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Dynamics of phase separation in non-local elastic networks
Oliver W Paulin1, Yicheng Qiang1, David Zwicker1
1Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, 37077 Göttingen, Germany. david.zwicker@ds.mpg.de.
Non-local elasticity in polymer gels prevents coarsening during phase separation, forming patterned domains. This dynamic theory links phase separation to large-deformation poroelasticity for experimental comparison.
Area of Science:
- Soft Matter Physics
- Materials Science
- Biophysics
Background:
- Phase separation in elastic networks is crucial for biological and industrial systems like biomolecular condensates and soft sediments.
- Previous theories suggested equilibrium and non-local elastic effects drive pattern formation when domain size matches network pore size.
- Experimental evidence in synthetic polymer gels shows patterned phases emerge under specific conditions.
Purpose of the Study:
- To develop a dynamic theory coupling phase separation with non-local elasticity using large-deformation poroelasticity.
- To investigate the parameter space for phase separation and the influence of different elasticity models.
- To provide a framework for quantitative comparison between theoretical models and experimental results.
Main Methods:
- Developed a dynamic theory based on large-deformation poroelasticity.
- Employed linear stability analysis to identify phase separation conditions.
- Utilized numerical simulations to study the impact of elasticity models and parameter variations.
Main Results:
- Local elasticity can hinder phase separation and alter domain numbers but does not prevent coarsening.
- Non-local elasticity effectively arrests coarsening, leading to the formation of patterned domains with a defined length scale.
- The characteristic length scale of patterned domains inversely correlates with network stiffness.
Conclusions:
- Non-local elasticity is key to forming stable, patterned phases in liquid mixtures within elastic networks.
- The developed dynamic theory accurately models pattern formation and offers insights into coarsening arrest.
- The framework facilitates direct comparison with experimental data, particularly for strain-stiffening networks.
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