Multi-scale modelling of ions in solution : from atomistic descriptions to chemical engineering

Ions in solution play a fundamental role in many physical, chemical, and biological processes. For industrial applications these systems are usually described using simple analytical models which are fitted to reproduce the available experimental data. In this work, we propose a multi-scale coarse graining procedure to derive such models from atomistic descriptions. First, parameters for classical force-fields of ions in solution are extracted from ab-initio calculations. Effective (McMillan-Mayer) ion-ion potentials are then derived from radial distribution functions measured in classical molecular dynamics simulations, allowing us to define an implicit solvent model of electrolytes. Finally, perturbation calculations are performed to define the best possible representation for these systems, in terms of charged hard-sphere models. Our final model is analytical and contains no free "fitting" parameters. It shows good agreement with the exact results obtained from Monte-Carlo simulations for the thermodynamic and structural properties. Development of a similar model for the electrolyte viscosity, from information derived from atomistic descriptions, is also introduced.

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Source https://theses.hal.science/tel-00825566
Author Molina, John Jairo
Maintainer CCSD
Last Updated May 11, 2026, 00:57 (UTC)
Created May 11, 2026, 00:57 (UTC)
Identifier NNT: 2011PA066363
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Physicochimie des Electrolytes, Colloïdes et Sciences Analytiques (PECSA) ; Université Pierre et Marie Curie - Paris 6 (UPMC)-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris) ; Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut de Chimie - CNRS Chimie (INC-CNRS)-Centre National de la Recherche Scientifique (CNRS)
creator Molina, John Jairo
date 2011-09-29T00:00:00
harvest_object_id 61de2ff8-0e73-4944-8702-fc881e207f89
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2025-08-12T00:00:00
set_spec type:THESE