CMOS-based computing systems that employ the von Neumann architecture are relatively
limited when it comes to parallel data storage and processing. In contrast, the human brain …

Abstract Domain walls (DWs) in magnetic nanowires are promising candidates for a variety
of applications including Boolean/unconventional logic, memories, in-memory computing as …

The spatiotemporal nature of neuronal behavior in spiking neural networks (SNNs) makes
SNNs promising for edge applications that require high energy efficiency. To realize SNNs …

Nanomagnetic and spintronic devices, which make use of physical phenomena in materials
and interfaces like perpendicular magnetic anisotropy (PMA) and spin–orbit torque (SOT) to …

Spintronics and magnetic materials exhibit many physical phenomena that are promising for
implementing neuromorphic computing natively in hardware. Here, we review the current …

The membrane potential of an isolated biological neuron results from the concentration
difference between intracellular and extracellular ions. Any external disturbance and …

Analog neuromorphic computing systems emulate the parallelism and connectivity of the
human brain, promising greater expressivity and energy efficiency compared to those of …

Topological solitons are exciting candidates for the physical implementation of next-
generation computing systems. As these solitons are nanoscale and can be controlled with …

Advanced synaptic devices with simultaneous memory and processor capabilities are
envisaged as core elements of neuromorphic computing (NC) for low‐power artificial …

Current-induced multilevel magnetization switching in ferrimagnetic spintronic devices is
highly pursued for the application in neuromorphic computing. In this work, we demonstrate …