| name | mat-calphad-property-diagram |
| description | Calculate temperature-dependent thermodynamic properties like Equilibrium Phase Fractions for a specific alloy composition using CALPHAD models. |
| category | materials |
mat-calphad-property-diagram
Goal
To predict the equilibrium phase stability, phase fractions, and other extensive thermodynamic properties for a fixed multi-component alloy at different temperatures using PyCalphad. Very useful for modeling solidification, heat treatment paths, and precipitation sequences.
Instructions
1. Identify Thermodynamic Database
You must obtain a legitimate .tdb (Thermodynamic Data Base) file for the chemical system.
2. Plot Equilibrium Phase Fractions
Calculate what phases are present, and their molar fractions, across a cooling/heating schedule for a fixed composition.
python .agents/skills/mat-calphad-property-diagram/scripts/plot_phase_fractions.py path/to/database.tdb --elements Element1 Element2 --composition Element2 0.3 --t-range 300 1000 10 --output research_dir/phase_fractions.png
--composition: The solute element and its molar fraction (e.g. Zn 0.3 means 30 mol% Zn).--t-range: START STOP STEP in Kelvin. Ensure solving across liquidus and solidus.
Examples
Evaluating phase fractions for an Al-40%Zn alloy as it cools:
python .agents/skills/mat-calphad-property-diagram/scripts/plot_phase_fractions.py .agents/skills/mat-calphad-phase-diagram/examples/Al-Zn/alzn_mey.tdb --elements Al Zn --composition Zn 0.4 --t-range 300 900 10 --output phase_fractions.png
Constraints
- Environments: Scripts require the
calphad-agent Conda environment.
- Only plots equilibrium step (lever-rule). For non-equilibrium fast solidification (Scheil), custom scripting is required.
References
- Richard Otis and Zi-Kui Liu. "pycalphad: CALPHAD-based Computational Thermodynamics in Python." Journal of Open Research Software (2017).
Author: Bowen Deng
Contact: GitHub @learningmatter-mit
