Understanding phase transitions of α-quartz under dynamic compression conditions by machine-learning driven atomistic simulations

LC Erhard and C Otzen and J Rohrer and C Prescher and K Albe, NPJ COMPUTATIONAL MATERIALS, 11, 58 (2025).

DOI: 10.1038/s41524-025-01542-4

Characteristic shock effects in quartz serve as a key indicator of historic impacts at geologic sites. Despite this geologic significance, atomistic details of structural transformations of quartz under high pressure and shock compression remain poorly understood. This ambiguity is evidenced by conflicting experimental observations of both amorphization and transitions to crystalline polymorphs. Utilizing a newly developed machine-learning interatomic potential, we examine the response of alpha-quartz to shock compression with a peak pressure of 56 GPa over nanosecond timescales. We observe initial amorphization of quartz before crystallization into a d-NiAs-structured silica phase with disorder on the silicon sublattice, accompanied by the formation of domains with partial order of silicon. Investigating a variety of strain conditions of quartz enables us to identify non-hydrostatic stress and strain states that allow for direct diffusionless transformation to rosiaite-structured silica.

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