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 increase in information in the big-data era calls for changes to information-
processing paradigms, which, in turn, demand new circuit-building blocks to overcome the …

Silicon photonics is evolving from laboratory research to real-world applications with the
potential to transform many technologies, including optical neural networks and quantum …

Reproducing ion channel–based neural functions with artificial fluidic systems has long
been an aspirational goal for both neuromorphic computing and biomedical applications. In …

Memristive devices are electrical resistance switches that can retain a state of internal
resistance based on the history of applied voltage and current. These devices can store and …

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

The global demand for data storage and processing has increased exponentially in recent
decades. To respond to this demand, research efforts have been devoted to the …

Artificial neuromorphic devices can emulate dendric integration, axonal parallel
transmission, along with superior energy efficiency in facilitating efficient information …

A diverse spectrum of technology drivers such as improved thermal barriers, higher
efficiency thermoelectric energy conversion, phase-change memory, heat-assisted magnetic …

Artificial neuromorphic systems based on populations of spiking neurons are an
indispensable tool in understanding the human brain and in constructing neuromimetic …