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Magnetically Induced Rotating Rayleigh-Taylor Instability
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Instabilities of complex fluids with partially structured and partially random interactions.

Giorgio Carugno1, Izaak Neri1, Pierpaolo Vivo1

  • 1Department of Mathematics, King's College London, Strand, London, WC2R 2LS, United Kingdom.

Physical Biology
|February 16, 2022
PubMed
Summary

This study introduces a new theory for complex fluid instabilities, revealing three distinct types: family condensation, family demixing, and random demixing. The findings offer insights into cellular processes like cytoplasm phase separation.

Keywords:
block structurefluid instabilitiesphase separationrandom matrix theory

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Area of Science:

  • Thermodynamics
  • Statistical Mechanics
  • Soft Matter Physics

Background:

  • Complex fluids with numerous interacting chemical species exhibit intricate phase behaviors.
  • Understanding thermodynamic instabilities is crucial for predicting fluid organization and function.
  • Previous models often simplified interactions, limiting their applicability to structured systems.

Purpose of the Study:

  • To develop a theoretical framework for thermodynamic instabilities in complex fluids with structured and random interactions.
  • To identify and characterize different types of fluid instabilities based on species organization.
  • To determine the critical conditions for these instabilities and apply the model to biological systems.

Main Methods:

  • Exact solution of a complex fluid model using random matrix theory.
  • Analysis of partially structured and partially random interaction potentials.
  • Determination of critical spinodal densities for various instability types.

Main Results:

  • Identified three distinct instabilities: family condensation, family demixing, and random demixing.
  • Found finite critical spinodal densities for family condensation and demixing.
  • Observed a square-root dependence of critical spinodal density on the number of species for random demixing.

Conclusions:

  • The developed theory accurately describes phase-separation phenomena in complex fluids.
  • The model provides a quantitative understanding of how species organization influences fluid instabilities.
  • The framework is applicable to biological contexts, such as pH-induced cytoplasm phase separation.