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An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
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Qualitatively different collective and single-particle dynamics in a supercooled liquid
Madhu Priya1, Neeta Bidhoodi1, Shankar P Das1
1School of Physical Sciences, Jawaharlal Nehru University, New Delhi 110067, India.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|January 15, 2016
Summary
This study reveals a key difference in particle dynamics during the ergodic-nonergodic transition in binary mixtures. Collective density fluctuations freeze, but tagged particle correlations continue to decay, challenging existing mode coupling theory predictions.
Area of Science:
- Nonlinear hydrodynamics
- Statistical mechanics
- Condensed matter physics
Background:
- Mode Coupling Theory (MCT) describes the ergodic-nonergodic (ENE) transition in complex fluids.
- Existing MCT posits simultaneous freezing of collective and single-particle dynamics at the ENE transition.
Purpose of the Study:
- To investigate the dynamics of tagged particles in a binary mixture near the ergodic-nonergodic transition.
- To re-evaluate the predictions of Mode Coupling Theory regarding the simultaneous freezing of correlations.
Main Methods:
- Derivation of fluctuating nonlinear hydrodynamic equations for a two-component mixture.
- Construction of MCT equations from these nonlinear hydrodynamics.
- Analysis using a nonperturbative approach in the one-component limit.
Main Results:
- The ergodic-nonergodic transition is characterized by the freezing of collective density fluctuations.
- Contrary to MCT, tagged-particle correlations were shown to decay to zero at this transition.
- This indicates a decoupling of collective and single-particle dynamics.
Conclusions:
- The point where self-diffusion extrapolates to zero does not align with the ENE transition predicted by simple MCT.
- This finding necessitates a revision of current models for glassy dynamics in mixtures.
- Highlights the importance of nonperturbative approaches for understanding complex system dynamics.
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