The interplay between size, shape, and surface segregation in high-entropy nanoalloys

Area of Science:

• Materials Science
• Computational Chemistry
• Nanotechnology

Background:

• High-entropy nanoalloys offer unique properties but their stability is complex.
• Understanding mixing behavior is crucial for designing stable nanoalloys.
• Particle size and shape influence energetic stability.

Purpose of the Study:

• Investigate particle shape and size effects on energetic stability of five-component multimetallic nanoparticles.
• Explore methods to approach ideal phase equilibrium in high-entropy nanoalloys.
• Characterize deviations from ideal solid solution behavior and evaluate entropy of mixing.

Main Methods:

• Computational investigation using embedded-atom model potentials.
• Exchange Monte Carlo simulations with systematic quenching.
• Percolation analysis and Gaussian regression modeling.

Main Results:

• AlCuFeCrNi nanoparticles show good mixing across considered conditions.
• AuCuPdNiCo nanoparticles exhibit significant segregation of cobalt and nickel.
• An approximation based on pair correlations effectively captures mixing entropy.

Conclusions:

• AlCuFeCrNi nanoparticles are promising for applications requiring good miscibility.
• AuCuPdNiCo nanoparticles deviate significantly from ideal random mixtures due to segregation.
• Gaussian regression can predict optimal mixing properties for stable nanoalloys.