Quantifying chemical short-range order in metallic alloys

Area of Science:

• Materials Science
• Computational Materials Science
• Alloy Physics

Background:

• Metallic alloys form solid solutions where elements occupy crystal lattice sites.
• Chemical short-range order (SRO) describes non-random arrangements of elements in alloys.
• Quantifying SRO in complex alloys like high-entropy alloys is challenging due to configurational complexity.

Purpose of the Study:

• To develop and present a multiscale method for predicting and quantifying SRO in alloys at atomic resolution.
• To bridge the gap between electronic-structure calculations and the characteristic length scale of SRO.
• To correlate SRO with fundamental material properties like local lattice distortions.

Main Methods:

• A multiscale computational approach integrating machine learning techniques.
• Utilizing electronic-structure calculations to inform SRO predictions.
• Developing a method to quantify SRO length scales and spatial distribution.

Main Results:

• The developed method accurately predicts SRO length scales, aligning with experimental measurements.
• Established comprehensive correlations between SRO and fundamental quantities, including local lattice distortions.
• Demonstrated the capability to quantify SRO at atomic resolution.

Conclusions:

• The new method advances the quantitative understanding of SRO in solid-solution phases.
• This work enables the rigorous incorporation of SRO length scales into predictive mechanical and thermodynamic models.
• Facilitates the design and optimization of advanced metallic alloys with tailored properties.