Ferroelectric materials, the charge equivalent of magnets, have been the subject of
continued research interest since their discovery more than 100 years ago. The …

The performance of conventional computer based on von Neumann architecture is limited
due to the physical separation of memory and processor. By synergistically integrating …

Reconfigurable field-effect transistors (FETs) combine unipolar n-and p-type characteristics
in a single programmable device and could be used to reduce the complexity of electronic …

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 …

In‐sensor computing with visual information, which can integrate photo‐sensing, data
storage, and computation functions within the same physical element, has promised a …

The neuromorphic system is an attractive platform for next-generation computing with low
power and fast speed to emulate knowledge-based learning. Here, we design ferroelectric …

General‐purpose computers usually use logic gate computing units based on
complementary metal oxide semiconductors (CMOS). Due to the separate memory and …

In-memory computing is a highly efficient approach for breaking the bottleneck of von
Neumann architectures, ie, reducing redundant latency and energy consumption during the …

Combining logical function and memory characteristics of transistors is an ideal strategy for
enhancing computational efficiency of transistor devices. Here, we rationally design a tri …

Increasing the demand for object motion detection (OMD) requires shifts of reducing
redundancy, heightened power efficiency, and precise programming capabilities to ensure …