mat-phase-field-non-conservative

You can simulate grain growth by running the provided Python scripts for the Allen-Cahn non-conservative phase-field benchmark. The simulation evolves a non-conserved order parameter to reduce interfacial energy and outputs visualizations of curvature-driven grain shrinkage as GIFs or PNGs.

Yes, you can model dendrite growth using the Kobayashi-style phase-field simulation included in the Skill. It couples phase-field evolution with thermal dynamics and anisotropy to produce dendritic morphologies and saves the results as reproducible visual outputs.

Yes, you need FiPy along with numpy, scipy, matplotlib, and imageio. These dependencies must be installed in the phasefield-agent environment to execute the numerical PDE scripts and generate visual outputs.

The Allen-Cahn equation models non-conservative phase-field evolution, driving curvature-driven boundary motion for grain shrinkage. The Cahn-Hilliard equation handles conserved order parameters, whereas this Skill specifically focuses on non-conservative dynamics.

You visualize phase transformations by executing the 2D benchmark scripts and generating outputs with matplotlib and imageio. The process produces reproducible visual outputs like PNGs or GIFs showing the evolving materials microstructure.

The Allen-Cahn equation is limited to non-conserved order parameters, making it suitable for curvature-driven grain shrinkage and solid-liquid transformations but unsuitable for conserved quantities like concentration fields found in spinodal decomposition.