Metastable states assisted homogeneous nucleation in supercooled liquid aluminum alloys: Insights from a phenomenologically coupled atomistic, phase-field, and machine learning investigation.

Crystallization due to liquid → solid transformation is observed in many natural and engineering processes. Extant literature indicates that crystallization in supercooled liquids is initiated by precursory metastable phases or states, also called non-classical nucleation. For face-centered cubic (FCC) materials, latest experimental and computational studies suggest that metastable hexagonal-closed packed (HCP) structures facilitate equilibrium FCC formation. However, the underlying nucleation mechanism remains unclear. Here, we examine structural changes and energetic barriers associated with such a non-classical mechanism, by performing molecular dynamics (MD) simulations using pure Al, Al-0.5 at. %Cu, and Al-0.5 at. %Ni (all FCC-formers) and phenomenologically coupling MD results with phase-field (PF) modeling. Such a coupling involved initializing PF simulation domains and constructing Landau polynomials-consistent with MD observations. Unsupervised machine learning was utilized to capture nuclei structures from MD simulations, while neural networks helped in extracting equilibrium interfacial energies from PF modeling. Atomistic simulations showed that precursory nuclei are comprised of collection of metastable-HCP states with medium ranged ordering. The pockets of HCP states later transform to critical nuclei-containing an FCC core and an outer layer of HCP. PF modeling qualitatively replicated the precursory-to-critical nuclei transformation and showed that the energetic barriers between the precursory and critical nuclei are substantially smaller than predictions obtained from classical nucleation theory. Together, these observations permitted us to propose a holistic non-classical mechanism that links triangular motifs within Al-based supercooled liquids to the critical nuclei via in-liquid structural transformations.