17 citations · 35 across the 7 of their papers we have counts for
7 papers
Transformation-mediated twinning governs plasticity in body-centered cubic nanocrystals under extreme loading
Jan Očenášek, Jesper Byggmästar, Guanying Wei +2
Plasticity in body-centered cubic (BCC) nanocrystals is often associated with twin nucleation phenomena under extreme loading conditions. Here, we reveal unconventional twinning pa…
Effects of training machine-learning potentials for radiation damage simulations using different pseudopotentials
A. Fellman, J. Byggmästar, F. Granberg +2
Machine learning (ML) has become a commonplace approach in the development of interatomic potentials for molecular dynamics simulations, and its use also for radiation effect model…
Four regimes of primary radiation damage in tungsten
Jesper Byggmästar, Ville-Markus Yli-Suutala, Aslak Fellman +3
We observe for the first time in silico the transition to a linear regime in the primary damage production in tungsten. As the critical plasma-facing material in fusion reactors, r…
Design Kinetic Parameters for Improved Resilience of Materials under Irradiation
Mohammadhossein Nahavandian, Eda Aydogan, Jesper Byggmästar +3
High entropy alloys (HEAs) have captured much attention in recent years due to their conceivably improved radiation resistance compared to pure metals and traditional alloys. Howev…
Segregation, ordering, and precipitation in WTaV-based concentrated refractory alloys
Jesper Byggmästar, Damian Sobieraj, Jan S. Wróbel +4
Tungsten-based low-activation high-entropy alloys are possible candidates for next-generation fusion reactors due to their exceptional tolerance to irradiation, thermal loads, and…
Utilizing a machine-learned potential to explore enhanced radiation tolerance in the MoNbTaVW high-entropy alloy
Jiahui Liu, Jesper Byggmastar, Zheyong Fan +3
High-entropy alloys (HEAs) based on tungsten (W) have emerged as promising candidates for plasma-facing components in future fusion reactors, owing to their excellent irradiation r…
Computational study of crystal defects formation in Mo by machine learned molecular dynamics simulations
F. J. Dominguez-Gutierrez, J. Byggmästar, K. Nordlund +2
In this work, we study the damage in crystalline molybdenum material samples due to neutron bombardment in a primary knock-on atom range of 0.5-10 keV at room temperature. We perfo…