collaborators

5 papers

cond-mat.mtrl-sci2026

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…

cond-mat.mtrl-sci2026

An Accurate 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…

cond-mat.supr-con2025

Beyond dpa: an atomistic framework for a quantitative description of radiation damage in YBa2Cu3O7

Federico Ledda, Daniele Torsello, Davide Gambino +8

Radiation damage in high-temperature cuprate superconductors represents one of the main technological challenges for their deployment in harsh environments, such as fusion reactors…

cond-mat.mtrl-sci2025

Spontaneous damage annealing reactions as a possible source of low energy excess in semiconductor detectors

Kai Nordlund, Fanhao Kong, Flyura Djurabekova +4

In semiconductor detectors designed for capturing dark matter particles or neutrinos, when the detection threshold is constantly improved to increasingly low energies, an "excess"…

cond-mat.mtrl-sci2025

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…