Memristors have recently attracted significant interest due to their applicability as promising
building blocks of neuromorphic computing and electronic systems. The dynamic …

Humanoid robots, intelligent machines resembling the human body in shape and functions,
cannot only replace humans to complete services and dangerous tasks but also deepen the …

Artificial synapses can boost neuromorphic computing to overcome the inherent limitations
of von Neumann architecture. As a promising memristor candidate, ferroelectric tunnel …

Next-generation non-volatile memories with ultrafast speed, low power consumption, and
high density are highly desired in the era of big data. Here, we report a high performance …

With the development of artificial intelligence, the demand for brain-like intelligent devices
capable of breaking the von Neumann bottleneck is growing. In light of the advantages of …

With the advent of the era of big data, resistive random access memory (RRAM) has become
one of the most promising nanoscale memristor devices (MDs) for storing huge amounts of …

Ferroelectric materials are promising candidates for synaptic weight elements in neural
network hardware because of their nonvolatile multilevel memory effect. This feature is …

Brain‐inspired neuromorphic computing is a new paradigm that holds great potential to
overcome the intrinsic energy and speed issues of traditional von Neumann based …

Neuromorphic computing consisting of artificial synapses and neural network algorithms
provides a promising approach for overcoming the inherent limitations of current computing …

Neuromorphic computing provides alternative hardware architectures with high
computational efficiencies and low energy consumption by simulating the working principles …