Achieving superconductivity with higher Tc in lightweight Al-Ti-Mg alloys: Prediction using machine learning and synthesis via high-pressure torsion process

Aluminum (Al) and titanium (Ti) are superconducting materials but their superconducting transition temperatures (T-c) are quite low as 1.20 and 0.39 K, respectively, while magnesium (Mg) never exhibits superconductivity. In this study, we explored new superconductors with higher T-c in the Al-Mg-Ti ternary system, along with the prediction using machine learning. High-pressure torsion (HPT) is utilized to produce the superconducting states. While performing AC magnetization measurements, we found, for the first time, superconducting states with T-c = 4.0 and 7.3 K for a composition of Al:Ti = 1:2. The magnetic anomalies appeared more sharply when the sample was processed by HPT at 573 K than at room temperature, and the anomalies exhibited DC magnetic field dependence characteristic of superconductivity. Magnetic anomalies also appeared at similar to 55 and similar to 93 K, being supported by the prediction using the machine learning for the Al-Ti-O system, and this suggests that Al-Ti oxides play an important role in the advent of such anomalies but that the addition of Mg could be less effective. Published under an exclusive license by AIP Publishing.

Automated summary

In this study, the researchers explored new superconductors with higher transition temperatures (Tc) in the Al-Mg-Ti ternary system. They utilized high-pressure torsion (HPT) to produce superconducting states and discovered superconductivity with Tc of 4.0 and 7.3 K. Machine learning predictions supported the appearance of magnetic anomalies at around 55 K and 93 K, indicating the importance of Al-Ti oxides in the manifestation of these anomalies, with the addition of Mg being less effective.