Derivation of an Internally Consistent Thermodynamic Dataset by Mathematical Programming

Abstract

A reliable prediction of phase relations in mineral systems is central to geochemical research. As demonstrated in the foregoing chapters, a thermodynamic dataset based exclusively on calorimetry seldom allows computation of phase diagrams sufficiently accurate for geochemical applications. Nevertheless, calorimetry is, and will remain, the fundamental source of thermodynamic data, even if such data need to be fine-tuned for further use. The preceding chapters have also taught us that reaction reversals are effective constraints for calorimetric data. Thus, a combination of reversal brackets and calorimetry must give us a thermodynamic dataset best suited to accomplish our goal of computing precise phase diagrams. A thermodynamic dataset, compatible with calorimetry and reaction reversals alike, is called an internally consistent thermodynamic dataset.