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The electrostatic persistence length of polymers beyond the OSF limit
R Everaers1, A Milchev, V Yamakov
1Max-Planck-Institut für Polymerforschung, Postfach 3148, D-55021 Mainz, Germany. everaers@mpip-maiz.mpg.de
The European Physical Journal. E, Soft Matter
|March 11, 2004
Summary
Large-scale simulations confirm that the electrostatic persistence length of charged polymers scales with the inverse square of the screening length (l(e) ∝ κ⁻²). This finding supports existing theories and rules out linear or sublinear dependencies.
Area of Science:
- Polymer Physics
- Computational Chemistry
- Statistical Mechanics
Background:
- Understanding the behavior of charged polymers (polyelectrolytes) in solution is crucial for various applications.
- Electrostatic interactions significantly influence polymer conformation, particularly the persistence length.
- Existing theories predict specific scaling relationships for electrostatic persistence length with screening length.
Purpose of the Study:
- To rigorously test scaling theories for the electrostatic persistence length of uniformly charged polymers.
- To investigate the dependence of electrostatic persistence length on screening length in the limit of large screening lengths.
- To clarify discrepancies in previous studies regarding polyelectrolyte scaling behavior.
Main Methods:
- Large-scale Monte Carlo simulations were employed.
- Simulations covered an extensive parameter space, exceeding previous studies.
- Debye-Hückel intrachain interactions were incorporated for uniformly charged polymers.
Main Results:
- No significant deviations were observed from the predicted scaling law l(e) ∝ κ⁻².
- The Khokhlov and Khachaturian prediction, based on Odijk-Skolnick-Fixman theories, was validated.
- Linear or sublinear dependencies of persistence length on screening length were conclusively ruled out.
Conclusions:
- The study validates theoretical predictions for electrostatic persistence length in polyelectrolytes.
- Finite chain length and excluded-volume effects were identified as sources of previous discrepancies.
- Scaling arguments are highlighted as essential for developing accurate models for experimental and simulation data.