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 …

2D material based synaptic devices for neuromorphic computing

G Cao, P Meng, J Chen, H Liu, R Bian… - Advanced Functional …, 2021‏ - Wiley Online Library
The demand for computing power has been increasing exponentially since the emergence
of artificial intelligence (AI), internet of things (IoT), and machine learning (ML), where novel …

[HTML][HTML] Oxygen vacancies: The (in) visible friend of oxide electronics

F Gunkel, DV Christensen, YZ Chen, N Pryds - Applied physics letters, 2020‏ - pubs.aip.org
Oxygen vacancies play crucial roles in determining the physical properties of metal oxides,
representing important building blocks in many scientific and technological fields due to their …

Nanoionic memristive phenomena in metal oxides: the valence change mechanism

R Dittmann, S Menzel, R Waser - Advances in Physics, 2021‏ - Taylor & Francis
This review addresses resistive switching devices operating according to the bipolar
valence change mechanism (VCM), which has become a major trend in electronic materials …

Stimuli‐responsive memristive materials for artificial synapses and neuromorphic computing

H Bian, YY Goh, Y Liu, H Ling, L **e… - Advanced Materials, 2021‏ - Wiley Online Library
Neuromorphic computing holds promise for building next‐generation intelligent systems in a
more energy‐efficient way than the conventional von Neumann computing architecture …

Nonvolatile memories based on graphene and related 2D materials

S Bertolazzi, P Bondavalli, S Roche, T San… - Advanced …, 2019‏ - Wiley Online Library
The pervasiveness of information technologies is generating an impressive amount of data,
which need to be accessed very quickly. Nonvolatile memories (NVMs) are making inroads …

Nonvolatile memory materials for neuromorphic intelligent machines

DS Jeong, CS Hwang - Advanced Materials, 2018‏ - Wiley Online Library
Recent progress in deep learning extends the capability of artificial intelligence to various
practical tasks, making the deep neural network (DNN) an extremely versatile hypothesis …

Single neuromorphic memristor closely emulates multiple synaptic mechanisms for energy efficient neural networks

C Weilenmann, AN Ziogas, T Zellweger… - Nature …, 2024‏ - nature.com
Biological neural networks do not only include long-term memory and weight multiplication
capabilities, as commonly assumed in artificial neural networks, but also more complex …

Anomalous resistance hysteresis in oxide ReRAM: oxygen evolution and reincorporation revealed by in situ TEM

D Cooper, C Baeumer, N Bernier… - Advanced …, 2017‏ - Wiley Online Library
The control and rational design of redox‐based memristive devices, which are highly
attractive candidates for next‐generation nonvolatile memory and logic applications, is …

On‐demand reconfiguration of nanomaterials: when electronics meets ionics

J Lee, WD Lu - Advanced Materials, 2018‏ - Wiley Online Library
Rapid advances in the semiconductor industry, driven largely by device scaling, are now
approaching fundamental physical limits and face severe power, performance, and cost …