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 memristor, a composite word of memory and resistor, has become one of the most
important electronic components for brain‐inspired neuromorphic computing in recent years …

Neuromorphic computing takes inspiration from the brain to create energy-efficient hardware
for information processing, capable of highly sophisticated tasks. Systems built with standard …

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 …

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 …

Due to the voltage driven switching at low voltages combined with nonvolatility of the
achieved polarization state, ferroelectric materials have a unique potential for low power …

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

Ion migration as well as electron transfer and coupling in resistive switching materials
endow memristors with a physically tunable conductance to resemble synapses, neurons …

Artificial synapses can boost neuromorphic computing to overcome the inherent limitations
of von Neumann architecture. As a promising memristor candidate, ferroelectric tunnel …