Glassy Dynamics from First-Principles Simulations

Abstract

The microscopic understanding of the dramatic increase in viscosity of liquids when cooled towards the glass transition is a major unresolved issue in condensed matter physics. Here, we use machine learning methods to accelerate molecular dynamics simulations with first-principles accuracy for the glass-former toluene. We show that the increase in viscosity is intimately linked to the increasing number of dynamically correlated molecules $N^{\ast }$. While certain hallmark features of glassy dynamics, like physical aging, are linked to $N^{\ast }$ as well, others, like relaxation stretching, are not.

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Cited by in corpus (6)

• On the Spectral Shape of the Structural Relaxation in Deeply Supercooled Liquids
• Dynamical Heterogeneity in Supercooled Water and its Spectroscopic Fingerprints
• Emergence of a Hump in the Cubic Dielectric Response of Glycerol
• Molecular dynamics insights into the Debye process of 1-propanol
• Computing dielectric spectra in molecular dynamics simulations: using a cavity to disentangle self and cross correlations
• Non-exponential relaxation without dynamic heterogeneity in van der Waals liquids above the melting point