V21C-02:
On the Future of Thermochemical Databases, the Development of Solution Models and the Practical Use of Computational Thermodynamics in Volcanology, Geochemistry and Petrology: Can Innovations of Modern Data Science Democratize an Oligarchy?

Tuesday, 16 December 2014: 8:50 AM
Mark S Ghiorso, OFM Research, Redmond, CA, United States
Abstract:
Computational thermodynamics (CT) has now become an essential tool of petrologic and geochemical research. CT is the basis for the construction of phase diagrams, the application of geothermometers and geobarometers, the equilibrium speciation of solutions, the construction of pseudosections, calculations of mass transfer between minerals, melts and fluids, and, it provides a means of estimating materials properties for the evaluation of constitutive relations in fluid dynamical simulations. The practical application of CT to Earth science problems requires data. Data on the thermochemical properties and the equation of state of relevant materials, and data on the relative stability and partitioning of chemical elements between phases as a function of temperature and pressure. These data must be evaluated and synthesized into a self consistent collection of theoretical models and model parameters that is colloquially known as a thermodynamic database. Quantitative outcomes derived from CT reply on the existence, maintenance and integrity of thermodynamic databases. Unfortunately, the community is reliant on too few such databases, developed by a small number of research groups, and mostly under circumstances where refinement and updates to the database lag behind or are unresponsive to need. Given the increasing level of reliance on CT calculations, what is required is a paradigm shift in the way thermodynamic databases are developed, maintained and disseminated. They must become community resources, with flexible and assessable software interfaces that permit easy modification, while at the same time maintaining theoretical integrity and fidelity to the underlying experimental observations. Advances in computational and data science give us the tools and resources to address this problem, allowing CT results to be obtained at the speed of thought, and permitting geochemical and petrological intuition to play a key role in model development and calibration.