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PreprintCC BY 4.0arXiv

Glassy dynamics, crossover temperature and density scaling in fragile glass-formers

Abstract

We investigate the slowing down of dynamics in a glass-forming mixture interacting via an inverse-power-law (IPL) potential using a combination of theory and large-scale molecular dynamics simulations. We measure the static pair-correlation function, configurational entropy, inherent-structure energy, and structural relaxation time. We employ a theoretical framework to calculate the structural relaxation time τα, which is found to be in very good agreement with the simulation results. The theory identifies a local structural order which defines the cooperativity of the relaxation and brings forth a fluctuation induced parameter $ψ( T )$ and a crossover temperature Ta that characterize the density and temperature dependence of the glassy dynamics. Furthermore, we determine a crossover temperature using independent dynamical and thermodynamic criteria and compare with the theoretically predicted crossover temperature Ta. Relaxation dynamics is shown to obey density-temperature scaling, similar to thermodynamic properties, in terms of a variable Γ formed by an appropriate combination of density and temperature, characteristic of IPL interactions. Finally, we show that, when the excess thermodynamic and dynamic quantities obtained at different densities are plotted as functions of the reduced temperature T/Ta (or Ta/T), the data collapse onto master curves with excellent agreement between theory and simulation. These scaling relations provide a unified description of the thermodynamics and dynamics in IPL systems, enabling the prediction of relaxation behavior over a wide range of densities from data at a single state point.

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BibTeX
@misc{singh2026glassy,
  title = {{Glassy dynamics, crossover temperature and density scaling in fragile glass-formers}},
  author = {Ankit Singh and Vinay Vaibhav and Swarn Lata Singh and Yashwant Singh},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.05159},
  eprint = {2609.05159},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.05159},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Glassy dynamics, crossover temperature and density scaling in fragile glass-formers
AU  - Ankit Singh
AU  - Vinay Vaibhav
AU  - Swarn Lata Singh
AU  - Yashwant Singh
PY  - 2026
DA  - 2026/09/04
PB  - arXiv
DO  - 10.48550/arxiv.2609.05159
UR  - https://arxiv.org/abs/2609.05159
AB  - We investigate the slowing down of dynamics in a glass-forming mixture interacting via an inverse-power-law (IPL) potential using a combination of theory and large-scale molecular dynamics simulations. We measure the static pair-correlation function, configurational entropy, inherent-structure energy, and structural relaxation time. We employ a theoretical framework to calculate the structural relaxation time τ_α, which is found to be in very good agreement with the simulation results. The theory identifies a local structural order which defines the cooperativity of the relaxation and brings forth a fluctuation induced parameter $ψ( T )$ and a crossover temperature T_a that characterize the density and temperature dependence of the glassy dynamics. Furthermore, we determine a crossover temperature using independent dynamical and thermodynamic criteria and compare with the theoretically predicted crossover temperature T_a. Relaxation dynamics is shown to obey density-temperature scaling, similar to thermodynamic properties, in terms of a variable Γ formed by an appropriate combination of density and temperature, characteristic of IPL interactions. Finally, we show that, when the excess thermodynamic and dynamic quantities obtained at different densities are plotted as functions of the reduced temperature T/T_a (or T_a/T), the data collapse onto master curves with excellent agreement between theory and simulation. These scaling relations provide a unified description of the thermodynamics and dynamics in IPL systems, enabling the prediction of relaxation behavior over a wide range of densities from data at a single state point.
ER  -