Theoretical and Experimental Adsorption Studies of Polyelectrolytes on an Oppositely Charged Surface
R. Jay Mashl, Niels Gr{\o}nbech-Jensen (Theoretical Division and, Center for Nonlinear Studies, LANL) M. R. Fitzsimmons, M. L\"utt (Manuel, Lujan Jr. Neutron Scattering Center, LANL) DeQuan Li (Chemical Science and, Technology Division, LANL)

TL;DR
This study combines experimental and simulation approaches to investigate the electrostatic interactions and adhesion forces between charged polyelectrolytes and oppositely charged surfaces, revealing weak salt dependence and structural stability.
Contribution
It provides a comprehensive analysis of polyelectrolyte-surface interactions through combined theoretical, simulation, and experimental methods, highlighting the weak influence of salt concentration.
Findings
Adhesion force is weakly dependent on salt concentration.
Polymer monolayer structure remains stable across different ionic strengths.
Simulation results agree with Debye-Huckel approximation near 0.1 M salt.
Abstract
Using self-assembly techniques, x-ray reflectivity measurements, and computer simulations, we study the effective interaction between charged polymer rods and surfaces. Long-time Brownian dynamics simulations are used to measure the effective adhesion force acting on the rods in a model consisting of a planar array of uniformly positively charged, stiff rods and a negatively charged planar substrate in the presence of explicit monovalent counterions and added monovalent salt ions in a continuous, isotropic dielectric medium. This electrostatic model predicts an attractive polymer-surface adhesion force that is weakly dependent on the bulk salt concentration and that shows fair agreement with a Debye-Huckel approximation for the macroion interaction at salt concentrations near 0.1 M. Complementary x-ray reflectivity experiments on poly(diallyldimethyl ammonium) chloride (PDDA) monolayer…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
