人工知能アプリケーションのためのスピントロニクス材料とデバイス

The core of spintronic technologies lies in the use of electrons' intrinsic spin states, along with their electric charge, for information storage and processing. Spin-based manipulation of electronic devices inherently enables exceptional properties, such as infinite endurance, high-speed operation, scalability, and non-volatility. These attributes make spintronic devices highly suitable for addressing the growing demands of artificial intelligence (AI) for energy-efficient, scalable computing hardware across diverse applications. This review begins by introducing the fundamental principles of spintronics, emphasizing its unique advantages for AI applications, and providing an overview of spintronic device architectures. We then examine recent advances in emerging spintronic materials, including antiferromagnets, 2D magnets, altermagnets, and topological magnetic materials. The diverse spintronic materials and structures contribute to the realization of various cutting-edge AI technologies. We will highlight in-memory computing, which minimizes energy for data transfer; neuromorphic computing, which emulates the architecture and functionality of the human brain; and probabilistic computing, which harnesses stochastic spintronic behaviors for hardware-efficient computation. Finally, we conclude the review by highlighting the challenges and the critical role of fundamental materials research in unlocking the full potential of spintronics, which contributes to driving AI technologies and systems forward.