Bioinspired Artificial Sensory Nerve Based on Nafion Memristor

Zhang, Chen; Ye, Wen Bin; Zhou, Kui; Chen, Hongye; Yang, Jiaqin; Ding, Guanglong; Chen, Xiaoli; Zhou, Ye; Zhou, Li; Li, Fengjiao; Han, Su‐Ting

doi:10.1002/adfm.201808783

Cited by 235 publications

(246 citation statements)

References 69 publications

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“…Nowadays, various types of electronic devices have been developed to simulate synaptic properties, such as phase‐change memories,13 synaptic transistors,14–16 and memristors 17–19. Synaptic behaviors have been successfully mimicked by these devices.…”

Section: Comparison Of the Energy Consumption From Other Researchesmentioning

confidence: 99%

The Design of 3D‐Interface Architecture in an Ultralow‐Power, Electrospun Single‐Fiber Synaptic Transistor for Neuromorphic Computing

Liu

Shi

Dai

et al. 2020

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Synaptic electronics is a new technology for developing functional electronic devices that can mimic the structure and functions of biological counterparts. It has broad application prospects in wearable computing chips, human–machine interfaces, and neuron prostheses. These types of applications require synaptic devices with ultralow energy consumption as the effective energy supply for wearable electronics, which is still very difficult. Here, artificial synapse emulation is demonstrated by solid‐ion gated organic field‐effect transistors (OFETs) with a 3D‐interface conducting channel for ultralow‐power synaptic simulation. The basic features of the artificial synapse, excitatory postsynaptic current (EPSC), paired‐pulse facilitation (PPF), and high‐pass filtering, are successfully realized. Furthermore, the single‐fiber based artificial synapse can be operated by an ultralow presynaptic spike down to −0.5 mV with an ultralow reading voltage at −0.1 mV due to the large contact surface between the ionic electrolyte and fiber‐like semiconducting channel. Therefore, the ultralow energy consumption at one spike of the artificial synapse can be realized as low as ≈3.9 fJ, which provides great potential in a low‐power integrated synaptic circuit.

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Section: Comparison Of the Energy Consumption From Other Researchesmentioning

confidence: 99%

The Design of 3D‐Interface Architecture in an Ultralow‐Power, Electrospun Single‐Fiber Synaptic Transistor for Neuromorphic Computing

Liu

Shi

Dai

et al. 2020

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“…a) A schematic of the steps required for the transduction of sensory stimuli from natural (top) or artificial (bottom) receptors in the brain. Reproduced with permission . Copyright 2019, John Wiley and Sons.…”

Section: Intelligent Artificial Perception Using Integrated Memristivmentioning

confidence: 99%

“…In Figure a, an artificial haptic neuron system was demonstrated by integrating a piezoresistive sensor with a Nafion‐based memristor . The piezoresistive sensor serves as a sensory receptor to transform mechanical stimuli into electric signals, exhibiting a high sensitivity of 6.7 × 10 7 kPa −1 within a low pressure range from 1 to 5 kPa (Figure b).…”

Section: Intelligent Artificial Perception Using Integrated Memristivmentioning

confidence: 99%

“…Artificial haptic perception system . a) The artificial haptic perception system consisting of a pressure sensor and a Nafion‐based memristor.…”

Section: Intelligent Artificial Perception Using Integrated Memristivmentioning

confidence: 99%

Section: Intelligent Artificial Perception Using Integrated Memristivmentioning

confidence: 99%

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Artificial Perception Built on Memristive System: Visual, Auditory, and Tactile Sensations

Zhao

Tan

et al. 2020

Advanced Intelligent Systems

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The widespread implementation and rapid development of autonomous systems pose stringent performance requirements on emerging sensory systems. In addition to the basic sensing requirements, leading sensory systems are required to process data and extract featured information from highly redundant data in real time. With the added edge‐computational capabilities, data shuttling is avoided, leading to significant reduction of computational burden and bandwidth pressure in the cloud. Among the different computing architectures, the neuromorphic sensory system stands out due to its high power efficiency, low latency, and excellent processing capability. Mimicking the biological neural network, the colocation of sensory, processor, and memory components of neuromorphic sensory systems enables the requirements for frequent data shuttles to be circumvented. In particular, artificial intelligent perceptions built on memristive neuromorphic systems exhibit outstanding characteristics of small footprint, low power consumption, 3D stacking ability, and high density. Herein, the two essential parts of the memristive artificial perceptron system are presented: 1) memristive systems for neuromorphic computing and 2) high‐performance sensors. Next, the current state of the art established on artificial perceptron systems covering visual, auditory, and tactile sensations is highlighted. To conclude, the current challenges and future direction in the area of advanced intelligent perceptions are presented.

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Realization of Artificial Nerve Synapses Based on Biological Threshold Resistive Random Access Memory

2023

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A one‐selector one resistor (1S1R) array formed of a selector and resistive random access memory (RRAM) is an important way to achieve high‐density storage and neuromorphic computing. However, the low durability and poor consistency of the selector limit its practical application. The fabrication of a selector based on egg albumen (EA) is reported in this paper. The device exhibits excellent bidirectional threshold switching characteristics, including a low leakage current (10−7 A), a high ON/OFF current ratio (106), and good endurance (>700 days). It is used as a selector to form a 1S1R unit in combination with an EA‐based RRAM to effectively solve the leakage current in a crossbar array. A feasible solution is provided for the realization of a protein‐based 1S1R array to achieve high‐density storage. The 1S1R unit shows characteristics similar to those of synapses in the human brain under impulse excitation and has great potential in simulating the human brain for neuromorphic calculations.)

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Bioinspired Artificial Sensory Nerve Based on Nafion Memristor

Cited by 235 publications

References 69 publications

The Design of 3D‐Interface Architecture in an Ultralow‐Power, Electrospun Single‐Fiber Synaptic Transistor for Neuromorphic Computing

The Design of 3D‐Interface Architecture in an Ultralow‐Power, Electrospun Single‐Fiber Synaptic Transistor for Neuromorphic Computing

Artificial Perception Built on Memristive System: Visual, Auditory, and Tactile Sensations

Realization of Artificial Nerve Synapses Based on Biological Threshold Resistive Random Access Memory

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