Memristors are considered promising energy-efficient artificial intelligence hardware, which
can eliminate the von Neumann bottleneck by parallel in-memory computing. The common …

Nonvolatile resistive switching, also known as the memristor effect, has emerged as an
important concept in the development of neuromorphic computing. Memristive operation …

Neuromorphic electronics attract significant attention as a new computing architecture.
Despite much effort for achieving practical neuromorphic systems, it is still challenging to …

Vanadium dioxide (VO 2) is a representative metal–insulator-transition (MIT) material that
undergoes a reversible phase transition at 68° C, which is close to room temperature. This …

An in-depth simulation and experimental study has been performed to analyze thermal
effects on the variability of resistive memories. Kinetic Monte Carlo (kMC) simulations, that …

In the present study, various statistical and machine learning (ML) techniques were used to
understand how device fabrication parameters affect the performance of copper oxide …

Approaching the application of redox‐based resistive switching random access memory
(ReRAM), the research focus shifts more and more toward different aspects of reliability …

With rapid advancement and deep integration of artificial intelligence and the internet-of-
things, artificial intelligence of things has emerged as a promising technology changing …

HfO2-based resistive random-access memory (RRAM) with a Ti buffer layer has been
extensively studied as an emerging nonvolatile memory (eNVM) candidate because of its …

Neuromorphic networks adopt human brain mechanisms and create a promising way to
solve various artificial cognitive problems. Memristors, novel circuit design elements, could …