Biopolymer based artificial synapses enable linear conductance tuning and low-power for neuromorphic computing

Zhang, Ke; Xue, Qi; Zhou, Chao; Mo, Wanneng; Chen, Chun‐Chao; Li, Ming; Hang, Tao

doi:10.1039/d2nr01996e

Cited by 7 publications

(3 citation statements)

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“…Thus, the LTP/LTD characteristics of the device showed good linear conductance updates. When highly integrated devices operate for a long time, dense Ag cluster-type CFs, as compared with dendritic CFs, can weaken the Joule heating effect of the device itself. ,, Moreover, the uniformly distributed Ag clusters disperse the control weight and the influence of each Ag cluster on the device performance. Thus, the dissolution of partial Ag clusters caused by thermal coupling between devices will not have a major impact on the device performance.…”

Section: Results and Discussionmentioning

confidence: 99%

Three-Dimensional Integrated Synaptic Devices Based on a Silver-Cluster Conduction Mechanism with High Thermostability

Li,

et al. 2024

ACS Appl. Mater. Interfaces

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During the operation of synaptic devices based on traditional conductive filament (CF) models, the formation and dissolution of CFs are usually uncertain. Moreover, when the device is operated for a long time, the CFs may dissolve due to both the Joule heat generated by the device itself and the thermal coupling between the devices. These problems seriously reduce the reliability and stability of the synaptic device. Here, an artificial synapse device based on polyimide-molybdenum disulfide quantum dot (MoS 2 QD) nanocomposites is presented. Research has shown that MoS 2 QDs doped into the active layer can effectively induce the reduction of Ag ions into Ag atoms, leading to the formation of Ag clusters and thereby achieving control over the growth of the CFs. Therefore, the device is capable of stably realizing various basic synaptic functions. Moreover, the long-term potentiation/longterm depression (LTP/LTD) of this device shows good linearity. In addition, due to the change in the shape of the CFs, the highly integrated devices with a three-dimensional (3D) stacked structure can operate normally even in a high-temperature environment of 110 °C. Finally, the synaptic characteristics of the devices on learning and inference tests show that their recognition rates are approximately 90.75% (room temperature) and 90.63% (110 °C).

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Section: Results and Discussionmentioning

confidence: 99%

Three-Dimensional Integrated Synaptic Devices Based on a Silver-Cluster Conduction Mechanism with High Thermostability

Li,

et al. 2024

ACS Appl. Mater. Interfaces

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“…Recently, a memristor based on AgNO 3 -doped iota-carrageenan (ι-car) with an Ag/AgNO 3 : ι-car/ITO structure was prepared by Zhang et al to solve the nonlinear limitation problem. 148 This memristor showed a higher linear conductance regulation capacity of ∼10 4 , richer conduction states over 2000, and lower power consumption of 3.6 μW compared with other memristors. The authors point out that the doping of AgNO 3 into ι-car suppressed the formation of Ag conductive filaments, thereby eliminating inhomogeneous Joule heating.…”

Section: Research Progressmentioning

confidence: 87%

“…(i) A comparison of the linearity of the weight update curves (bottom) and the recognition accuracy of the handwritten digits (top). Panel i is reproduced with permission 148. Copyright 2021, American Chemical Society.…”

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confidence: 99%

Memristor-based neural networks: a bridge from device to artificial intelligence

et al. 2023

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Hydrogel‐Based Artificial Synapses for Sustainable Neuromorphic Electronics

Yan,

Armstrong,

Scarpa

et al. 2024

Advanced Materials

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Hydrogels find widespread applications in biomedicine because of their outstanding biocompatibility, biodegradability, and tunable material properties. Hydrogels can be chemically functionalized or reinforced to respond to physical or chemical stimulation, which opens up new possibilities in the emerging field of intelligent bioelectronics. Here, the state‐of‐the‐art in functional hydrogel‐based transistors and memristors is reviewed as potential artificial synapses. Within these systems, hydrogels can serve as semisolid dielectric electrolytes in transistors and as switching layers in memristors. These synaptic devices with volatile and non‐volatile resistive switching show good adaptability to external stimuli for short‐term and long‐term synaptic memory effects, some of which are integrated into synaptic arrays as artificial neurons; although, there are discrepancies in switching performance and efficacy. By comparing different hydrogels and their respective properties, an outlook is provided on a new range of biocompatible, environment‐friendly, and sustainable neuromorphic hardware. How potential energy‐efficient information storage and processing can be achieved using artificial neural networks with brain‐inspired architecture for neuromorphic computing is described. The development of hydrogel‐based artificial synapses can significantly impact the fields of neuromorphic bionics, biometrics, and biosensing.

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Biopolymer based artificial synapses enable linear conductance tuning and low-power for neuromorphic computing

Abstract: Neuromorphic computing is considered a promising method for resolving the traditional Von Neuman bottleneck. Natural biomaterial-based artificial synapse is the popular unit to construct neuromorphic computing systems while suffering from...

Cited by 7 publications

References 38 publications

Three-Dimensional Integrated Synaptic Devices Based on a Silver-Cluster Conduction Mechanism with High Thermostability

Three-Dimensional Integrated Synaptic Devices Based on a Silver-Cluster Conduction Mechanism with High Thermostability

Memristor-based neural networks: a bridge from device to artificial intelligence

Hydrogel‐Based Artificial Synapses for Sustainable Neuromorphic Electronics

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