Nonvolatile memories are in strong demand due to the desire for miniaturization, high-speed
storage, and low energy consumption to fulfill the rapid developments of big data, the …

The interest in ferroelectric tunnel junctions (FTJ) has been revitalized by the discovery of
ferroelectricity in fluorite‐structured oxides such as HfO2 and ZrO2. In terms of thickness …

Data-intensive computing operations, such as training neural networks, are essential for
applications in artificial intelligence but are energy intensive. One solution is to develop …

Human brain outperforms the current von Neumann digital computer in many aspects, such
as energy efficiency and fault‐tolerance. Inspired by human brain, neuromorphic …

A continuous exponential rise has been observed in the storage and processing of the data
that may not curtail in the foreseeable future. The required data processing speed and …

A neuromorphic system is composed of hardware-based artificial neurons and synaptic
devices, designed to improve the efficiency of neural computations inspired by energy …

Analog storage through synaptic weights using conductance in resistive neuromorphic
systems and devices inevitably generates harmful heat dissipation. This thermal issue not …

The progress of artificial intelligence and the development of large‐scale neural networks
have significantly increased computational costs and energy consumption. To address these …

The von Neumann bottleneck and memory wall have posed fundamental limitations in
latency and energy consumption of modern computers based on von Neumann architecture …

Nonvolatile memory (NVM)‐based neuromorphic computing has been attracting
considerable attention from academia and the industry. Although it is not completely …