Advanced artificial synaptic thin-film transistor based on doped potassium ions for neuromorphic computing <i>via</i> third-generation neural network

Cao, Yixin; Zhao, Tianshi; Liu, Yina; Song, Pengfei; Gao, Hao; Zhao, Chun

doi:10.1039/d1tc04827a

Cited by 17 publications

(5 citation statements)

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“…In neural networks, STP and LTP, along with PPF, are essential in the configuration of spiking neural networks (SNNs) [ 38 ]. As third-generation neural networks, SNNs are considered the most suitable model for neuromorphic hardware implementations due to their faster processing and highly efficient energy consumption [ 39 , 40 ]. However, compared to the conventional ANN with backpropagation learning, SNNs still lack robust learning rules and their network design principles are immature, requiring further research for commercialization, unlike established frameworks like TensorFlow [ 41 ].…”

Section: Resultsmentioning

confidence: 99%

Enhanced Synaptic Behaviors in Chitosan Electrolyte-Based Electric-Double-Layer Transistors with Poly-Si Nanowire Channel Structures

Lee,

Kim,

Park

et al. 2023

Biomimetics

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In this study, we enhance the synaptic behavior of artificial synaptic transistors by utilizing nanowire (NW)-type polysilicon channel structures. The high surface-to-volume ratio of the NW channels enables efficient modulation of the channel conductance, which is interpreted as the synaptic weight. As a result, NW-type synaptic transistors exhibit a larger hysteresis window compared to film-type synaptic transistors, even within the same gate voltage sweeping range. Moreover, NW-type synaptic transistors demonstrate superior short-term facilitation and long-term memory transition compared with film-type ones, as evidenced by the measured paired-pulse facilitation and excitatory post-synaptic current characteristics at varying frequencies and pulse numbers. Additionally, we observed gradual potentiation/depression characteristics, making these artificial synapses applicable to artificial neural networks. Furthermore, the NW-type synaptic transistors exhibit improved Modified National Institute of Standards and Technology pattern recognition rate of 91.2%. In conclusion, NW structure channels are expected to be a promising technology for next-generation artificial intelligence (AI) semiconductors, and the integration of NW structure channels has significant potential to advance AI semiconductor technology.

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Section: Resultsmentioning

confidence: 99%

Enhanced Synaptic Behaviors in Chitosan Electrolyte-Based Electric-Double-Layer Transistors with Poly-Si Nanowire Channel Structures

Lee,

Kim,

Park

et al. 2023

Biomimetics

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“…This study curated a dataset comprising images of five sign languages: 'prayer', 'you are awesome', 'prohibition', 'sleep', and 'ok', as depicted in figure 5(a). To facilitate the learning process of the sign language dataset, the ANN based on a single-layer perceptron was devised, consisting of an input layer, a hidden layer, and an output layer (figure 5(b)) [39]. When the input layer receives the visual data, it divides the current vector (I) by the matrices formed by the input vector (V ) and the synaptic weight matrix (W), yielding the output.…”

Section: Synaptic Characteristics Of Tftmentioning

confidence: 99%

High precision of sign language recognition based on In₂O₃ transistors gated by AlLiO solid electrolyte

Bian,

Geng,

Dong

et al. 2023

Nanotechnology

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In recent years, the synaptic properties of transistors have been extensively studied. Compared with liquid or organic material-based transistors, inorganic solid electrolyte-gated transistors have the advantage of better chemical stability. This study uses a simple, low-cost solution technology to prepare In2O3 transistors gated by AlLiO solid electrolyte. The electrochemical performance of the device is achieved by forming a double electric layer and electrochemical doping, which can mimic basic functions of biological synapses, such as excitatory postsynaptic current, paired-pulse promotion, and spiking time-dependent plasticity. Furthermore, complex synaptic behaviors such as Pavlovian classical conditioning is successfully emulated. With a 95% identification accuracy, an artificial neural network based on transistors is built to recognize sign language and enable sign language interpretation. Additionally, the handwriting digit’s identification accuracy is 94%. Even with various levels of Gaussian noise, the recognition rate is still above 84%. The above findings demonstrate the potential of In2O3/AlLiO TFT in shaping the next generation of artificial intelligence.

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“…It encodes spatiotemporal information within the neurons, which transmit information only when the membrane potential reaches a specific threshold. [6][7][8] Thus, an SNN offers a promising alternative to an ANN with higher energy efficiency.…”

Section: Introductionmentioning

confidence: 99%

A bi-functional three-terminal memristor applicable as an artificial synapse and neuron

Liu,

Dananjaya,

Ang

et al. 2023

Nanoscale

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Advanced artificial synaptic thin-film transistor based on doped potassium ions for neuromorphic computing via third-generation neural network

Abstract: As the basic and essential unit of neuromorphic computing systems, artificial synaptic devices have the great potential to accelerate high-performance parallel computation, artificial intelligence, and adaptive learning. Among the proposed...

Cited by 17 publications

References 70 publications

Enhanced Synaptic Behaviors in Chitosan Electrolyte-Based Electric-Double-Layer Transistors with Poly-Si Nanowire Channel Structures

Enhanced Synaptic Behaviors in Chitosan Electrolyte-Based Electric-Double-Layer Transistors with Poly-Si Nanowire Channel Structures

High precision of sign language recognition based on In₂O₃ transistors gated by AlLiO solid electrolyte

A bi-functional three-terminal memristor applicable as an artificial synapse and neuron

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Advanced artificial synaptic thin-film transistor based on doped potassium ions for neuromorphic computing via third-generation neural network

Abstract: As the basic and essential unit of neuromorphic computing systems, artificial synaptic devices have the great potential to accelerate high-performance parallel computation, artificial intelligence, and adaptive learning. Among the proposed...

Cited by 17 publications

References 70 publications

Enhanced Synaptic Behaviors in Chitosan Electrolyte-Based Electric-Double-Layer Transistors with Poly-Si Nanowire Channel Structures

Enhanced Synaptic Behaviors in Chitosan Electrolyte-Based Electric-Double-Layer Transistors with Poly-Si Nanowire Channel Structures

High precision of sign language recognition based on In2O3 transistors gated by AlLiO solid electrolyte

A bi-functional three-terminal memristor applicable as an artificial synapse and neuron

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Product

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High precision of sign language recognition based on In₂O₃ transistors gated by AlLiO solid electrolyte