The cointegration of artificial neuronal and synaptic devices with homotypic materials and
structures can greatly simplify the fabrication of neuromorphic hardware. We demonstrate …

Future‐generation neuromorphic computing seeks to overcome the limitations of von
Neumann architectures by colocating logic and memory functions, thereby emulating the …

Neuromorphic computing has shown remarkable capabilities in silicon-based artificial
intelligence, which can be optimized by using Mott materials for functional synaptic …

In neuromorphic hardware, peripheral circuits and memories based on heterogeneous
devices are generally physically separated. Thus, exploration of homogeneous devices for …

Designing transparent flexible electronics with multi‐biological neuronal functions and
superior flexibility is a key step to establish wearable artificial intelligence equipment. Here …

Neuromorphic networks that consist of electronic synapses are very important for energy-
efficient artificial intelligent applications. Therefore, in recent years, many efforts have been …

Electronic synaptic devices are important building blocks for neuromorphic computational
systems that can go beyond the constraints of von Neumann architecture. Although two …

The recent surge of interest in brain-inspired computing and power-efficient electronics has
dramatically bolstered development of computation and communication using neuron-like …

Memristive devices based on two-dimensional (2D) semiconducting materials have
emerged as highly promising neuromorphic devices due to their intrinsic atomic body and …

The slowing pace of performance improvements in modern processors along with the
breakdown of power scaling forecasts an imminent end to the traditional transistor scaling …