The Ideal Thermodynamics of Ion-Exchange and Soil Solution Chemistry

Abstract

Thermodynamic models are widely used to predict ion-exchange behavior, aqueous electrolyte properties, contaminant transport, and waste treatment performance. However, large environmental and waste treatment systems such as those at the Hanford Site frequently involve complex multicomponent solutions where detailed thermodynamic calculations can become computationally expensive. The objective of this Thesis was to develop better tools including computationally efficient thermodynamic methods for multicomponent ion-exchange and aqueous electrolyte systems while improving understanding of the assumptions underlying their behavior.
The Thesis presents studies in two major areas: ion-exchange thermodynamics and aqueous electrolyte solution thermodynamics. For ion-exchange systems, new approaches were developed to fit and interpret multicomponent compositional data while accounting for mathematical constraints inherent in mixture systems. These studies
demonstrated that apparent interactions in multicomponent exchange systems may arise from compositional effects rather than true chemical interactions and identified ideal behavior in multicomponent ion-exchange on montmorillonite.
For aqueous electrolyte systems, this work examined the assumption that aqueous electrolytes are intrinsically non-ideal except at extreme dilution. Rubidium nitrite (RbNO₂) solutions were shown to exhibit near-ideal behavior even at very high concentrations.
Zavitsas' hydration model, which accounts for ion-pair formation and strongly bound water molecules, was extended to multicomponent systems and methods were developed to parameterize the model for sparingly soluble electrolytes and systems stable only in the presence of other electrolytes.
Collectively, these studies provide new methods for representing multicomponent ion-exchange and aqueous electrolyte systems using thermodynamically based yet computationally efficient approaches. These developments have potential applications in large-scale environmental and waste treatment models, including prediction of contaminant behavior and remediation performance at sites such as Hanford.

Date of Award	11 Jun 2026
Original language	English
Awarding Institution	University of Portsmouth
Supervisor	Jim Smith (Supervisor)