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Updated: May 27, 2026

Generation and Control of Electrohydrodynamic Flows in Aqueous Electrolyte Solutions
Published on: September 7, 2018
Linear and nonlinear evolution and diffusion layer selection in electrokinetic instability
E A Demekhin1, V S Shelistov, S V Polyanskikh
1Aerodynamics Laboratory, Institute of Mechanics for Moscow State University, Moscow, 119192, Russian Federation. edemekhi@gmail.com
Direct numerical simulation reveals four stages of electrokinetic instability in ion-exchange membranes. A primary instability arrests diffusion layer growth and sets a characteristic length, validating prior experimental predictions.
Area of Science:
- Electrokinetics
- Fluid Dynamics
- Physical Chemistry
Background:
- Electrokinetic phenomena are crucial in ion-exchange membranes.
- Understanding instability dynamics is key to controlling membrane performance.
- Previous theories predicted self-similar evolution and primary instabilities.
Purpose of the Study:
- To identify and characterize the stages of electrokinetic instability.
- To numerically simulate Rubinstein and Zaltzman instability and nonlinear evolution.
- To compare simulation results with theoretical and experimental predictions.
Main Methods:
- Direct numerical simulation (DNS) of the Nernst-Planck-Poisson-Stokes system.
- Analysis of four distinct stages of electrokinetic instability.
- Comparison of numerical results with established theoretical and experimental data.
Main Results:
- Four nontrivial stages of electrokinetic instability were identified.
- Self-similar evolution was confirmed at moderately large times.
- Primary instability was observed to arrest diffusion layer growth and define characteristic length.
- A novel principle for characteristic wave-number selection from noise was established.
Conclusions:
- The study confirms and elaborates on the stages of electrokinetic instability.
- Numerical simulations align with experimental findings regarding primary instability and characteristic length.
- A new mechanism for wave-number selection in noisy systems was discovered.
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