Data underlying the research of Kinetic and thermodynamic transition pathways of silica by machine learning: implication for meteorite impacts

Datacite citation style:
Cao, Xuyan (2024): Data underlying the research of Kinetic and thermodynamic transition pathways of silica by machine learning: implication for meteorite impacts. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/c881f6f4-3217-439e-8331-026bce99e9f7.v1
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Dataset
choose version: version 2 - 2024-03-08 (latest)
version 1 - 2024-01-10

We construct the potential energy surface of silica under various pressure conditions using machine learning potential and have refined three unique pressure windows, either kinetically or thermodynamically favored, to stabilize seifertite, which reached an agreement with observations in meteorites.

history
  • 2024-01-10 first online, published, posted
publisher
4TU.ResearchData
format
gzipped shape files
organizations
Center for High Pressure Science & Technology Advanced Research, Collaborative Research for Earth and Applied Materials (CREAM), Beijing, China

DATA

files (1)