Composition reign favored for the formation of CuZrAl amorphous phases investigated by ion beam mixing

Bai, Xue; Li, J.H.; Cui, Yuanyuan; Liu, B.X.

doi:10.1016/j.matlet.2012.10.100

Cited by 2 publications

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References 10 publications

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“…While many efforts have been devoted to exploring combinations of materials to form stable metallic glasses [13][14][15][16][17] as well as microstructure analysis, it is believed that understanding the fundamental aspects of the liquid state dynamics of these melts still holds the key to understanding their glass-forming abilities.…”

Section: Introductionmentioning

confidence: 99%

Atomic-scale dynamics of a model glass-forming metallic liquid: Dynamical crossover, dynamical decoupling, and dynamical clustering

2015

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The phase behavior of multi-component metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamical aspects of a model ternary metallic liquid Cu40Zr51Al9 using molecular dynamics simulations with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (self diffusion coefficient, self relaxation time, and shear viscosity) bordered at Tx ∼ 1300 K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs well above the melting point of the system (Tm ∼ 900 K) in the equilibrium liquid state; and the crossover temperature Tx is roughly twice of the glass-transition temperature of the system (Tg). Below Tx, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a non-parametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below Tx and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter α2 and the four-point correlation function χ4.

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