Equilipy: a python package for calculating phase equilibria

Kwon, Sun Yong; Thibodeau, Eric; Plotkowski, Alex; Yang, Ying

doi:10.21105/joss.06875

Equilipy: a python package for calculating phase equilibria

Journal Article · Fri Aug 02 00:00:00 EDT 2024 · Journal of Open Source Software

DOI:https://doi.org/10.21105/joss.06875· OSTI ID:2428063

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Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Independent Researcher (Canada)

The CALPHAD (CALculation of PHAse Diagram) approach (Nigel Saunders & Miodownik, 1998) provides predictions for thermodynamically stable phases in multicomponent-multiphase materials across a wide range of temperatures. Consequently, the CALPHAD calculations became an essential tool in materials and process design (Luo, 2015). Such design tasks frequently require navigating a high-dimensional space due to multiple components involved in the system. This increasing complexity demands high-throughput CALPHAD calculations, especially in the rapidly evolving field of alloy design. In response to the need, we developed Equilipy an open-source Python package designed for calculating phase equilibria of multicomponent-multiphase systems. Equilipy is specifically tailored for high-throughput CALPHAD calculations, offering parallel computations across multiple processors and nodes with the given NPT input conditions namely elemental compositions (N), pressure (P), and temperature (T). Equilipy utilizes the program structure and Gibbs energy functions from the Fortran-based program, Thermochimica (Piro et al., 2013), with incorporating a new Gibbs energy minimization algorithm. This algorithm, originally developed by Capitani and Brown in 1987 (Capitani & Brown, 1987), has been revised and implemented to enhance the stability and performance of calculations. The Fortran codes are precompiled and interfaced with Python via F2PY, ensuring high computation speed. Benchmark tests shown in Figure 1 demonstrate that Equilipy’s computation speed is comparable to those of established commercial software, TC-Python and PanPython. This result highlights its efficiency and potential applications in various scientific and industrial fields.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Vehicle Technologies Office (VTO)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 2428063

Journal Information:: Journal of Open Source Software, Journal Name: Journal of Open Source Software Journal Issue: 100 Vol. 9; ISSN 2475-9066

Publisher:: Open Source Initiative - NumFOCUSCopyright Statement

Country of Publication:: United States

Language:: English

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