Predictive potentialities of the Quasi-Random Lattice model for electrolyte solutions, discussion and improvement strategies

Abstract

This article focuses on the predictive potentialities of the Quasi-Random Lattice (QRL) model, developed for describing the activity behaviour of electrolytic solutions, and elaborates strategies for their improvement.

First, the study critically discusses the computational-experimental procedure (previously published) for determining the QRL parameterization, whose convergence within few iterations is counterbalanced by known experimental issues concerning, in particular, the mean activity coefficient. An alternative procedure is proposed, that makes use of osmotic data at medium-high concentrations, so as to make QRL more interesting from a practical point of view.

Second, the study explores the applicability of the model beyond the concentration ranges earlier considered. To this purpose, the solution density is evaluated in detail. Its thermodynamic relationship with the mean activity coefficient yields a parametric Abel Equation of the Second Kind valid in the medium-high range of concentrations. A further density equation is formulated, useful in the low-medium range, based on a classical power-series combined with appropriate analytical constraints to improve estimation and prediction methods.

QRL theory, methods and procedures are applied to binary aqueous solutions at 25°C.