Spin–orbit torque (SOT) is an emerging technology that enables the efficient manipulation of
spintronic devices. The initial processes of interest in SOTs involved electric fields, spin …

Traditional von Neumann computing systems involve separate processing and memory
units. However, data movement is costly in terms of time and energy and this problem is …

Learning is highly important for edge intelligence devices to adapt to different application
scenes and owners. Current technologies for training neural networks require moving …

With the scaling of lateral dimensions in advanced transistors, an increased gate
capacitance is desirable both to retain the control of the gate electrode over the channel and …

Memristor-enabled neuromorphic computing systems provide a fast and energy-efficient
approach to training neural networks,,–. However, convolutional neural networks (CNNs) …

In this manuscript, recent progress in the area of resistive random access memory (RRAM)
technology which is considered one of the most standout emerging memory technologies …

Guided by brain-like 'spiking'computational frameworks, neuromorphic computing—brain-
inspired computing for machine intelligence—promises to realize artificial intelligence while …

Neuromorphic Computing, a concept pioneered in the late 1980s, is receiving a lot of
attention lately due to its promise of reducing the computational energy, latency, as well as …

Hafnium oxide (HfO2) is one of the mature high‐k dielectrics that has been standing strong
in the memory arena over the last two decades. Its dielectric properties have been …

The development of silicon semiconductor technology has produced breakthroughs in
electronics—from the microprocessor in the late 1960s to early 1970s, to automation …