Configurational entropy measurements in extremely supercooled liquids that break the glass ceiling

Abstract

Liquids relax extremely slowly on approaching the glass state. One explanation is that an entropy crisis, because of the rarefaction of available states, makes it increasingly arduous to reach equilibrium in that regime. Validating this scenario is challenging, because experiments offer limited resolution, while numerical studies lag more than eight orders of magnitude behind experimentally relevant timescales. In this work, we not only close the colossal gap between experiments and simulations but manage to create in silico configurations that have no experimental analog yet. Deploying a range of computational tools, we obtain four estimates of their configurational entropy. These measurements consistently confirm that the steep entropy decrease observed in experiments is also found in simulations, even beyond the experimental glass transition. Our numerical results thus extend the observational window into the physics of glasses and reinforce the relevance of an entropy crisis for understanding their formation.

Does a Growing Static Length Scale Control the Glass Transition?

“…We shall infer from this outcome that E el rather than E coll is dominant in controlling τ α . This finding applies, strictly speaking, only to the polydisperse systems studied numerically in [20][21][22][23]. We then give a more general and complementary argument, to the effect that the Stokes-Einstein factor should obey S ≥ exp[E coll /k B T ] = τ α /τ el .…”

“…In this work we present arguments for the contrary view, proposing instead that most of the increase in τ α stems from an increase upon cooling of E el . Our main argument is based on recent numerical observations [20][21][22][23] in which a judicious choice of dynamics is shown to equilibrate systems far deeper inside the glass (T ≪ T G ) than previously achievable. Indeed this dynamics almost abolishes the glass transition.…”

“…Recent Monte-Carlo schemes have managed to equilibrate liquids at temperatures where traditional algorithms would need at least a 10 10 speedup to allow equilibration [20][21][22][23][24][25]. These swap algorithms consider polydisperse particles.…”

“…Accordingly the free energy landscape F ({r}) as a function of the particle positions {r} is, after integration over sizes, well defined and independent of the chosen dynamical rules. The swap rules can involve either well-separated particles as reported in [22,23], or be local, for instance restricted to nearest neighbour swaps [26]. For the dynamical rules of [22,23], the time scale τ + α on which density fluctuations relax with swaps [49] can be measured and compared to the value τ − α without swaps allowed.…”

“…The swap rules can involve either well-separated particles as reported in [22,23], or be local, for instance restricted to nearest neighbour swaps [26]. For the dynamical rules of [22,23], the time scale τ + α on which density fluctuations relax with swaps [49] can be measured and compared to the value τ − α without swaps allowed. The latter case behaves like molecular dynamics simulations, and display the standard glass transition.…”