This review concentrates on the specific properties and characteristics of damage structures generated with high-energy ions in the electronic energy loss regime. Irradiation experiments with so-called swift heavy ions (SHI) find applications in many different fields, with examples presented in ion-track nanotechnology, radiation hardness analysis of functional materials, and laboratory tests of cosmic radiation. The basics of the SHI-solid interaction are described with special attention to processes in the electronic subsystem. The broad spectrum of damage phenomena is exemplified for various materials and material classes, along with a description of typical characterization techniques. The review also presents state-of-the-art modeling efforts that try to account for the complexity of the coupled processes of the electronic and atomic subsystems. Finally, the relevance of SHI phenomena for effects induced by fission fragments in nuclear fuels and how this knowledge can be applied to better estimate damage risks in nuclear materials is discussed.

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Developing data-driven machine-learning interatomic potentials for materials containing many elements becomes increasingly challenging due to the vast configuration space that must be sampled by the training data. We study the learning rates and achievable accuracy of machine-learning interatomic potentials for many-element alloys with different combinations of descriptors for the local atomic environments. We show that for a five-element alloy system, potentials using simple low-dimensional descriptors can reach meV/atom-accuracy with modestly sized training datasets, significantly outperforming the high-dimensional SOAP descriptor in data efficiency, accuracy, and speed. In particular, we develop a computationally fast machine-learned and tabulated Gaussian approximation potential (tabGAP) for Mo-Nb-Ta-V-W alloys with a combination of two-body, three-body, and a new simple scalar many-body density descriptor based on the embedded atom method.

The widespread adoption of gGaN in radiation‐hard semiconductor devices relies on a comprehensive understanding of its response to strongly ionizing radiation. Despite being widely acclaimed for its high radiation resistance, the exact effects induced by ionization are still hard to predict due to the complex phase‐transition diagrams and defect creation‐annihilation dynamics associated with group‐III nitrides. Here, the Two‐Temperature Model, Molecular Dynamics simulations and Transmission Electron Microscopy, are employed to study the interaction of Swift Heavy Ions with GaN at the atomic level. The simulations reveal a high propensity of GaN to recrystallize the region melted by the impinging ion leading to high thresholds for permanent track formation. Although the effect exists in all studied electronic energy loss regimes, its efficiency is reduced with increasing electronic energy loss, in particular when there is dissociation of the material and subsequent formation of N2 bubbles. The recrystallization is also hampered near the surface where voids and pits are prominent. The exceptional agreement between the simulated and experimental results establishes the applicability of the model to examine the entire electronic energy loss spectrum. Furthermore, the model supports an empirical relation between the interaction cross sections (namely for melting and amorphization) and the electronic energy loss.

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