Functional Materials for Neuromorphic Computing: Superconducting Solution
The development of artificial intelligence increasingly depends on the emergence of novel functional materials capable of performing computation, memory storage, and adaptive information processing beyond the limitations of conventional CMOS technologies. While considerable progress has been achieved through advances in computing architectures and learning algorithms, the future development of intelligent hardware increasingly depends on the discovery and engineering of novel functional materials capable of integrating computation, memory, and adaptive behavior within the same physical platform. This article presents a materials-oriented perspective on the evolution of neuromorphic computing, tracing the development from conventional insulating and semiconductor materials to hybrid superconducting spintronic systems. Particular attention is devoted to magnetic Josephson junctions and superconducting spintronic nanostructures as multifunctional quantum materials combining ultrafast dynamics, programmable magnetic states, intrinsic nonlinearity, and ultralow energy dissipation.