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Resistive switching materials for information processing
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 …
processing paradigms, which, in turn, demand new circuit-building blocks to overcome the …
2D material based synaptic devices for neuromorphic computing
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 …
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
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 …
representing important building blocks in many scientific and technological fields due to their …
Nanoionic memristive phenomena in metal oxides: the valence change mechanism
This review addresses resistive switching devices operating according to the bipolar
valence change mechanism (VCM), which has become a major trend in electronic materials …
valence change mechanism (VCM), which has become a major trend in electronic materials …
Stimuli‐responsive memristive materials for artificial synapses and neuromorphic computing
Neuromorphic computing holds promise for building next‐generation intelligent systems in a
more energy‐efficient way than the conventional von Neumann computing architecture …
more energy‐efficient way than the conventional von Neumann computing architecture …
Nonvolatile memories based on graphene and related 2D materials
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 …
which need to be accessed very quickly. Nonvolatile memories (NVMs) are making inroads …
Nonvolatile memory materials for neuromorphic intelligent machines
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 …
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
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 …
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
The control and rational design of redox‐based memristive devices, which are highly
attractive candidates for next‐generation nonvolatile memory and logic applications, is …
attractive candidates for next‐generation nonvolatile memory and logic applications, is …
On‐demand reconfiguration of nanomaterials: when electronics meets ionics
Rapid advances in the semiconductor industry, driven largely by device scaling, are now
approaching fundamental physical limits and face severe power, performance, and cost …
approaching fundamental physical limits and face severe power, performance, and cost …