Dynamical classification of metallic supercooled liquids: Critical cooling rates and entropic signatures

B B. Zhang D D. M. Zhang (Key Laboratory for Computational Physical Sciences (MOE), Institute of Computational Physics, Fudan University 2 , 200433 Shanghai,) D D. Y. Sun (School of Physics and Electronic Science, East China Normal University 1 , 200241 Shanghai,) X X. G. Gong (Key Laboratory for Computational Physical Sciences (MOE), Institute of Computational Physics, Fudan University 2 , 200433 Shanghai,)

Abstract

Using molecular dynamics simulations, we systematically investigate supercooled liquids formed at cooling rates below and above the critical cooling rate (CCR). By analyzing the distribution of short-time averaged potential energies (DPE) and crystallization behaviors, we identify two distinct dynamical regimes in supercooled liquids: the glass-forming regime (GFR) and the crystal-forming regime (CFR). For systems cooled below CCR (CFR), the DPE exhibits a sharp peak, indicative of reduced configurational entropy. In contrast, liquids cooled above CCR (GFR) display a broad DPE distribution, reflecting higher configurational entropy. These findings establish a robust classification framework for supercooled liquids. Further analysis reveals a crossover temperature (Tx) in both regimes, consistent with the freezing temperature (Tf). Near Tx, crystallization barrier–temperature relationships exhibit abrupt changes. Below Tx, CFR crystallizes marginally faster than GFR, whereas above Tx, the influence of cooling rates on crystallization rates diminishes. These results further categorize GFR and CFR into high- and low-temperature sub-regimes, highlighting the interplay between thermodynamics and kinetics in supercooled liquids.

Article Details

Volume / Issue Vol. 163, Issue 3
Published July 21, 2025
ISSN 0021-9606
Publisher American Institute of Physics

Journal Info

The Journal of Chemical Physics

American Institute of Physics

ISSN: 0021-9606 Physical Sciences

Authors (4)

B

B. Zhang

D

D. M. Zhang

Key Laboratory for Computational Physical Sciences (MOE), Institute of Computational Physics, Fudan University 2 , 200433 Shanghai,

D

D. Y. Sun

School of Physics and Electronic Science, East China Normal University 1 , 200241 Shanghai,

X

X. G. Gong

Key Laboratory for Computational Physical Sciences (MOE), Institute of Computational Physics, Fudan University 2 , 200433 Shanghai,