Although the structure and function of the human brain are still far from being fully
understood, brain‐inspired computing architectures mainly consisting of artificial neurons …

Brain‐inspired neuromorphic computing is a new paradigm that holds great potential to
overcome the intrinsic energy and speed issues of traditional von Neumann based …

To implement artificial neural networks (ANNs) based on memristor devices, it is essential to
secure the linearity and symmetry in weight update characteristics of the memristor, and …

Memristors have attracted increasing attention due to their tremendous potential to
accelerate data-centric computing systems. The dynamic reconfiguration of memristive …

Doped‐HfO2 thin films with ferroelectricity have attracted great attention due to their
potential application in semiconductor industry as negative capacitance and resistance …

To apply resistive random‐access memory (RRAM) to the neuromorphic system and
improve performance, each cell in the array should be able to operate independently by …

Artificial synapse having good linearity is crucial to achieve an efficient learning process in
neuromorphic computing. It is found that the synaptic linearity can be enhanced by …

Bipolar redox-based resistive random-access memory cells are intensively studied for new
storage class memory and beyond von Neumann computing applications. However, the …

A self-rectifying ferroelectric tunnel junction that employs a HfO2/ZrO2/HfO2 superlattice
(HZH SL) combined with Al2O3 and TiO2 layers is proposed. The 6 nm-thick HZH SL …

In this study, by inserting a buffer layer of TiO x between the SiO x: Ag layer and the bottom
electrode, we have developed a memristor device with a simple structure of Ag/SiO x: Ag/TiO …