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Symmetric diffusion equations, barodiffusion, and cross-diffusion in concentrated liquid mixtures
Martin E Schimpf1, Semen N Semenov
1Department of Chemistry, Boise State University, Boise, Idaho 83725, USA.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|November 5, 2004
Summary
This study introduces a new symmetric diffusion model for multicomponent mixtures, incorporating secondary pressure gradients to explain barodiffusion and diffusiophoresis. The model predicts lower concentration gradients and different diffusion coefficients compared to standard theories.
Area of Science:
- Physical Chemistry
- Chemical Engineering
- Thermodynamics
Background:
- Current diffusion models for multicomponent mixtures are often asymmetric and rely on arbitrary solvent selection.
- This leads to interpreter-dependent experimental data analysis, especially in concentrated mixtures.
Purpose of the Study:
- To derive a symmetric system of diffusion equations for multicomponent mixtures.
- To incorporate secondary pressure gradients, barodiffusion, and diffusiophoresis into diffusion modeling.
- To apply the new model to a binary mixture and compare predictions with standard theory.
Main Methods:
- Derivation of a symmetric system of diffusion equations using a spontaneously produced secondary pressure gradient.
- Introduction of barodiffusion (force = secondary pressure gradient × molecular volume).
- Inclusion of diffusiophoresis due to hydrodynamic stresses from concentration gradients.
Main Results:
- The new model predicts lower concentration gradients in binary mixtures compared to standard theories.
- The concentration dependence of the effective diffusion coefficient differs from standard predictions.
- The model was applied to a benzene and 1,2-dichloroethane mixture under a uniform force field.
Conclusions:
- The developed symmetric diffusion model offers a new perspective on multicomponent mixture behavior.
- The findings suggest potential for more accurate interpretation of experimental diffusion data.
- Proposed experiments aim to validate the new model against existing theoretical frameworks.