We introduce a machine-learning interatomic potential for tungsten using the Gaussian Approximation Potential framework. We specifically focus on properties relevant for simulations of radiationinduced collision cascades and the damage they produce, including a realistic repulsive potential for the short-range many-body cascade dynamics and a good description of the liquid phase. Furthermore, the potential accurately reproduces surface properties and the energetics of vacancy and self-interstitial clusters, which have been long-standing deficiencies of existing potentials. The potential enables molecular dynamics simulations of radiation damage in tungsten with unprecedented accuracy.

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Overlap of collision cascades with previously formed defect clusters become increasingly likely at radiation doses typical for materials in nuclear reactors. Using molecular dynamics, we systematically investigate the effects of different pre-existing self-interstitial clusters on the damage produced by an overlapping cascade in bcc iron and tungsten. We find that the number of new Frenkel pairs created in direct overlap with an interstitial cluster is reduced to essentially zero, when the size of the defect cluster is comparable to that of the disordered cascade volume. We develop an analytical model for this reduced defect production as a function of the spatial overlap between a cascade and a defect cluster of a given size. Furthermore, we discuss cascade-induced changes in the morphology of self-interstitial clusters, including transformations between 1/2 1 1 1 and 1 0 0 dislocation loops in iron and tungsten, and between C15 clusters and dislocation loops in iron. Our results provide crucial new cascade-overlap effects to be taken into account in multi-scale modelling of radiation damage in bcc metals.

We develop a set of machine-learning interatomic potentials for elemental V, Nb, Mo, Ta, and W using the Gaussian approximation potential framework. The potentials show good accuracy and transferability for elastic, thermal, liquid, defect, and surface properties. All potentials are augmented with accurate repulsive potentials, making them applicable to radiation damage simulations involving high-energy collisions. We study melting and liquid properties in detail and use the potentials to provide melting curves up to 400 GPa for all five elements.

We develop a silicon Gaussian approximation machine learning potential suitable for radiation effects, and use it for the first ab initio simulation of primary damage and evolution of collision cascades. The model reliability is confirmed by good reproduction of experimentally measured threshold displacement energies and sputtering yields. We find that clustering and recrystallization of radiation-induced defects, propagation pattern of cascades, and coordination defects in the heat spike phase show striking differences to the widely used analytical potentials. The results reveal that small defect clusters are predominant and show new defect structures such as a vacancy surrounded by three interstitials. IMPACT STATEMENT Quantum-mechanical level of accuracy in simulation of primary damage was achieved by a silicon machine learning potential. The results show quantitative and qualitative differences from the damage predicted by any previous models.

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The sputtering and reflection properties of wurtzite beryllium oxide (BeO) subjected to deuterium (D) ions bombardment at 300 K with ion energy between 10 eV and 200 eV is studied by classical molecular dynamics. Cumulative irradiations of wurtzite BeO show a D concentration threshold above which an 'unphysical dramatic' sputtering is observed. From the cumulative irradiations, simulation cells with different D concentrations are used to run non-cumulative irradiations at different concentrations. Using a D concentration close to the experimentally determined saturation concentration (0.12 atomic fraction), the simulations are able to reproduce accurately the experimental sputtering yield of BeO materials. The processes driving the sputtering of beryllium (Be) and oxygen (O) atoms as molecules are subsequently determined. At low irradiation energy, between 10 eV and 80 eV, swift chemical sputtering is dominant and produces mostly ODz molecules. At high energy, the sputtered molecules are mostly BexOy molecules (mainly BeO dimer). Four different processes are associated to the formation of such molecules: the physical sputtering of BeO dimer, the delayed swift chemical sputtering not involving D ions and the detachmentinduced sputtering. The physical sputtering of BeO dimer can be delayed if the sputtering event implies two interactions with the incoming ion (first interaction in its way in the material, the other in its way out if it is backscattered). The detachment-induced sputtering is a characteristic feature of the 'dramatic' sputtering and is mainly observed when the concentration of D is close to the threshold leading to this sputtering regime.