The booming development of artificial intelligence (AI) requires faster physical processing
units as well as more efficient algorithms. Recently, reservoir computing (RC) has emerged …

With the advent of the big data era and the Internet of Things, promising hardware
techniques for data storage and energy-efficient data processing are in great demand. This …

Memristors are essential components of neuromorphic systems that mimic the synaptic
plasticity observed in biological neurons. In this study, a novel approach employing one …

With the rapid application of artificial intelligence in daily life and work, the traditional von
Neumann architecture device faces the limitation of scalability and high energy …

Possessing the merits of high efficiency, low consumption, and versatility, emerging photonic
memristive and memristive‐like devices exhibit an attractive future in constructing novel …

The explosion in digital communication with the huge amount of data and the internet of
things (IoT) led to the increasing demand for data storage technology with faster operation …

The substantial amount of data generated every second in the big data age creates a
pressing requirement for new and advanced data storage techniques. Luminescent …

Due to the excessively high electrical conductivity and single dielectric properties of the
graphene material, when used as a wave absorbing material, the imbalance of impedance …

Memristors emulating biological synapses to perform memory and learning functions are
crucial for realizing bio-inspired neuromorphic systems. However, to meet the increasing …

Quantum dots (QDs) have garnered a significant amount of attention as promising
memristive materials owing to their size-dependent tunable bandgap, structural stability, and …