About

Academy postdoctoral research fellow in computational materials physics at University of Helsinki, Department of Physics.

My main research interest is development of machine-learning and analytical interatomic potentials for molecular dynamics simulations. I also use them to simulate radiation damage in various materials. Current research topics:

• Machine-learning potentials for metals, alloys, and semiconductors.

• tabGAP: Tabulated Gaussian approximation potentials for high-entropy alloys.

• Plasticity of (high-entropy) alloys.

• Radiation damage in metals, alloys, and semiconductors.

Selected/highlighted publications

J. Byggmästar, K. Nordlund, and F. Djurabekova, Modelling refractory high-entropy alloys with machine-learned interatomic potentials: Defects and segregation, Physical Review B, 104, 104101 (2021), https://arxiv.org/abs/2106.03369, https://doi.org/10.1103/PhysRevB.104.104101

J. Byggmästar, K. Nordlund, and F. Djurabekova, Simple machine-learned interatomic potentials for complex alloys, Physical Review Materials, 6, 083801 (2022), https://arxiv.org/abs/2203.08458, https://doi.org/10.1103/PhysRevMaterials.6.083801

J. Byggmästar, A. Hamedani, K. Nordlund, and F. Djurabekova, Machine-learning interatomic potential for radiation damage and defects in tungsten, Physical Review B, 100, 144105 (2019), https://arxiv.org/abs/1908.07330, https://doi.org/10.1103/PhysRevB.100.144105

J. Byggmästar and F. Granberg, Dynamical stability of radiation-induced C15 clusters in iron, Journal of Nuclear Materials, 528, 151893 (2020) , https://arxiv.org/abs/1909.09818, https://doi.org/10.1016/j.jnucmat.2019.151893

Contact information

email: jesper.byggmastar(a)helsinki.fi