Resistive switching materials for information processing

Z Wang, H Wu, GW Burr, CS Hwang, KL Wang… - Nature Reviews …, 2020 - nature.com
The rapid increase in information in the big-data era calls for changes to information-
processing paradigms, which, in turn, demand new circuit-building blocks to overcome the …

A comprehensive review on emerging artificial neuromorphic devices

J Zhu, T Zhang, Y Yang, R Huang - Applied Physics Reviews, 2020 - pubs.aip.org
The rapid development of information technology has led to urgent requirements for high
efficiency and ultralow power consumption. In the past few decades, neuromorphic …

2022 roadmap on neuromorphic computing and engineering

DV Christensen, R Dittmann… - Neuromorphic …, 2022 - iopscience.iop.org
Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented …

Volatile and nonvolatile memristive devices for neuromorphic computing

G Zhou, Z Wang, B Sun, F Zhou, L Sun… - Advanced Electronic …, 2022 - Wiley Online Library
Ion migration as well as electron transfer and coupling in resistive switching materials
endow memristors with a physically tunable conductance to resemble synapses, neurons …

Electrochemical‐Memristor‐Based Artificial Neurons and Synapses—Fundamentals, Applications, and Challenges

S Chen, T Zhang, S Tappertzhofen, Y Yang… - Advanced …, 2023 - Wiley Online Library
Artificial neurons and synapses are considered essential for the progress of the future brain‐
inspired computing, based on beyond von Neumann architectures. Here, a discussion on …

Fully memristive neural networks for pattern classification with unsupervised learning

Z Wang, S Joshi, S Savel'Ev, W Song, R Midya, Y Li… - Nature …, 2018 - nature.com
Neuromorphic computers comprised of artificial neurons and synapses could provide a
more efficient approach to implementing neural network algorithms than traditional …

Ionic modulation and ionic coupling effects in MoS2 devices for neuromorphic computing

X Zhu, D Li, X Liang, WD Lu - Nature materials, 2019 - nature.com
Coupled ionic–electronic effects present intriguing opportunities for device and circuit
development. In particular, layered two-dimensional materials such as MoS2 offer highly …

An artificial spiking afferent nerve based on Mott memristors for neurorobotics

X Zhang, Y Zhuo, Q Luo, Z Wu, R Midya, Z Wang… - Nature …, 2020 - nature.com
Neuromorphic computing based on spikes offers great potential in highly efficient computing
paradigms. Recently, several hardware implementations of spiking neural networks based …

Artificial visual perception nervous system based on low-dimensional material photoelectric memristors

Y Pei, L Yan, Z Wu, J Lu, J Zhao, J Chen, Q Liu… - ACS nano, 2021 - ACS Publications
The visual perception system is the most important system for human learning since it
receives over 80% of the learning information from the outside world. With the exponential …

Echo state graph neural networks with analogue random resistive memory arrays

S Wang, Y Li, D Wang, W Zhang, X Chen… - Nature Machine …, 2023 - nature.com
Recent years have witnessed a surge of interest in learning representations of graph-
structured data, with applications from social networks to drug discovery. However, graph …