Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring

Abstract More than a century after the discovery of superconductors (SCs), numerous studies have been accomplished to take advantage SCs in physics, power engineering, quantum computing, electronics, communications, aviation, healthcare, and defence-related applications. However, there are still challenges that hinder full-scale commercialization SCs, such as high cost superconducting wires/tapes, technical issues related AC losses, structure devices, complexity cooling systems, critical temperature, manufacturing-related issues. In current century, massive advancements achieved artificial intelligence (AI) techniques by offering disruptive solutions handle engineering problems. Consequently, AI can be implemented tackle those facing superconductivity act shortcut towards full their approaches capable providing fast, efficient, accurate for technical, manufacturing, economic problems with level nonlinearity field superconductivity. this paper, concept widely used algorithms first given. Then topical review is presented conducted methods improvement, design, condition monitoring, fault detection location apparatuses large-scale applications, well prediction temperature new any other This three main categories: materials, physics SCs. addition, applying its applications Finally, future trends on how integrate discussed.