Reversible optical switching memristors with tunable STDP synaptic plasticity: a route to hierarchical control in artificial intelligent systems

Jaafar, Ayoub H.; Gray, Robert; Verrelli, E.; O’Neill, Mary; Kelly, Stephen M.; Kemp, Neil T.

doi:10.1039/c7nr06138b

Cited by 72 publications

(77 citation statements)

References 26 publications

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“…[61] UV-vis 0.6 -√ --Au/In 2 O 3 /ZnO/FTO [14] UV 0.4-4 √ √ --W/MoS 2 /SiO 2 /p-Si [62] UV 0.11 √ √ --Au/TiO 2 /Au [63] Violet 0.5 -√ --ITO/MWCNTs/CdS [64] Blue --√ --Pt/HfO 2 /p-Si [65] Blue 0.01-5 -√ --ITO/Si-NC/Al [12] UV-NIR 18 √ √ --ITO/ZnO/Si-NCs/CBP/MoO 3 /Au [66] UV -√ √ --Al/ZnO/PDR1A/ITO [67] Green 180 -√ --ITO/ZnO 1−x /AlO y /Al [ [61] UV-vis 0.6 -√ --Au/In 2 O 3 /ZnO/FTO [14] UV 0.4-4 √ √ --W/MoS 2 /SiO 2 /p-Si [62] UV 0.11 √ √ --Au/TiO 2 /Au [63] Violet 0.5 -√ --ITO/MWCNTs/CdS [64] Blue --√ --Pt/HfO 2 /p-Si [65] Blue 0.01-5 -√ --ITO/Si-NC/Al [12] UV-NIR 18 √ √ --ITO/ZnO/Si-NCs/CBP/MoO 3 /Au [66] UV -√ √ --Al/ZnO/PDR1A/ITO [67] Green 180 -√ --ITO/ZnO 1−x /AlO y /Al [ …”

Section: Supporting Informationunclassified

An Artificial Optoelectronic Synapse Based on a Photoelectric Memcapacitor

Zhao

Fan

Cheng

et al. 2019

Adv Elect Materials

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away quickly when the light stimuli are removed. [3][4][5] In other words, traditional photodetectors can detect the images like a retina, but they lack the memory function owned by the visual cortex (see schematic illustration of human visual system in Figure 1a). To realize both detection and memory functions so as to better imitate the human visual system, researchers have attempted to integrate the photodetectors with the nonvolatile memory devices. [6][7][8][9] For example, a bioinspired visual system comprising an In 2 O 3 nanowire photodetector connected in series with an Al 2 O 3 memristor was fabricated recently, which could capture a butterflyshaped image and store it for more than 1 week. [9] In such integrated devices, however, the units responsible for detection, processing, and storage of optical information are physically separated, resulting in high power consumption for data transfer between different units (just as the Von Neumann bottleneck [10,11] ).A simple yet effective humanoid optoelectronic device emerging recently is the artificial optoelectronic synapse based on the photoelectric memristor, which can co-locate the detection and memory functions in a single unit. As the name suggests, a photoelectric memristor can continuously change its resistance upon light stimuli, resembling the physiological The rapid development of artificial intelligence technology has led to the urge for artificial optoelectronic synapses with visual perception and memory capabilities. A new type of artificial optoelectronic synapse, namely a photo electric memcapacitor, is proposed and demonstrated. This photoelectric memcapacitor, with a planar Au/La 1.875 Sr 0.125 NiO 4 /Au metal-semiconductormetal structure, displays a complementary optical and electrical modulation of capacitance, which can be attributed to the charge trapping/detrapping induced Schottky barrier variation. It further exhibits versatile synaptic functions, such as photonic potentiation/electric depression, pairedpulse facilitation, short/longterm memory, and "learningexperience" behavior. Moreover, the photoplasticity of the memcapacitor can be modulated by varying the frequency of applied AC voltage, thus enabling selfadaptive optical signal detection and mimicry of interestmodulated human visual memory. Therefore, it represents a new paradigm for artificial optoelectronic synapses and opens up opportunities for developing lowpower humanoid optoelectronic devices.

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Section: Supporting Informationunclassified

An Artificial Optoelectronic Synapse Based on a Photoelectric Memcapacitor

Zhao

Fan

Cheng

et al. 2019

Adv Elect Materials

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“…[152][153][154] Various optoelectronic synaptic devices based on different 2D layered materials and architectures have been proposed to emulate bio-synaptic features. Similarly, light stimulus can also be used as signal input to tune and control behaviors of the optoelectronic synaptic devices through modifying their electrical conductance.…”

Section: Optoelectronic Synaptic Devicesmentioning

confidence: 99%

2D Layered Materials for Memristive and Neuromorphic Applications

Wang

Meng

et al. 2019

Adv Elect Materials

102

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demonstrated that the memristive devices exhibit many promising features, [3][4][5][6][7][8] such as non-volatility, high speed switching, high endurance, high-density integration, CMOS-compatible fabrication, and so on. These features make them ideal candidates for applications in memory devices, [3,5,9] in-memory computing, [3,[10][11][12] and edge computing. [13,14] The working principle of the TMOs-based memristive devices relies on ion drift or diffusion, which resembles motion of ions in the biological neurons and synapses. The ionic motions exhibit dynamic behaviors. Thus, the memristive devices can be used to emulate the synaptic plasticity [15] and neurons. [16][17][18] Compared to traditional silicon synapses [19][20][21] and neurons [22,23] requiring complex circuits, such emerging memristive devices have compact structures and enhanced func-

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“…Artificial synapses triggered by combined optical and electrical stimulation have also been implemented based on InAs quantum dot‐doped GaAs/AlGaAs, azobenzene polymer/ZnO nanorod, and CH 3 NH 3 PbI 3 memristive devices …”

Section: Photoelectric Synapsesmentioning

confidence: 99%

Photonic Synapses for Ultrahigh‐Speed Neuromorphic Computing

Zhuge

Wang

Zhuge

2019

Physica Rapid Research Ltrs

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Neuromorphic computing based on a non‐von Neumann architecture is a promising way for the efficient implementation of artificial intelligence. A neuromorphic computing system is mainly composed of artificial synapses and neurons. Various electronic neuromorphic devices have been developed by different technologies. Neuromorphic photonics combines the efficiency of neural networks and the speed of photonics to build computing systems. Compared with their electronic counterparts, photonic neurons and synapses have the potential advantages of ultrafast operation speed, large bandwidth, and no electrical interconnect power loss, inherent to the computing by optical means. Therefore, photonic neuromorphic devices are attracting more and more attention. This work reviews the recent advances in the development of photonic synapses. Both purely photonic synapses and photoelectric synapses are described. Their structures and working mechanisms are discussed in detail.

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Reversible optical switching memristors with tunable STDP synaptic plasticity: a route to hierarchical control in artificial intelligent systems

Cited by 72 publications

References 26 publications

An Artificial Optoelectronic Synapse Based on a Photoelectric Memcapacitor

An Artificial Optoelectronic Synapse Based on a Photoelectric Memcapacitor

2D Layered Materials for Memristive and Neuromorphic Applications

Photonic Synapses for Ultrahigh‐Speed Neuromorphic Computing

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