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

Photonic computing and neuromorphic computing could address the inherent limitations of
traditional von Neumann architecture and gradually invalidate Moore's law. As photonics …

Neuromorphic computing (NC) is a new generation of artificial intelligence. Memristors are
promising candidates for NC owing to the feasibility of their ultrahigh‐density 3D integration …

Ferroelectrics have been demonstrated as excellent building blocks for high‐performance
nonvolatile memories, including memristors, which play critical roles in the hardware …

Neuromorphic computing systems that are capable of parallel information storage and
processing with high area and energy efficiencies, offer important opportunities for future …

Metal–organic framework (MOF) nanosheets have attracted significant interests for sensing,
electrochemical, and catalytic applications. Most significantly, 2D MOF with highly …

Biological nonassociative learning is one of the simplest forms of unsupervised learning in
animals and can be categorized into habituation and sensitization according to mechanism …

The von Neumann bottleneck and memory wall have posed fundamental limitations in
latency and energy consumption of modern computers based on von Neumann architecture …

The field of neuromorphic computing systems has been through enormous progress in
recent years, whereas some issues are still remaining to be solved. One of the biggest …

Inspired by biological neuromorphic systems, which can simultaneously perceive,
remember, and process enormous information through parallel, energy-efficient processes …