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Chaos and threshold for irreversibility in sheared suspensions
D J Pine1, J P Gollub, J F Brady
1Department of Chemical Engineering and KITP, University of California, Santa Barbara, California 93106-5080, USA. pine@nyu.edu
Nature
|December 16, 2005
Summary
Researchers experimentally observed how time reversibility fails in slowly sheared suspensions. A concentration-dependent strain threshold causes particle configurations to become unpredictable, resembling anisotropic random walks.
Area of Science:
- Statistical physics
- Soft matter physics
- Non-equilibrium systems
Background:
- Time-reversible equations of motion can lead to irreversible behavior in many-body systems.
- This transition is fundamental but experimentally unobserved in many systems.
- Low Reynolds number fluid flow, like sheared Newtonian fluids and suspensions, is typically time-reversible.
Purpose of the Study:
- To experimentally demonstrate the failure of time reversibility in slowly sheared suspensions.
- To identify the conditions and mechanisms leading to irreversible behavior in these systems.
- To connect the observed irreversibility to concepts of chaos and predictability.
Main Methods:
- Experimental shearing of particle suspensions at various concentrations.
- Measurement of particle displacements and configurations over multiple shear cycles.
- Numerical simulations to model particle interactions and chaotic dynamics.
- Calculation of Lyapunov exponents to quantify chaotic behavior.
Main Results:
- A concentration-dependent strain threshold was identified, beyond which time reversibility fails.
- Particle displacements after cycling followed anisotropic random walk statistics.
- A pronounced growth in the Lyapunov exponent was observed at the threshold strain.
- Experimental results were consistent with numerical simulations.
Conclusions:
- The study provides the first experimental observation of time reversibility failure in sheared suspensions.
- The threshold strain is linked to the onset of chaotic particle interactions.
- This work bridges the understanding of chaos, reversibility, and predictability in soft matter systems.
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