JESS, a Joint Expert Speciation System—V: Approaching thermodynamic property prediction for multicomponent concentrated aqueous electrolyte solutions
Rowland, D. and May, P.M. (2010) JESS, a Joint Expert Speciation System—V: Approaching thermodynamic property prediction for multicomponent concentrated aqueous electrolyte solutions. Talanta, 81 (1-2). pp. 149-155.
*Subscription may be required
Considerable difficulties persist in modelling the thermodynamics of multicomponent aqueous electrolyte solutions, especially at high concentrations. The widely adopted Pitzer formalism suffers from severe disadvantages, particularly with the combinatorial increase in mixing parameters required in multicomponent systems. As an alternative, the simple mixing rules of Young, of Harned and of Zdanovskii have been employed to predict the properties of mixtures using only the properties of the binary constituents with few or no additional parameters. Among these, Zdanovskii's rule is particularly promising because it constitutes a fundamental criterion for ideal mixing, i.e. when solutions having the same solvent activity are mixed in any proportion, the solvent activity remains unchanged. Many mixtures of strong electrolyte solutions are known from experiment to obey Zdanovskii's rule. This is important because application to aqueous electrolyte systems of practical interest has been hindered due to the process-intensive determination of water activities using the Gibbs-Duhem relation. This paper describes an alternative method which efficiently calculates the water activity of a multicomponent solution obeying Zdanovskii's rule. Some specific examples of the method are presented and various applications considered. In some systems, where deviations from Zdanovskii's rule occur, a single empirical parameter can be obtained and can be easily incorporated into the calculations.
|Publication Type:||Journal Article|
|Murdoch Affiliation:||School of Chemical and Mathematical Science|
|Copyright:||© 2009 Elsevier B.V.|
|Item Control Page|
Downloads per month over past year