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Dressed counterions: Strong electrostatic coupling in the presence of salt

2009/12/31 by Matej Kanduč, Matej Kanduc, Ali Naji +2 · 1 citation
Chemistry · Earth and Planetary Sciences · Mathematics · Physics and Astronomy · #Chemical physics #Chemistry #Counterion #Coupling (piping) #Debye length #Electrochemical Analysis and Applications #Electrolyte #Electrostatics #Electrostatics and Colloid Interactions #Geophysical and Geoelectrical Methods #Ion #Materials science #Mathematics #Monte Carlo method #Physical chemistry #Physics #Quantum mechanics #Salt (chemistry) #Statistical physics #cond-mat.soft #cond-mat.stat-mech

paper · pdf · doi:10.1063/1.3361672

published as J. Chem. Phys. 132, 124701 (2010) · 17 pages, 10 figures

arxiv created 2010/02/22 · openalex publication_date 2010/03/23 · arxiv updated 2015/05/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

We reformulate the theory of strong electrostatic coupling in order to describe an asymmetric electrolyte solution of monovalent salt ions and polyvalent counterions using field-theoretical techniques and Monte Carlo simulations. The theory is based on an asymmetric treatment of the different components of the electrolyte solution. The weak coupling Debye-Hückel approach is used in order to describe the monovalent salt ions while a strong coupling approach is used to tackle the polyvalent counterions. This combined weak-strong coupling approach effectively leads to dressed interactions between polyvalent counterions and thus directly affects the correlation attraction mediated by polyvalent counterions between like-charged objects. The general theory is specifically applied to a system composed of two uniformly charged plane-parallel surfaces in the presence of salt and polyvalent counterions. In the strong coupling limit for polyvalent counterions, the comparison with Monte Carlo simulations shows good agreement for large enough values of the electrostatic coupling parameter. We delineate two limiting laws that in fact encompass all the Monte Carlo data.

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