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Label-free Isolation and Enrichment of Cells Through Contactless Dielectrophoresis

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Nonequilibrium relation between potential and stationary distribution for driven diffusion.

Christian Maes¹, Karel Netocný, Bidzina M Shergelashvili

¹Instituut voor Theoretische Fysica, K.U. Leuven, B-3001 Belgium. christian.maes@fys.kuleuven.be

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|August 8, 2009

Summary

This summary is machine-generated.

Applying a potential to diffusion processes affects particle density globally. Conversely, altering density locally requires significant potential changes. This study explores these nonequilibrium diffusion dynamics.

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Area of Science:

Statistical Physics
Non-equilibrium Thermodynamics
Diffusion Processes

Background:

Understanding the relationship between external potentials and particle distribution is crucial in statistical physics.
Nonequilibrium and overdamped diffusion systems exhibit complex behaviors not captured by equilibrium theories.

Purpose of the Study:

To investigate the relationship between applied potentials and stationary-state particle occupations in nonequilibrium diffusion.
To analyze the implications of local potential perturbations on global particle density and vice versa.

Main Methods:

Analysis of response theory for determining density from potential.
Exploration of inverse problem methods for determining potential from density.
Application of fluctuation theory to variational characterization of stationary states.

Main Results:

Local potential perturbations lead to long-range effects and global changes in relative particle density.
Creating localized changes in particle density necessitates substantial rearrangements of the applied potential.
A variational characterization of stationary density and potential was established.

Conclusions:

The study elucidates the intricate, often non-local, relationship between potentials and particle densities in nonequilibrium diffusion.
Findings have implications for controlling and predicting particle distributions in complex systems.
The work bridges response theory and fluctuation theory for a deeper understanding of dynamical systems.