An experiment has shown that ~10 nm Si nanoparticles undergo a Si-I (diamond cubic) to Si-V (simple hexagonal) phase transition under compression, in contrast to the Si-I to Si-II (tetragonal) transition observed in bulk silicon. However, the atomistic mechanism underlying this size-dependent transition pathway remains unclear. Here, we employ molecular dynamics simulations with a machine learning interatomic potential to reveal a stress triaxiality driven, two-step Si-I to Si-V transition pathway in a spherical Si nanoparticle subjected to an idealized triaxial contact loading model. An intermediate amorphous phase nucleates at the nanoparticle surface and propagates inward around the Si-I core in regions of low stress triaxiality dominated by shear. Within this amorphous shell, Si-V recrystallizes at locations with elevated stress triaxiality and hydrostatic pressure. Upon unloading, the Si-V structure transforms into an amorphous state. A subsequent loading-unloading cycle applied to this amorphous nanoparticle reveals a reversible amorphous-to-Si-V transformation, demonstrating a nanoscale phase-memory effect.

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