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

Abstract 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 α -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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Publication Details

Journal
npj Computational Materials
Published
2025-03-02
DOI
https://doi.org/10.1038/s41524-025-01542-4
Citations
3
Primary Topic
Rock Mechanics and Modeling
Type
article
Field-Weighted Citation Impact
2.59

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article

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

Karsten Albe, Jochen Rohrer, Linus C. Erhard, Clemens Prescher et al.
3 citations
npj Computational Materials
Rock Mechanics and Modeling
2.59
article

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

Karsten Albe, Jochen Rohrer, Linus C. Erhard, Clemens Prescher, Christoph Otzen
article en
3 citations

Abstract

Abstract 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 α -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.

npj Computational MaterialsVol. 11(1)
University of Freiburg (DE), Technische Universität Darmstadt (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 13%
Rock Mechanics and Modeling
2.59
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