Memristive devices can offer dynamic behaviour, analogue programmability, and scaling
and integration capabilities. As a result, they are of potential use in the development of …

New computing technologies inspired by the brain promise fundamentally different ways to
process information with extreme energy efficiency and the ability to handle the avalanche of …

Motion processing has proven to be a computational challenge and demands considerable
computational resources. Contrast this with the fact that flying insects can agilely perceive …

Neuromorphic computing memristors are attractive to construct low-power-consumption
electronic textiles due to the intrinsic interwoven architecture and promising applications in …

Reservoir computing offers a powerful neuromorphic computing architecture for
spatiotemporal signal processing. To boost the power efficiency of the hardware …

Reservoir computing is a highly efficient network for processing temporal signals due to its
low training cost compared to standard recurrent neural networks, and generating rich …

Atom‐economic catalysts open a new era of computationally driven atomistic design of
catalysts. Rationally manipulating the structures of the catalyst with atomic‐level precision …

As human society enters the big data era, huge data storage and energy‐efficient data
processing are in great demand. The resistive switching device is an emerging device with …

The emergence of memristors with potential applications in data storage and artificial
intelligence has attracted wide attentions. Memristors are assembled in crossbar arrays with …

Memristors, promising nanoelectronic devices with in-memory resistive switching behavior
that is assembled with a physically integrated core processing unit (CPU) and memory unit …