6 papers
Machine-learned interatomic potential for sputtering of tungsten-boron surfaces
Alexandre Bergero, Jesper Byggmästar, Fredric Granberg
Boronization, where boron is deposited onto tungsten surfaces, is a key technique to reduce plasma contamination, such as oxygen in Tokamak fusion reactors. The exact interaction b…
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…
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…
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…
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…
Ultrahigh Stability of O-Sublattice in -GaO
Ru He, Junlei Zhao, Jesper Byggmästar +2
Recently reported remarkably high radiation tolerance of /-GaO double-polymorphic structure brings this ultrawide bandgap semiconductor to the frontiers of power el…