Cluster and network formation in Fe-Si-B amorphous alloys: a machine learning molecular dynamics study

Area of Science:

• Materials Science
• Condensed Matter Physics
• Computational Materials Science

Background:

• Local atomic arrangements, including short- and medium-range order (SRO and MRO), dictate amorphous material properties.
• Gaskell's 1979 model proposed that structural motifs in transition metal-metalloid glasses mirror crystalline ordering.
• Amorphous Fe-Si-B alloys are crucial soft-magnetic materials for energy-efficient motors.

Purpose of the Study:

• Investigate SRO and MRO in amorphous Fe-Si-B alloys.
• Clarify the structural roles of minor elements Boron (B) and Silicon (Si).
• Validate Gaskell's structural model for amorphous alloys.

Main Methods:

• Utilized a previously developed machine-learning interatomic potential (Gaussian Approximation Potential framework).
• Performed melt-quench molecular dynamics simulations on 2,048-atom systems.
• Analyzed SRO and MRO to understand element-specific cluster geometries and connectivity.

Main Results:

• Boron-centered clusters predominantly form bi-capped anti-prism (BAP) and tri-capped trigonal prism (TTP) geometries, mirroring crystalline Fe₂B and Fe₃B.
• Silicon-centered clusters preferentially adopt icosahedral motifs, typical of amorphous structures.
• Boron clusters, especially BAP, exhibit a greater tendency for network formation at the MRO level compared to silicon clusters.

Conclusions:

• Simulation results strongly support Gaskell's model by demonstrating crystalline-like ordering in Boron clusters.
• Distinct structural preferences of Boron and Silicon contribute to the unique properties of amorphous Fe-Si-B alloys.
• Understanding SRO and MRO is key to designing advanced soft-magnetic materials.