Resistive memories are outstanding electron devices that have displayed a large potential in
a plethora of applications such as nonvolatile data storage, neuromorphic computing …

The conventional computing architecture faces substantial challenges, including high
latency and energy consumption between memory and processing units. In response, in …

In-memory computing (IMC) has emerged as a new computing paradigm able to alleviate or
suppress the memory bottleneck, which is the major concern for energy efficiency and …

Memristor crossbar with programmable conductance could overcome the energy
consumption and speed limitations of neural networks when executing core computing tasks …

The memristor is an excellent candidate for nonvolatile memory and neuromorphic
computing. Recently, two-dimensional (2D) materials have been developed for use in …

The quest to imbue machines with intelligence akin to that of humans, through the
development of adaptable neuromorphic devices and the creation of artificial neural …

In-memory computing technology built on 2D material-based nonvolatile resistive switches
(aka memristors) has made great progress in recent years. It has however been debated …

In the race of fabricating solid‐state nano/microelectronic devices using 2D layered
materials (LMs), achieving high yield and low device‐to‐device variability are the two main …

Brain-inspired computing enabled by memristors has gained prominence over the years due
to the nanoscale footprint and reduced complexity for implementing synapses and neurons …

Brain‐inspired neuromorphic computing has been developed as a potential candidate for
solving the von Neumann bottleneck of traditional computing systems. 2D materials‐based …