Results 271 to 280 of about 1,933,006 (329)

Nanoionics-based resistive switching memories.

Nature Materials, 2007
Many metal-insulator-metal systems show electrically induced resistive switching effects and have therefore been proposed as the basis for future non-volatile memories. They combine the advantages of Flash and DRAM (dynamic random access memories) while avoiding their drawbacks, and they might be highly scalable.
R. Waser, M. Aono
semanticscholar   +3 more sources

Bipolar Resistive Switching in TiO2 Artificial Synapse Mimicking Pavlov's Associative Learning.

ACS Applied Materials and Interfaces, 2023
Memristive devices are among the most emerging electronic elements to realize artificial synapses for neuromorphic computing (NC) applications and have potential to replace the traditional von-Neumann computing architecture in recent times. In this work,
A. K. Jena   +6 more
semanticscholar   +1 more source

Hafnium Oxide (HfO2 ) - A Multifunctional Oxide: A Review on the Prospect and Challenges of Hafnium Oxide in Resistive Switching and Ferroelectric Memories.

Small, 2022
Hafnium oxide (HfO2 ) is one of the mature high-k dielectrics that has been standing strong in the memory arena over the last two decades. Its dielectric properties have been researched rigorously for the development of flash memory devices.
W. Banerjee, Alireza Kashir, S. Kamba
semanticscholar   +1 more source

A Review of Resistive Switching Devices: Performance Improvement, Characterization, and Applications

Small Structures, 2021
As human society enters the big data era, huge data storage and energy‐efficient data processing are in great demand. The resistive switching device is an emerging device with both inherent memory and computation capabilities.
Tuo Shi   +5 more
semanticscholar   +1 more source

In-memory Learning with Analog Resistive Switching Memory: A Review and Perspective

Proceedings of the IEEE, 2021
In this article, we review the existing analog resistive switching memory (RSM) devices and their hardware technologies for in-memory learning, as well as their challenges and prospects.
Yue Xi   +8 more
semanticscholar   +1 more source

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