BeerOz, a set of Matlab routines for the quantitative interpretation of spectrophotometric measurements of metal speciation in solution

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Abstract

The modelling of the speciation and mobility of metals under surface and hydrothermal conditions relies on the availability of accurate thermodynamic properties for all relevant minerals, aqueous species, gases and surface species. Spectroscopic techniques obeying the Beer-Lambert law can be used to obtain thermodynamic properties for reactions among aqueous species (e.g., ligand substitution; protonation). BeerOz is a set of Matlab routines designed to perform both qualitative and quantitative analysis of spectroscopic data following the Beer-Lambert law. BeerOz is modular and can be customised for particular experimental strategies or for simultaneous refinement of several datasets obtained using different techniques. Distribution of species calculations are performed using an implementation of the EQBRM code, which allows for customised activity coefficient calculations. BeerOz also contains routines to study the n-dimensional solution space, in order to provide realistic estimates of errors and test for the existence of multiple local minima and correlation between the different refined variables. The paper reviews the physical principles underlying the qualitative and quantitative analysis of spectroscopic data collected on aqueous speciation, in particular for studying successive ligand replacement reactions, and presents the non-linear least-squares algorithm implemented in BeerOz. The discussion is illustrated using UV-Vis spectra collected on acidic Fe(III) solutions containing varying LiCl concentrations, and showing the change from the hexaaquo Fe(H2O)6 3+ complex to the tetrahedral FeCl4 - complex.

Original languageEnglish
Pages (from-to)248-261
Number of pages14
JournalComputers and Geosciences
Volume33
Issue number2
DOIs
Publication statusPublished - 1 Feb 2007
Externally publishedYes

Keywords

  • Aqueous geochemistry
  • Distribution of species
  • Principal component analysis
  • Spectroscopy

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