Ion beam analysis of fusion plasma-facing materials and components : facilities and research challenges

Following the IAEA Technical Meeting on ‘Advanced Methodologies for the Analysis of Materials in Energy Applications Using Ion Beam Accelerators’, this paper reviews the current status of ion beam analysis (IBA) techniques and some aspects of ion-induced radiation damage in materials for the field of materials relevant to fusion. Available facilities, apparatus development, future research options and challenges are presented and discussed. The analysis of beryllium and radioactivity-containing samples from future experiments in JET or ITER represents not only an analytical but also a technical challenge. A comprehensive list of the facilities, their current status, and analytical capabilities comes alongside detailed descriptions of the labs. A discussion of future issues of sample handling and the current status of facilities at JET complete the technical section. To prepare the international IBA community for these challenges, the IAEA technical meeting concludes the necessity for determining new nuclear reaction cross-sections and improving the inter-laboratory comparability by defining international standards and testing these via a round-robin test.Peer reviewe

Disruption prediction with artificial intelligence techniques in tokamak plasmas

In nuclear fusion reactors, plasmas are heated to very high temperatures of more than 100 million kelvin and, in so-called tokamaks, they are confined by magnetic fields in the shape of a torus. Light nuclei, such as deuterium and tritium, undergo a fusion reaction that releases energy, making fusion a promising option for a sustainable and clean energy source. Tokamak plasmas, however, are prone to disruptions as a result of a sudden collapse of the system terminating the fusion reactions. As disruptions lead to an abrupt loss of confinement, they can cause irreversible damage to present-day fusion devices and are expected to have a more devastating effect in future devices. Disruptions expected in the next-generation tokamak, ITER, for example, could cause electromagnetic forces larger than the weight of an Airbus A380. Furthermore, the thermal loads in such an event could exceed the melting threshold of the most resistant state-of-the-art materials by more than an order of magnitude. To prevent disruptions or at least mitigate their detrimental effects, empirical models obtained with artificial intelligence methods, of which an overview is given here, are commonly employed to predict their occurrence—and ideally give enough time to introduce counteracting measures