A review of rare earth materials for emerging memory devices for neuromorphic computing

Abstract

Neuromorphic computing represents a transformative approach to emulating human brain functionality, paving the way for advanced data processing and efficient learning systems. Two-terminal memory devices are central to this approach, as they replicate synaptic behavior essential for brain-like computational efficiency. This review focuses on the emerging role of rare earth materials in developing memory devices tailored for neuromorphic applications. The superior electrical, thermal, and optical properties of rare earths are compared to conventional materials, highlighting their potential to enhance performance metrics such as switching speed, retention time, endurance, energy efficiency, and synaptic plasticity. Key architectures and working principles of neuromorphic devices are discussed, emphasizing the unique attributes and motivations for integrating rare earth elements into memory systems. Furthermore, critical challenges, including scalability, cost, and material integration, are addressed to provide a comprehensive perspective. By exploring the intersection of advanced material science, device architecture, and neuromorphic computing, this review aims to guide future research efforts toward developing efficient, scalable memory devices for next-generation neuromorphic computing systems.