A first-principles phase field method for quantitatively predicting multi-composition phase separation without...

Area of Science:

• Materials Science
• Computational Materials Science
• Thermodynamics

Background:

• Predicting alloy microstructures is crucial for designing tailored materials.
• Traditional phase field models (PFMs) require empirical parameters.
• First-principles methods struggle with the microstructural length scales relevant to alloys.

Purpose of the Study:

• To develop a parameter-free phase field model (PFM) for microstructure prediction.
• To enable microstructure prediction without relying on empirical adjustments.
• To provide a theoretical tool applicable to various alloy systems.

Main Methods:

• Combined density functional theory, cluster expansion theory, and potential renormalization theory.
• Derived a composition-dependent free energy function.
• Constructed a parameter-free PFM for microstructure evolution.

Main Results:

• Successfully predicted microstructures in high-temperature alloy phase diagrams.
• Applied the method to Ni-Al alloys at 1027°C, reproducing microstructure evolution solely based on composition.
• Observed excellent agreement between predicted and experimental microstructures, including cuboidal precipitations.

Conclusions:

• The developed parameter-free PFM accurately predicts alloy microstructures.
• This approach eliminates the need for empirical thermodynamic parameters.
• The method is broadly applicable to diverse alloy systems for materials design.