Field-effect transistors based on two-dimensional (2D) materials have the potential to be
used in very large-scale integration (VLSI) technology, but whether they can be used at the …

The unique electronic and catalytic properties emerging from low symmetry anisotropic (1D
and 2D) metal chalcogenides (MCs) have generated tremendous interest for use in next …

In-sensor processing, which can reduce the energy and hardware burden for many machine
vision applications, is currently lacking in state-of-the-art active pixel sensor (APS) …

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 …

Since the isolation of graphene in 2004, two-dimensional (2D) materials research has
rapidly evolved into an entire subdiscipline in the physical sciences with a wide range of …

Synapses are essential for the transmission of neural signals. Synaptic plasticity allows for
changes in synaptic strength, enabling the brain to learn from experience. With the rapid …

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

Continued reduction in transistor size can improve the performance of silicon integrated
circuits (ICs). However, as Moore's law approaches physical limits, high‐performance …

Abstract From Deep Blue to AlphaGo, artificial intelligence and machine learning are
booming, and neural networks have become the hot research direction. However, due to the …

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 …