A light-stimulated synaptic transistor with synaptic plasticity and memory functions based on InGaZnOx–Al2O3 thin film structure

Li, Hua Kai; Chen, T. P.; Liu, P.; Hu, Shaoxiang; Liu, Y.; Zhang, Qing; Lee, Pooi See

doi:10.1063/1.4955042

Cited by 169 publications

(122 citation statements)

References 29 publications

(26 reference statements)

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“…It should be noted that PPF ( y ) dependence with pulse interval reported here also depicts a similar two‐phase behavior defined by the equation:

y = A_{1} \times \exp (- \frac{x}{t_{1}}) + A_{2} \times \exp (- \frac{x}{t_{2}}) + y_{0}

where x is pulse interval time, y 0 is resting facilitation magnitude, A 1 (88%) and A 2 (26%) are facilitation magnitudes of the rapid and slow phases, respectively, and t 1 (7 ms) and t 2 (198 ms) are characteristic relaxation times of respective phases. Values inside the parenthesis indicate the best fit values in our case and are comparable to those of a biological synapse …”

Section: Resultssupporting

confidence: 71%

“…Besides, STM can be converted to LTM through repeated rehearsals or repetitive learning, which physically changes the structure of neurons. This time‐dependent stabilization, whereby our experiences achieve a permanent record in our memory, is referred to as “consolidation.” For the synaptic transistor reported here, such temporal characteristics of memory retention were realized by repeated gate pulse activation, which is analogous to repetitive learning in human brain . To study this transition, a series of presynaptic spikes with fixed intensity, width, and interval (3 V, 502 ms, and 7.25 ms, respectively) were applied with V ds = 1 V. Postsynaptic current was recorded immediately after the last pulse of the spike train.…”

Section: Resultsmentioning

confidence: 99%

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Flexible Ionic‐Electronic Hybrid Oxide Synaptic TFTs with Programmable Dynamic Plasticity for Brain‐Inspired Neuromorphic Computing

John

Kulkarni

et al. 2017

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158

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Emulation of biological synapses is necessary for future brain-inspired neuromorphic computational systems that could look beyond the standard von Neuman architecture. Here, artificial synapses based on ionic-electronic hybrid oxide-based transistors on rigid and flexible substrates are demonstrated. The flexible transistors reported here depict a high field-effect mobility of ≈9 cm V s with good mechanical performance. Comprehensive learning abilities/synaptic rules like paired-pulse facilitation, excitatory and inhibitory postsynaptic currents, spike-time-dependent plasticity, consolidation, superlinear amplification, and dynamic logic are successfully established depicting concurrent processing and memory functionalities with spatiotemporal correlation. The results present a fully solution processable approach to fabricate artificial synapses for next-generation transparent neural circuits.

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“…It should be noted that PPF ( y ) dependence with pulse interval reported here also depicts a similar two‐phase behavior defined by the equation:

y = A_{1} \times \exp (- \frac{x}{t_{1}}) + A_{2} \times \exp (- \frac{x}{t_{2}}) + y_{0}

Section: Resultssupporting

confidence: 71%

Section: Resultsmentioning

confidence: 99%

Flexible Ionic‐Electronic Hybrid Oxide Synaptic TFTs with Programmable Dynamic Plasticity for Brain‐Inspired Neuromorphic Computing

John

Kulkarni

et al. 2017

Small

158

140

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“…Compared with the previous report, the field effect mobility of the IZO synaptic thin-film transistor gated by MC solid electrolyte is higher 262728…”

Section: Resultscontrasting

confidence: 55%

Excitatory Post-Synaptic Potential Mimicked in Indium-Zinc-Oxide Synaptic Transistors Gated by Methyl Cellulose Solid Electrolyte

Wen

Ding

Wan

et al. 2016

Sci Rep

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The excitatory postsynaptic potential (EPSP) of biological synapses is mimicked in indium-zinc-oxide synaptic transistors gated by methyl cellulose solid electrolyte. These synaptic transistors show excellent electrical performance at an operating voltage of 0.8 V, Ion/off ratio of 2.5 × 106, and mobility of 38.4 cm2/Vs. After this device is connected to a resistance of 4 MΩ in series, it exhibits excellent characteristics as an inverter. A threshold potential of 0.3 V is achieved by changing the gate pulse amplitude, width, or number, which is analogous to biological EPSP.

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“…These photonic synapses are highly promising for the implementation of optic‐neural networks; however, a neuromorphic system based on photonic synapses is expected to be extremely inefficient and expensive because it would require a large number of wavelength conversions and sophisticated laser systems . Very recently, a light‐stimulated synaptic function was demonstrated in metal oxide transistors with persistent photoconductivity (PPC) characteristic . Owing to the metastable nature of the oxygen vacancies of metal oxides, which governs the PPC characteristic, it was difficult to achieve deterministic control of synaptic weight and reliable operation of these synaptic devices.…”

Section: Introductionmentioning

confidence: 99%

Optoelectronic Synapse Based on IGZO‐Alkylated Graphene Oxide Hybrid Structure

Sun

Choi

et al. 2018

Adv Funct Materials

312

275

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Recently, research interest in brain-inspired neuromorphic computing based on robust and intelligent artificial neural networks has surged owing to the ability of such technology to facilitate massive parallel, low-power, highly adaptive, and event-driven computing. Here, a photosynaptic device with a novel weight updating mechanism for high-speed and low-power optoelectronic spike processing is proposed, wherein a synaptic weight is controlled by a mixed spike consisting of voltage and light spikes; the light spike, in particular, boosts up the probability of electron detrapping from graphene oxide charge-trapping layer to the photosensitive indium-gallium-zinc oxide charge-transporting layer. Compared to electrically operating synaptic device, the magnitude of conductance change in the proposed photosynaptic device increases remarkably from 2.32 to 5.95 nS without degradation of the nonlinearity (potentiation/depression values are changed from 4.24/8 to 5/8). Owing to this enhancement of synaptic operation, the recognition rates for the Modified National Institute of Standards and Technology digit patterns improve from 36% and 49% to 50% and 62% in artificial neural networks using long-term potentiation/depression characteristics with 20 and 100 weight states, respectively. The proposed photosynaptic device technology capable of optoelectronic spike processing is expected to play a crucial role in the implementation of neuromorphic computing in the future.

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A light-stimulated synaptic transistor with synaptic plasticity and memory functions based on InGaZnOx–Al2O3 thin film structure

Abstract: A light-stimulated synaptic transistor with synaptic plasticity and memory functions based on InGaZnOx-Al2O3 thin film structure

Cited by 169 publications

References 29 publications

Flexible Ionic‐Electronic Hybrid Oxide Synaptic TFTs with Programmable Dynamic Plasticity for Brain‐Inspired Neuromorphic Computing

Flexible Ionic‐Electronic Hybrid Oxide Synaptic TFTs with Programmable Dynamic Plasticity for Brain‐Inspired Neuromorphic Computing

Excitatory Post-Synaptic Potential Mimicked in Indium-Zinc-Oxide Synaptic Transistors Gated by Methyl Cellulose Solid Electrolyte

Optoelectronic Synapse Based on IGZO‐Alkylated Graphene Oxide Hybrid Structure

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