Machine learning... Machine learning applied to X-ray tomography as a new tool to analyse the voids in RRP Nb3Sn wires 19-05-2021 Scientists have developed a new tool to investigate the internal features of Nb3Sn superconducting wires, combining X-ray tomographic data acquired at beamline ID19 with an unsupervised machine-learning algorithm. The method provides new insights for enhancing wire performance. Share Interest in niobium-tin (Nb 3Sn) as a material for superconducting wires has recently been renewed because this material has been selected to replace niobium-titanium as the next step in accelerator magnet technology [1]. The design of these magnets relies on the availability of advanced Nb