Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …

The rapid development of artificial intelligence (AI) demands the rapid development of
domain-specific hardware specifically designed for AI applications. Neuro-inspired …

Synaptic devices, including synaptic memristor and synaptic transistor, are emerging
nanoelectronic devices, which are expected to subvert traditional data storage and …

Flexible neuromorphic electronics that emulate biological neuronal systems constitute a
promising candidate for next‐generation wearable computing, soft robotics, and …

A spiking neural network (SNN) inspired by the structure and principles of the human brain
can significantly enhance the energy efficiency of artificial intelligence computing by …

Convolutional neural networks (CNNs) have gained much attention because they can
provide superior complex image recognition through convolution operations. Convolution …

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

Deep learning has become ubiquitous, touching daily lives across the globe. Today,
traditional computer architectures are stressed to their limits in efficiently executing the …

Neuromorphic photonics system based on the principle of biological brain is emerging as
one of the potential solutions to the bottleneck inherent in classical von Neumann computing …

Ferroelectric tunnel junctions (FTJ) based on hafnium zirconium oxide (Hf1–x Zr x O2; HZO)
are a promising candidate for future applications, such as low-power memories and …