Electrical engineering

Physics

Neuromorphic engineering

Nanotechnology

Tunnel magnetoresistance

Ferromagnetism

Electronic circuit

Computer architecture

Engineering

Artificial intelligence

Spintronics

Materials science

Electronic engineering

Layer (electronics)

Computer science

Quantum mechanics

Artificial neural network

Nature Electronics

Neuromorphic computing uses brain-inspired principles to design circuits that can perform computational tasks with superior power efficiency to conventional computers. Approaches that use traditional electronic devices to create artificial neurons and synapses are, however, currently limited by the energy and area requirements of these components. Spintronic nanodevices, which exploit both the magnetic and electrical properties of electrons, can increase the energy efficiency and decrease the area of these circuits, and magnetic tunnel junctions are of particular interest as neuromorphic computing elements because they are compatible with standard integrated circuits and can support multiple functionalities. Here, we review the development of spintronic devices for neuromorphic computing. We examine how magnetic tunnel junctions can serve as synapses and neurons, and how magnetic textures, such as domain walls and skyrmions, can function as neurons. We also explore spintronics-based implementations of neuromorphic computing tasks, such as pattern recognition in an associative memory, and discuss the challenges that exist in scaling up these systems. This Review Article examines the development of spintronic devices for neuromorphic computing, exploring how magnetic tunnel junctions and magnetic textures can act as artificial neurons and synapses, as well as considering the challenges that exist in scaling up current systems.

Neuromorphic spintronics