Ionic complexes between gold and C60 have been observed for the first time. Cations and anions of the type [Au(C60)2]+/– are shown to have particular stability. Calculations suggest that these ions adopt a C60–Au–C60 sandwich-like (dumbbell) structure, which is reminiscent of [XAuX]+/– ions previously observed for much smaller ligands. The [Au(C60)2]+/– ions can be regarded as Au(I) complexes, regardless of whether the net charge is positive or negative, but in both cases, the charge transfer between the Au and C60 is incomplete, most likely because of a covalent contribution to the Au–C60 binding. The C60–Au–C60 dumbbell structure represents a new architecture in fullerene chemistry that might be replicable in synthetic nanostructures.

Reactive self-sputtering from a Be surface is simulated using neural network trained forces with high accuracy. The key in machine learning from DFT calculations is a well-balanced and complete training set of energies and forces obtained by iterative refinement.

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Material erosion and fuel retention will limit the life and the performance of thermonuclear fusion reactors. In this work, sputtering, reflection and retention processes are atomistically modeled by simulating the non-cumulative sputtering by deuterium projectiles on a beryllium–tungsten alloy surface. The forces for the molecular dynamics trajectories were machine learned from density functional theory with a neural network architecture. Our data confirms and supplements previous results for simulated sputtering rates. In the non-cumulative scenario we simulate, we did not observe reaction mechanisms leading to swift chemical sputtering. Thus, our sputtering rates at low impact energies are smaller than in comparable non-cumulative studies. The sputtering yields of the Be2W alloy are generally lower than those of pure beryllium. We found a strong dependence of the sputtering yield on the incident angle with an increase by about a factor of 3 for larger incident angles at 100 eV impact energy. In the pristine surface, a large majority of the impacting hydrogen projectiles at perpendicular impact remains in the surface.

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Sputtering from plasma-facing surfaces upon particle impact can limit the lifetime of components in fusion devices, especially in the diverter region. Atomistic simulations of the processes associated with plasma–wall interactions allow for a detailed analysis of sputtering, reflection and adsorption. Most former works of beryllium sputtering by hydrogen isotopes were aimed mostly on the sputtering yield. We investigate the influence of impact energy and angle on sputtering, and analyze these quantities also for the outgoing particle. We model the sputtering by non-cumulative molecular dynamics simulations with a large number of trajectories for the various parameters. The underlying forces and energies are obtained from high-dimensional neural networks fitted to density functional calculations. We find a good agreement with the previously reported sputtering yields for perpendicular impact and a qualitative accordance with experimental data. In detail, the sputtering yield increases with increasing impact energy for angles of incidence larger than 45° with respect to the surface normal, while smaller angles show a maximal yield up to 100 eV. In cases where D reflection rather than sputtering occurs, a similar pattern is found for all angles, with the maximal reflection rate at 80°.

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