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

Masaki Mito, Narimichi Mokutani, Hiroki Tsuji, Yongpeng Tang, Kaname Matsumoto, Mitsuhiro Murayama, Zenji Horita

研究成果: ジャーナルへの寄稿学術誌査読

2 被引用数 (Scopus)

抄録

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 ∼55 and ∼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.

本文言語英語
論文番号105903
ジャーナルJournal of Applied Physics
131
10
DOI
出版ステータス出版済み - 3月 14 2022

!!!All Science Journal Classification (ASJC) codes

  • 物理学および天文学一般

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