Thermodynamic modeling with uncertainty quantification using the modified quasichemical model in quadruplet approximation: Implementation into PyCalphad and ESPEI

TL;DR

This paper integrates the modified quasichemical model in quadruplet approximation into open-source tools PyCalphad and ESPEI, enabling thermodynamic calculations and uncertainty quantification for complex liquids with short-range order.

Contribution

It introduces a new implementation of MQMQA into PyCalphad and ESPEI, including a novel XML database structure for enhanced thermodynamic modeling and UQ capabilities.

Findings

Successful implementation demonstrated with KF-NiF2 system

Thermodynamic calculations of Gibbs energy and phase diagrams performed

Database development with uncertainty quantification achieved

Abstract

The modified quasichemical model in the quadruplet approximation (MQMQA) considers the first- and the second-nearest-neighbor coordination and interactions, particularly useful in describing short-range ordering in complex liquids such as molten salts, slag in metal processing, and electrolytic solutions. The present work implements the MQMQA into the Python based open-source software PyCalphad for thermodynamic calculations. This endeavor facilitates the development of MQMQA-based thermodynamic database with uncertainty quantification (UQ) using the open-source software ESPEI. A new database structure based on Extensible Markup Language (XML) is proposed for ESPEI evaluation of MQMQA model parameters. Using the KF-NiF2 system as an example, we demonstrate the successful implementation of MQMQA in PyCalphad through thermodynamic calculations of Gibbs energy, equilibrium quadruplet fractions, and phase diagram, as well as database development with UQ using ESPEI. The present implementation offers an open-source capability for performing CALPHAD modeling for complex liquids with short-range ordering using MQMQA.