Primary damage and electronic effects in Si with machine learning-driven molecular dynamics - Atomic structure of final defects
Description
This dataset contains the atomic structure of survived defects, induced from self-irradiated silicon with different primary knock-on atom (PKA) energies. The molecular dynamics simulations were performed with the Gaussian approximation machine learning potential, GAP, using the TurboGAP code. In the simulations, a first-principles-derived model for the electronic stopping power was employed. More information about the simulation details is provided in the corresponding README file.
Show moreYear of publication
2025
Authors
Ali Hamedani - Creator, Publisher
Other information
Open access
Open
License
Creative Commons Attribution 4.0 International (CC BY 4.0)
Keywords
Molecular Dynamics, primary radiation damage, machine learning, electronic stopping, GAP potential, m, TurboGAP