The rapid development of information technology has led to urgent requirements for high
efficiency and ultralow power consumption. In the past few decades, neuromorphic …

Abstract Two-dimensional (2D) nanomaterials are an emerging class of biomaterials with
remarkable potential for biomedical applications. The planar topography of these …

Neuromorphic computing could address the inherent limitations of conventional silicon
technology in dedicated machine learning applications. Recent work on silicon-based …

Neuromorphic computing can potentially solve the von Neumann bottleneck of current
mainstream computing because it excels at self‐adaptive learning and highly parallel …

Develo** a single-phase self-rectifying memristor with the continuously tunable feature is
structurally desirable and functionally adaptive to dynamic environmental stimuli variations …

As human society enters the big data era, huge data storage and energy‐efficient data
processing are in great demand. The resistive switching device is an emerging device with …

Neuromorphic computing simulates the operation of biological brain function for information
processing and can potentially solve the bottleneck of the von Neumann architecture. This …

The rapid development of artificial intelligence techniques and future advanced robot
systems sparks emergent demand on the accurate perception and understanding of the …

Facing the exponential growth of data digital communications and the advent of artificial
intelligence, there is an urgent need for information technologies with huge storage capacity …

Animals execute intelligent and efficient interactions with their surroundings through neural
pathways, exhibiting learning, memory, and cognition. Artificial autonomous devices that …