Neuromorphic visual artificial synapse in-memory computing systems based on GeOx-coated MXene nanosheets

Caa, Yixin; Zhao, Tianshi; Liu, Chenguang; Zhao, Chun; Gao, Hao; Huang, Shichen; Li, Xianyao; Wang, Chengbo; Liu, Yina; Lim, Eng Gee; Wen, Zhen

doi:10.1016/j.nanoen.2023.108441

Cited by 11 publications

(3 citation statements)

References 62 publications

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“…Oversampling leads to data redundancy, and undersampling leads to data loss. 11 There have been many reports on optoelectronic synapses achieving dynamic target detection, 12–14 but they did not further consider the application scenario of synapses. Under extreme conditions, the ability of optoelectronic synapses to process signals may not be sufficient to complete the task of detecting motion targets.…”

Section: Introductionmentioning

confidence: 99%

MXene-based optoelectronic synaptic transistors utilize attentional mechanisms to achieve hierarchical responses

Qin,

Ren,

Fan

et al. 2024

J. Mater. Chem. C

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Section: Introductionmentioning

confidence: 99%

MXene-based optoelectronic synaptic transistors utilize attentional mechanisms to achieve hierarchical responses

Qin,

Ren,

Fan

et al. 2024

J. Mater. Chem. C

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“…To date, optoelectronic devices have successfully replicated important functions of biological synapses, including excitatory postsynaptic current (EPSC)/inhibitory postsynaptic current (IPSC), short-term plasticity (STP)/long-term plasticity (LTP), and so on. – However, many of the reported artificial synapses are based on fragile inorganic materials, which generally require complex and expensive preparation methods and are unlikely to work well for large-scale and flexible optoelectronic synaptic devices. – , On the other hand, the quick development of wearable electronics puts a strong demand on flexible computing systems. Thus, great efforts have been made to explore flexible organic materials for synaptic devices. – Until now, a variety of organic materials have been successfully utilized for the fabrication of optoelectronic synapses, such as chitosan, chlorophyll, copper(II) phthalocyanine (CuPc), , pentacene, poly(3-hexylthiophene) (P3HT), , and poly(3,4-ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS). , However, in most cases, these devices were constructed on rigid substrates, failing to fully exploit the flexible nature of these organic materials. ,– …”

Section: Introductionmentioning

confidence: 99%

“…21−26 However, many of the reported artificial synapses are based on fragile inorganic materials, which generally require complex and expensive preparation methods and are unlikely to work well for large-scale and flexible optoelectronic synaptic devices. [21][22][23][24][25]27 On the other hand, the quick development of wearable electronics puts a strong demand on flexible computing systems. Thus, great efforts have been made to explore flexible organic materials for synaptic devices.…”

Section: Introductionmentioning

confidence: 99%

Multifunctional Two-Terminal Optoelectronic Synapse Based on an Organic Semiconductor Film

Zhao,

Peng,

Cui

et al. 2023

ACS Appl. Polym. Mater.

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Organic materials show great potential in the fields of biomimetics and neuromorphic computing due to their molecular diversity, cost-effective manufacturing processes, unique optical and chemical properties, and remarkable mechanical flexibility. In this work, an optoelectronic synaptic device based on the organic semiconductor poly [2,5-(2-octyldodecyl)-3,6-diketopyrrolopyrrole-alt-5,5-(2,5-di(thien-2-yl))thieno [3,2b]thiophene] (DPPDTT) is fabricated by a simple solution process. The fabricated device successfully emulates typical functions of biological synapses, including excitatory postsynaptic current, pair-pulse facilitation, the conversion of short-term memory to long-term memory, and "learning experience" behavior by modulating light stimuli. Furthermore, the light logic functions of "AND" and "OR" are realized by using light pulses with different wavelengths, as well as the simulation of associative learning. Moreover, a flexible device was fabricated on a PET substrate, which not only exhibits good synaptic performance but also demonstrates excellent bending stability. Eventually, through the simulation based on a convolutional neural network algorithm, our device successfully realizes the high-precision recognition of handwritten digital even after bending 1000 times. This work showcases a promising methodology for developing brain-inspired flexible optoelectronic synapses for future neural computing networks based on organic materials.

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Tailoring Neuroplasticity in a Ferroelectric‐Gated Multi‐Terminal Synaptic Transistor by Bi‐Directional Modulation for Improved Pattern Edge Recognition

Li,

Liu,

Sun

et al. 2023

Adv Funct Materials

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The dynamic modulation of the plasticity of artificial neuromorphic devices facilitates a wide range of neuromorphic functions. However, integrating diverse plasticity modulation techniques into a single device presents a challenge due to limitations in the device structure design. Here, a multiterminal artificial synaptic device capable of bi‐directional modulation on its plasticity is proposed. Significantly, the conversion of inhibitory and excitatory synaptic plasticity can be achieved not only by modifying the polarity of the presynaptic voltage spike but also by exchanging its input terminal between top and bottom gate while maintaining the same presynaptic stimuli. This unique bi‐directional modulation of synaptic plasticity has been attributed to two distinct physical mechanisms: nonvolatile ferroelectric polarization and interface charge trap‐induced memory characteristics. Additionally, the effective dynamic modulation of the synaptic behaviors is quantified under different back‐gate bias and verified in the constructed neural network perceptron. Further, a visual simulation demonstrates the enhanced clarity and precision of edge recognition through the back‐gate modulation in the artificial synapses. This study provides a strategy to fulfill diversified modulation on synaptic plasticity in ferroelectric‐gated transistors, thereby prompting efficient and controllable neuromorphic visual systems.

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Neuromorphic visual artificial synapse in-memory computing systems based on GeOx-coated MXene nanosheets

Cited by 11 publications

References 62 publications

MXene-based optoelectronic synaptic transistors utilize attentional mechanisms to achieve hierarchical responses

MXene-based optoelectronic synaptic transistors utilize attentional mechanisms to achieve hierarchical responses

Multifunctional Two-Terminal Optoelectronic Synapse Based on an Organic Semiconductor Film

Tailoring Neuroplasticity in a Ferroelectric‐Gated Multi‐Terminal Synaptic Transistor by Bi‐Directional Modulation for Improved Pattern Edge Recognition

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