A grand family of two-dimensional (2D) materials and their heterostructures have been
discovered through the extensive experimental and theoretical efforts of chemists, material …

Efforts to design devices emulating complex cognitive abilities and response processes of
biological systems have long been a coveted goal. Recent advancements in flexible …

Traditional von Neumann computing systems involve separate processing and memory
units. However, data movement is costly in terms of time and energy and this problem is …

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

Memristive and nanoionic devices have recently emerged as leading candidates for
neuromorphic computing architectures. While top-down fabrication based on conventional …

As the research on artificial intelligence booms, there is broad interest in brain‐inspired
computing using novel neuromorphic devices. The potential of various emerging materials …

Modern computers are based on the von Neumann architecture in which computation and
storage are physically separated: data are fetched from the memory unit, shuttled to the …

Simulating biological synaptic functionalities through artificial synaptic devices opens up an
innovative way to overcome the von Neumann bottleneck at the device level. Artificial …

Memristors are two-terminal passive circuit elements that have been developed for use in
non-volatile resistive random-access memory and may also be useful in neuromorphic …

Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL)
techniques, which rely on networks of connected simple computing units operating in …