The Algorithm to Predict the Grain Boundary Diffusion in Non-Dilute Metallic Systems.

Area of Science:

• Materials Science
• Physical Chemistry
• Metallurgy

Background:

• Grain boundary (GB) diffusion is crucial for understanding material properties and performance.
• Previous studies often focused on dilute solutions, limiting predictive power for non-dilute systems.
• Metallic systems based on Cu, Ni, Ag, and Al exhibit complex diffusion behaviors.

Purpose of the Study:

• To demonstrate common behaviors in grain boundary diffusion across various metallic systems.
• To identify key energetic parameters governing diffusion and segregation.
• To develop a predictive model for diffusing element behavior in non-dilute solutions.

Main Methods:

• Analysis of 11 metallic systems including Cu, Ni, Ag, and Al.
• Investigation of energetic parameters: energy of interaction with GB and interatomic interaction energy.
• Classification of systems into four groups based on segregation and phase formation tendencies.
• Mathematical formulation and solution of GB diffusion problems.

Main Results:

• Identified slow penetration in 11 systems, correlating with negative segregation or specific interatomic interactions.
• Proposed two energetic parameters as primary characteristics for GB diffusion.
• Established a qualitative method to predict diffusing element behavior in non-dilute solutions by grouping systems.
• Presented mathematical models and solutions for GB diffusion.

Conclusions:

• Common behaviors in GB diffusion exist across different metallic systems.
• Energetic parameters effectively characterize and predict diffusion and segregation tendencies.
• The developed classification and predictive method offer insights into non-dilute solution diffusion.