Thermodynamic modeling applied to understanding disequilibrium textures preserved in magmatic systems

Equilibrium based thermodynamic models are powerful tools for illuminating processes within magmatic systems that cannot be directly observed or occur on timescales greater than human lifetimes. However, chemical equilibrium is often not an accurate assumption in a dynamic system with a changing equilibrium state, such as one undergoing reheating or decompression. The extent of disequilibrium can be estimated from calculations of the chemical affinity of a mineral. This quantitative measure of disequilibrium is the thermodynamic driver for crystal nucleation, growth, or dissolution. Modeling the changes in the chemical affinity in temperature and pressure space for a given composition provides new insights about emerging textures (i.e. microlite growth or dissolution) in a system approaching or diverging from equilibrium. Here we calculate the chemical affinity of plagioclase saturation at a range of temperatures and pressures in MELTS to explore how plagioclase crystallization or dissolution may be slowed during reheating and decompression. Mineral phases are limited to plagioclase for simplicity and because its abundance in silicate melts. The code is written in python-based MELTS.

We apply this approach to data from the 2008 rhyolitic eruption of Chaitén Volcano in southern Chile. The Chaitén system is a good candidate for this study because of the presence of plagioclase microphenocrysts in the melt, and the microphenocrysts described in the study have textural indications that the system was not in equilibrium prior to ascent. By exploring a range of P-T paths and the resulting changes in chemical affinity for the magma during the eruption, we derive potential ascent histories for this eruption.