2010
DOI: 10.1002/adma.200903680
|View full text |Cite
|
Sign up to set email alerts
|

Learning Abilities Achieved by a Single Solid‐State Atomic Switch

Abstract: Learning abilities are demonstrated using a single solid‐state atomic switch, wherein the formation and dissolution of a metal filament are controlled depending on the history of prior switching events. The strength of the memorization level gradually increases when the number of input signals is increased. Once the filament forms a bridge, electrons flow in a ballistic mode and long‐term memorization is achieved (see figure).

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3

Citation Types

4
251
1
1

Year Published

2011
2011
2023
2023

Publication Types

Select...
5
3

Relationship

0
8

Authors

Journals

citations
Cited by 296 publications
(257 citation statements)
references
References 24 publications
4
251
1
1
Order By: Relevance
“…Moreover, memristors can function as stateful Boolean logic gates via the material implication operation [15]. In addition, memristors can also be used for neuromorphic computing [16,17] because of their analog switching, and some hybrid circuits due to their ease of stacking [18,19].…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Moreover, memristors can function as stateful Boolean logic gates via the material implication operation [15]. In addition, memristors can also be used for neuromorphic computing [16,17] because of their analog switching, and some hybrid circuits due to their ease of stacking [18,19].…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, memristors can function as stateful Boolean logic gates via the material implication operation [15]. In addition, memristors can also be used for neuromorphic computing [16,17] because of their analog switching, and some hybrid circuits due to their ease of stacking [18,19].Among all the kinds of switching materials that have been reported, oxides are the most extensively studied [4]. The interfaces between the metal electrodes and the oxide play a crucial role, especially for bipolar switches [5,6,20].…”
mentioning
confidence: 99%
“…29,30 In addition, multilevel memory states will enable more delicate mimicking of short-term and long-term memories in the human neuromorphic system. 27,28 …”
Section: Introductionmentioning
confidence: 99%
“…The working principle of this memory effect is highly similar to that of a neuromorphic system in the human neural network. 27,28 Therefore, ionic devices have attracted renewed interest to mimic the neuromorphic systems and to develop neuromorphic devices, so-called neuristors.…”
Section: Introductionmentioning
confidence: 99%
“…6,7 Memristive systems, as theoretically defined by Leon Chua in 1970s, 8,9 are expected to achieve the learning abilities and neuromophic computing where the synaptic function is required. 6,[10][11][12][13] The first memristor found by Strukov et al in 2008 works in the way that the interface barrier is modulated by the evolution of these thermally-reduced titanium oxides. 6,7 It is also demonstrated lately that the diffusion of "adhesion layer" Ti metal atoms through the contact Pt electrode controls the memristive switching, as these diffused Ti atoms lead to the local thermally-derived TiO x .…”
mentioning
confidence: 99%