105 citations · 341 across the 16 of their papers we have counts for
16 papers · 1 filter
Surface-mediated reduction of ion-irradiation-induced damage in tungsten revealed by advanced ion channeling analysis
Xin Jin, Fredric Granberg, Kai Nordlund +3
Tungsten is a leading candidate material for plasma-facing components in future fusion reactors. In this work, we integrate advanced ion channeling analysis with large-scale molecu…
A General-Purpose and Efficient Machine-Learned Potential for SiC from Ambient to Extreme Environments
Jintong Wu, Zhuang Shao, Junlei Zhao +5
Silicon carbide (SiC) polymorphs are widely employed as nuclear materials, mechanical components, and wide-bandgap semiconductors. The rapid advancement of SiC-based applications h…
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…
Radiation damage and phase stability of AlCrCuFeNi alloys using a machine-learned interatomic potential
Aslak Fellman, Jesper Byggmästar, Fredric Granberg +2
We develop a machine-learned interatomic potential for AlCrCuFeNi high-entropy alloys (HEA) using a diverse set of structures from density functional theory calculated including ma…
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…
High-dose long-time defect evolution in tungsten studied by atomistically informed Object Kinetic Monte Carlo simulations
Jintong Wu, Juan-Pablo Balbuena, Zhiwei Hu +4
Irradiation of materials in nuclear test reactors and power plants is known to alter the properties of the material. The irradiation event happening at pico- or nanosecond time sca…
Fast and accurate machine-learned interatomic potentials for large-scale simulations of Cu, Al and Ni
Aslak Fellman, Jesper Byggmästar, Fredric Granberg +2
Machine learning (ML) has become widely used in the development of interatomic potentials for molecular dynamics simulations. However, most ML potentials are still much slower than…
Atomistic Study of Irradiation-Induced Plastic and Lattice Strain in Tungsten
Jintong Wu, Daniel R. Mason, Fredric Granberg
We demonstrate a practical way to perform decomposition of the elasto-plastic deformation directly from atomistic simulation snapshots. Through molecular dynamics simulations on a…
An empirical potential for simulating hydrogen isotope retention in highly irradiated tungsten
Daniel R. Mason, Duc Nguyen-Manh, Victor W. Lindblad +2
We describe the parameterization of a tungsten-hydrogen empirical potential designed for use with large-scale molecular dynamics simulations of highly irradiated tungsten containin…
Multiscale machine-learning interatomic potentials for ferromagnetic and liquid iron
Jesper Byggmästar, Giorgos Nikoulis, Aslak Fellman +3
We develop and compare four interatomic potentials for iron: a simple machine-learned embedded atom method (EAM) potential, a potential with machine-learned two- and three-body-dep…
Revealing hidden defects through stored energy measurements of radiation damage
Charles A. Hirst, Fredric Granberg, Boopathy Kombaiah +6
With full knowledge of a material's atomistic structure, it is possible to predict any macroscopic property of interest. In practice, this is hindered by limitations of the chosen…
Parameter-free quantitative simulation of high dose microstructure and hydrogen retention in ion-irradiated tungsten
Daniel R. Mason, Fredric Granberg, Max Boleininger +3
Hydrogen isotopes are retained in materials for fusion power applications, changing both hydrogen embrittlement and tritium inventory as the microstructure undergoes irradiation da…
An estimate for thermal diffusivity in highly irradiated tungsten using Molecular Dynamics simulation
Daniel R Mason, Abdallah Reza, Fredric Granberg +1
The changing thermal conductivity of an irradiated material is among the principal design considerations for any nuclear reactor, but at present few models are capable of predictin…
Dynamical stability of radiation-induced C15 clusters in iron
Jesper Byggmästar, Fredric Granberg
Density functional theory predicts clusters in the form of the C15 Laves phase to be the most stable cluster of self-interstitials in iron at small sizes. The C15 clusters can form…
Local segregation versus irradiation effects in high-entropy alloys: Steady-state conditions in a driven system
Leonie Koch, Fredric Granberg, Tobias Brink +4
We study order transitions and defect formation in a model high-entropy alloy (CuNiCoFe) under ion irradiation by means of molecular dynamics simulations. Using a hybrid Monte-Carl…
Multi-scale modeling of dislocation-precipitate interactions in Fe: from molecular dynamics to discrete dislocations
Arttu Lehtinen, Fredric Granberg, Lasse Laurson +2
The stress-driven motion of dislocations in crystalline solids, and thus the ensuing plastic deformation process, is greatly influenced by the presence or absence of various point-…