Achieving high-T_c superconductivity in Magneli phase based on Ti oxides: prediction by machine learning and material synthesis by high-pressure torsion processing

We explored superconductors with high superconducting transition temperatures (T-c) tuning the stability of Magneli phase through high-pressure torsion (HPT). This study has started from exploring superconducting states in the Al-Mg-O ternary system along with the prediction using machine learning. We successfully found superconducting states with T-c = 4.0 and 7.3 K for a composition of Al:Ti = 1:2 in the mixture of Al and surface-oxidized Ti powders. Another magnetic anomaly was also observed at similar to 93 K, being supported by the T-c prediction using the machine learning for the Al-Ti-O system. In this study, the HPT processing was also performed on a Magneli material Ti4O7 and such mixtures of stable materials as Al + TiO2, Al2O3 + Ti, Al2O3 + TiO2, and Al + Ti4O7. In HPT-processed Ti4O7, the metal-insulator transition was maintained even after the HPT processing. HPT experiments using stable oxides indicate the difficulty of newly stabilizing the Magneli phase starting from thermodynamically stable materials under severe plastic deformation. A series of attempts reveals that the superconducting state in the mixture with ratio Al:Ti = 1:2 is attributed to both strained Ti-oxide created on the surface of the Ti powder and its reaction with Al under HPT processing, resulting in the stabilization of a Magneli phase. [GRAPHICS] .