We present Thermobar, a new open-source Python3 package for calculating pressures, temperatures, and melt compositions from mineral and mineral-melt equilibrium. Thermobar allows users to perform calculations with >100 popular parametrizations involving liquid, olivine-liquid, olivine-spinel, pyroxene only, pyroxene-liquid, two pyroxene, feldspar-liquid, two feldspar, amphibole only, amphibole-liquid, and garnet equilibria. Thermobar is the first open-source tool which can match up all possible pairs of phases from a given region, and apply various equilibrium tests to identify pairs from which to calculate pressures and temperatures (e.g. pyroxene-liquid, two pyroxene, feldspar-liquid, two feldspar, amphibole-liquid). Thermobar also contains functions allowing users to propagate analytical errors using Monte-Carlo methods, convert pressures to depths using different crustal density profiles, plot mineral classification and mineral-melt equilibrium diagrams, calculate liquid viscosities, and convert between oxygen fugacity values, buffer positions and Fe speciation in a silicate melt. Thermobar can be downloaded using pip and extensive documentation is available at https://thermobar.readthedocs.io/.
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This content will become publicly available on January 1, 2025
Surface phase diagrams from nested sampling
Studies in atomic-scale modeling of surface phase equilibria often focus on temperatures near zero Kelvin due to the challenges in calculating the free energy of surfaces at finite temperatures. The Bayesian-inference-based nested sampling (NS) algorithm allows for modeling phase equilibria at arbitrary temperatures by directly and efficiently calculating the partition function, whose relationship with free energy is well known. This work extends NS to calculate adsorbate phase diagrams, incorporating all relevant configurational contributions to the free energy. We apply NS to the adsorption of Lennard-Jones (LJ) gas particles on low-index and vicinal LJ solid surfaces and construct the canonical partition function from these recorded energies to calculate ensemble averages of thermodynamic properties, such as the constant-volume heat capacity and order parameters that characterize the structure of adsorbate phases. Key results include determining the nature of phase transitions of adsorbed LJ particles on flat and stepped LJ surfaces, which typically feature an enthalpy-driven condensation at higher temperatures and an entropy-driven reordering process at lower temperatures, and the effect of surface geometry on the presence of triple points in the phase diagrams. Overall, we demonstrate the ability and potential of NS for surface modeling.
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- Award ID(s):
- 2305155
- NSF-PAR ID:
- 10503541
- Publisher / Repository:
- arXiv
- Date Published:
- Journal Name:
- Physical Chemistry Chemical Physics
- ISSN:
- 1463-9076
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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