The advent of compact fusion reactors designs holds the promise of swift and affordable fusion energy [1,2]. The key technology that enables such reactors is high temperature superconductors (HTS)-based magnets, which produce extremely high magnetic fields and therefore can confine the plasma in smaller volumes. However, the compactness of these devices comes at a price: the magnet will be subject to neutron irradiation, introducing structural defects and degrade its superconducting properties[3,4]. Therefore, a full assessment of the radiation hardness of this fundamental component is needed. Computational methods can provide important insights in the microscopic mechanisms underlying the degradation process, therefore suggesting strategies to prolong the lifetime of HTS magnets.
In this presentation I will show our efforts in modelling the collision cascades started by impact of neutrons on primary knock-on atoms (PKAs) and their evolution on short timescales in YBa2Cu3O7 (YBCO) with molecular dynamics (MD) simulations [5]. Based on Monte Carlo neutronics calculations, we obtained energy spectra of PKAs for specific reactor’s or experimental design, and we investigated with MD the collision cascades at several representative energies and PKA species employing an interatomic potential developed for radiation damage modeling [6]. Results are analyzed in terms of generated number of defects, defect morphologies, and temperature transients. As a step forward, we expanded the investigation of collision cascades in the energy-PKA element landscape including also electronic stopping power, providing the base for integration of damage from MD and binary collision approximation simulations for specific reactor’s designs. Preliminary results regarding the development of a machine learning interatomic potential for collision cascade simulations for YBCO and its sub-phases will also be shown.
[1] B. N. Sorbom et al., Fusion Engineering and Design 100, 378 (2015)
[2] A. Kuang, et al., Fusion Engineering and Design 137, 221 (2018)
[3] D. X. Fischer, et al., Superconductor Science and Technology 31, 044006 (2018)
[4] W. Iliffe, et al., Superconductor Science and Technology 34, 09LT01 (2021).
[5] D. Torsello, D. Gambino et al., Superconductor Science and Technology 36, 014003 (2023).
[6] R. L. Gray, M. J. D. Rushton and S. T. Murphy, Superconductor Science and Technology 35, 035010 (2022).
DG acknowledges financial support from the Swedish Research Council (VR) through Grant No. 2023-00208. This work is partially supported by COST action CA19108, by the Italian Ministry of Foreign Affairs and International Cooperation, grant n PGR01173, by Eni S.p.A.. DT carried it out within the Ministerial Decree 1062/2021, with funding from the FSE REACT-EU - PON Ricerca e Innovazione 2014-2020.
Keywords: HTS radiation damage, Fusion technology, Molecular Dynamics, Machine learning interatomic potentials