Published May 5, 2022 | Version Supplemental Material
Journal Article Open

Local-Average Free Volume Correlates with Dynamics in Glass Formers

  • 1. ROR icon Changchun Institute of Applied Chemistry
  • 2. ROR icon University of Illinois Urbana-Champaign
  • 3. ROR icon Yale-NUS College
  • 4. ROR icon California Institute of Technology

Abstract

Glass formers exhibit a pronounced slowdown in dynamics, accompanied by progressive heterogeneity as they approach the glass transition. There is intense debate over whether the dramatic slowdown is caused by dynamical heterogeneity and whether the enhanced dynamical heterogeneity originates from structural causes. However, the connection between dynamical heterogeneity and the spatial distribution of the single-particle free volume (a purely static structural quantity) was found to be rather weak, which raises the question of whether dynamic heterogeneity has a purely structural origin. Here, by introducing the concept of local-average free volume, we present numerical evidence that long-time dynamic heterogeneity shows significantly enhanced correlation with the average local free volume over a length scale of a few neighboring shells. Our results resolve the long-standing controversy about whether free volume plays an important role in particle rearrangements associated with the activated hopping relaxation. The concept of "local average" can be applied to other local structural descriptors to better correlate with dynamic heterogeneity in glass-forming liquids.

Additional Information

© 2022 American Chemical Society. Received 10 January 2022. Accepted 5 April 2022. Published online 28 April 2022. Published in issue 5 May 2022. This work was supported by the National Key R&D Program of China (Grant 2020YFA0713601) and the National Natural Science Foundation of China (Grants 21790340 and 22073092). Additional support for Y.L. was provided by the Youth Innovation Promotion Association of CAS (Grant Y202054). Z.-G.W. acknowledges financial support from the Hong Kong Quantum AI Lab Ltd. The authors declare no competing financial interest.

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Additional details

Identifiers

Eprint ID
114844
DOI
10.1021/acs.jpclett.2c00072
Resolver ID
CaltechAUTHORS:20220520-388267000

Funding

Ministry of Science and Technology (China)
2020YFA0713601
National Natural Science Foundation of China
21790340
National Natural Science Foundation of China
22073092
Chinese Academy of Sciences
Y202054
Hong Kong Quantum AI Lab Ltd

Dates

Created
2022-05-20
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Updated
2022-05-20
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