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Journal ArticleDOI

Memristive devices for computing

TLDR
The performance requirements for computing with memristive devices are examined and how the outstanding challenges could be met are examined.
Abstract
Memristive devices are electrical resistance switches that can retain a state of internal resistance based on the history of applied voltage and current. These devices can store and process information, and offer several key performance characteristics that exceed conventional integrated circuit technology. An important class of memristive devices are two-terminal resistance switches based on ionic motion, which are built from a simple conductor/insulator/conductor thin-film stack. These devices were originally conceived in the late 1960s and recent progress has led to fast, low-energy, high-endurance devices that can be scaled down to less than 10 nm and stacked in three dimensions. However, the underlying device mechanisms remain unclear, which is a significant barrier to their widespread application. Here, we review recent progress in the development and understanding of memristive devices. We also examine the performance requirements for computing with memristive devices and detail how the outstanding challenges could be met.

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Citations
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Journal ArticleDOI

Training and operation of an integrated neuromorphic network based on metal-oxide memristors

TL;DR: The experimental implementation of transistor-free metal-oxide memristor crossbars, with device variability sufficiently low to allow operation of integrated neural networks, in a simple network: a single-layer perceptron (an algorithm for linear classification).
Journal ArticleDOI

Giant switchable photovoltaic effect in organometal trihalide perovskite devices

TL;DR: The demonstration of switchable OTP photovoltaics and electric-field-manipulated doping paves the way for innovative solar cell designs and for the exploitation of OTP materials in electrically and optically readable memristors and circuits.
Journal ArticleDOI

The future of electronics based on memristive systems

TL;DR: The state of the art in memristor-based electronics is evaluated and the future development of such devices in on-chip memory, biologically inspired computing and general-purpose in-memory computing is explored.
Journal ArticleDOI

In-memory computing with resistive switching devices

TL;DR: This Review Article examines the development of in-memory computing using resistive switching devices, where the two-terminal structure of the devices, theirresistive switching properties, and direct data processing in the memory can enable area- and energy-efficient computation.
Journal ArticleDOI

Recent progress in resistive random access memories: Materials, switching mechanisms, and performance

TL;DR: A comprehensive review of the recent progress in the so-called resistive random access memories (RRAMs) can be found in this article, where a brief introduction is presented to describe the construction and development of RRAMs, their potential for broad applications in the fields of nonvolatile memory, unconventional computing and logic devices, and the focus of research concerning RRAMS over the past decade.
References
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Journal ArticleDOI

The missing memristor found

TL;DR: It is shown, using a simple analytical example, that memristance arises naturally in nanoscale systems in which solid-state electronic and ionic transport are coupled under an external bias voltage.
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Memristor-The missing circuit element

TL;DR: In this article, the memristor is introduced as the fourth basic circuit element and an electromagnetic field interpretation of this relationship in terms of a quasi-static expansion of Maxwell's equations is presented.
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Nanoionics-based resistive switching memories

TL;DR: A coarse-grained classification into primarily thermal, electrical or ion-migration-induced switching mechanisms into metal-insulator-metal systems, and a brief look into molecular switching systems is taken.
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Nanoscale Memristor Device as Synapse in Neuromorphic Systems

TL;DR: A nanoscale silicon-based memristor device is experimentally demonstrated and it is shown that a hybrid system composed of complementary metal-oxide semiconductor neurons and Memristor synapses can support important synaptic functions such as spike timing dependent plasticity.
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