic number density of the melt ρmelt and that of the critical crystal nucleus ρc⁎rystal are computed and summarized in Table 2 by taking the average volume of simulation cell V (N = 16,000) with PBC over 100 ps NPT ensemble MD simulation at the critical temperature and a zero pressure condition. In order to compute the attachment rate, 4 ns NPT ensemble MD simulations on the same melt spherical crystal model with r = r*(T) used in the previous analysis are performed at different temperatures ranging from 1,060 to 1,160 K under a zero pressure condition. It is expected that the method can open up a computational high-throughput screening of higher GFA alloys
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