Spintronic Materials and Devices for Artificial Intelligence Applications

Area of Science:

• Spintronics and Materials Science
• Artificial Intelligence Hardware

Background:

• Spintronic devices utilize electron spin and charge for data storage and processing, offering benefits like non-volatility and high speed.
• These properties are crucial for meeting the increasing demands of artificial intelligence (AI) for energy-efficient computing.

Purpose of the Study:

• To review the fundamental principles of spintronics and its advantages for AI applications.
• To examine recent advancements in emerging spintronic materials and their role in AI technologies.
• To highlight key AI applications enabled by spintronics, including in-memory, neuromorphic, and probabilistic computing.

Main Methods:

• Review of fundamental spintronic principles and device architectures.
• Examination of recent advances in spintronic materials (antiferromagnets, 2D magnets, altermagnets, topological magnets).
• Analysis of spintronic applications in in-memory, neuromorphic, and probabilistic computing.

Main Results:

• Spintronics offers unique advantages for AI, including energy efficiency, speed, and scalability.
• Emerging materials like 2D magnets and topological materials are expanding spintronic capabilities.
• Spintronic devices are enabling in-memory, neuromorphic, and probabilistic computing paradigms.

Conclusions:

• Fundamental materials research is critical for advancing spintronics and AI.
• Spintronics holds significant potential for driving future AI technologies and systems.
• Continued development in spintronic materials and devices will accelerate AI innovation.