With the booming growth of artificial intelligence (AI), the traditional von Neumann
computing architecture based on complementary metal oxide semiconductor devices are …

Ion migration as well as electron transfer and coupling in resistive switching materials
endow memristors with a physically tunable conductance to resemble synapses, neurons …

In-sensor and near-sensor computing are becoming the next-generation computing
paradigm for high-density and low-power sensory processing. To fulfil a high-density and …

Memristors have recently become powerful competitors toward artificial synapses and
neuromorphic computation, arising from their structural and electrical similarity to biological …

The unique electron spin, transfer, polarization and magnetoelectric coupling characteristics
of ABO3 multiferroic perovskite materials make them promising candidates for application in …

In the era of big data and artificial intelligence (AI), advanced data storage and processing
technologies are in urgent demand. The innovative neuromorphic algorithm and hardware …

Carbon dots (CDs) are widely utilized in sensing, energy storage, and catalysis due to their
excellent optical, electrical and semiconducting properties. However, attempts to optimize …

Photonic in-memory computing exhibits promising potential to address the inherent
limitations of traditional von Neumann architecture. In this study, we demonstrate a tantalum …

Neuromorphic computing can process large amounts of information in parallel and provides
a powerful tool to solve the von Neumann bottleneck. Constructing an artificial neural …

As a kind of photodetector, position-sensitive-detectors (PSDs) have been widely used in
noncontact photoelectric positioning and measurement. However, fabrications and …