In this work, electronic synaptic plasticity and analog bipolar switching behavior by using a
Pt/TiO x/AlO x/AlTaON/TaN multilayer resistive random-access memory (RRAM) device were …

Memristors emulating biological synapses to perform memory and learning functions are
crucial for realizing bio-inspired neuromorphic systems. However, to meet the increasing …

Memristors have been emerging as promising candidates for computing systems in post‐
Moore applications, particularly electrochemical metallization‐based memristors, which are …

High density memory storage capacity, in-memory computation and neuromorphic
computing utilizing memristors are expected to solve the limitation of von-Neumann …

The emergence of the big data era has led to enormous demand for memory devices that
are low cost, flexible, fabrication friendly, transparent, energy efficient, and have a higher …

Two-dimensional (2D) layered dielectrics have recently emerged as the attractive building
blocks for the next-generation resistive random-access memory (RRAM). The ability to tailor …

Neuromorphic computing is a potential approach for imitating massive parallel processing
capabilities of a bio‐synapse. To date, memristors have emerged as the most appropriate …

The fabrication of nanoscale electronic synapses is an essential step towards the
development of neuromorphic devices having a high integration density. Excellent learning …

The alteration in microstructure, induced by ion migration due to applied voltage, constitutes
a pivotal factor influencing the performance of the memristor. This phenomenon adversely …

Two-terminal memristors are recognized as potential ingredients to build electronic
synapses for in in-memory computing applications with high density integration. However …