P042-0014
A Python-Implemented Deep Earth Water Model to Aid in Determining the Composition of Icy Ocean World Interiors
A Python-Implemented Deep Earth Water Model to Aid in Determining the Composition of Icy Ocean World Interiors
Friday, 11 December 2020
Poster
Abstract:
Currently, the Helgeson-Kirkham-Flowers (HKF) model is used to calculate thermodynamic properties of aqueous complexes and ions at differing temperatures and pressures. However, this model has certain regions of density and pressure where, for certain temperatures, it is inaccurate at predicting the speciation of solutes (Miron, Leal, & Yapparova, 2019). The combination of a different model for the properties of water alongside the Deep Earth Water (DEW) model (Huang & Sverjensky, 2019) could prove robust in determining the composition and evolution of icy ocean worlds interiors. We specifically explore the combination of SeaFreeze (Journaux, 2019), a Local Basis Function evaluation-based package that allows a user to examine icy polymorphs at different temperatures and pressures, with the DEW model. We present an object-oriented implementation of the DEW model which allows for convenient array inputs of custom water properties, specifically the Gibbs free energy, dielectric constant, and water density. Our implementation behaves identically to the Excel spreadsheet-implemented DEW model while additionally simplifying and streamlining the process to input reactions and make changes to calculations quickly. Additionally, our model builds in the full set of minerals from the thermodynamic database SUPCRTBL.dat (Zimmer et al., 2016), to provide an easy way to access a full range of minerals thermodynamic properties without having to calculate them separately. We compare the calculated properties of water from the DEW model and to those calculated by SeaFreeze. We find a discrepancy between the two models indicates a need to reevaluate the parameterization of the DEW model. We also present a set of reactions relevant to icy ocean world interiors calculated with the SeaFreeze-predicted ΔGr of water incorporated into the Python implementation of the DEW model and a cross-comparison between these calculations and those with the “original” DEW model implementation.
A part of the research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. © 2020. All rights reserved.