A. Hamedani

Machine-learning interatomic potential for radiation damage and defects in tungsten

Jesper Byggmästar, A. Hamedani, K. Nordlund et al. · Physical review. B./Physical review. B · 2019 · 141 citations · Full text

Materials Science, Crystal Structure, Ion Implantation +14

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

A. Hamedani, Jesper Byggmästar, Flyura Djurabekova et al. · Materials Research Letters · 2020 · 30 citations · Full text

Artificial Intelligence, Engineering, Machine Learning +23

Mechanical properties of carbon nanotube- and graphene-reinforced Araldite LY/Aradur HY 5052 resin epoxy composites: a molecular dynamics study

S. Faragi, A. Hamedani, Gh. Alahyarizadeh et al. · Journal of Molecular Modeling · 2019 · 27 citations

Materials Science, Fiber Reinforcement, Engineering +7

Performance analysis of the perovskite solar cells by a realistic, DFT-accurate optical absorption spectrum

J. Laali, A. Hamedani, Gh. Alahyarizadeh et al. · Superlattices and Microstructures · 2020 · 25 citations

Engineering, Perovskite Solar Cell, Physics +11

The role of chromium and nickel on the thermal and mechanical properties of FeNiCr austenitic stainless steels under high pressure and temperature: a molecular dynamics study

A. Hasanzadeh, A. Hamedani, Ghasem Alahyarizadeh et al. · Molecular Simulation · 2019 · 14 citations

Magnetic Properties, Engineering, Mechanical Engineering +17