Insights into the primary radiation damage of silicon by a machine learning interatomic potential

A. Hamedani; J. Byggmästar; F. Djurabekova; G. Alahyarizadeh; R. Ghaderi; A. Minuchehr; K. Nordlund

doi:10.1080/21663831.2020.1771451

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Insights into the primary radiation damage of silicon by a machine learning interatomic potential

Original Reports | 更新时间：2026-08-19

- Insights into the primary radiation damage of silicon by a machine learning interatomic potential
- Insights into the primary radiation damage of silicon by a machine learning interatomic potential
- 材料研究快报（英文） 2020年8卷第10期页码：364-372
- 作者机构：
  
  1. a Department of Physics University of Helsinki
  2. a Department of Physics University of Helsinki Helsinki Finland
  3. c Helsinki Institute of Physics
  4. b Engineering Department Shahid Beheshti University
- 作者简介：
- 基金信息：
- DOI：10.1080/21663831.2020.1771451
  中图分类号：
- 网络首发：2020-06-01，
  
  纸质出版：2020
- 稿件说明：
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A. Hamedani, J. Byggmästar, F. Djurabekova, 等. Insights into the primary radiation damage of silicon by a machine learning interatomic potential[J]. 材料研究快报（英文）, 2020,8(10):364-372.

A. Hamedani, J. Byggmästar, F. Djurabekova, et al. Insights into the primary radiation damage of silicon by a machine learning interatomic potential[J]. Materials Research Letters, 2020, 8(10): 364-372.
A. Hamedani, J. Byggmästar, F. Djurabekova, 等. Insights into the primary radiation damage of silicon by a machine learning interatomic potential[J]. 材料研究快报（英文）, 2020,8(10):364-372. DOI： 10.1080/21663831.2020.1771451.

A. Hamedani, J. Byggmästar, F. Djurabekova, et al. Insights into the primary radiation damage of silicon by a machine learning interatomic potential[J]. Materials Research Letters, 2020, 8(10): 364-372. DOI： 10.1080/21663831.2020.1771451.

摘要

Abstract

BSTRACTWe develop a silicon Gaussian approximation machine learning potential suitable for radiation effects

and use it for the first

ab initio

simulation of primary damage and evolution of collision cascades. The model reliability is confirmed by good reproduction of experimentally measured threshold displacement energies and sputtering yields. We find that clustering and recrystallization of radiation-induced defects

propagation pattern of cascades

and coordination defects in the heat spike phase show striking differences to the widely used analytical potentials. The results reveal that small defect clusters are predominant and show new defect structures such as a vacancy surrounded by three interstitials.

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相关机构

a Department of Materials Engineering Indian Institute of Technology Gandhinagar

b Regional Institute of Education Manasagangothri University of Mysore

c Herbert Gleiter International Institute Liaoning Academy of Materials

d Department of Advanced Materials Science The University of Tokyo

a Explosives Research and Development Sandia National Laboratories Albuquerque

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