An Artificial Neural Network Implemented Using Parallel Dual-Gate Thin-Film Transistors

Hu, Yushen; Lei, Tengteng; Wang, Yuqi; Wang, Fei; Wong, Man

doi:10.1109/ted.2022.3201836

Cited by 5 publications

(1 citation statement)

References 15 publications

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“…Various hardware implementations of ANNs have been explored, including memristors, floating-gate transistors, and ferroelectric field effect transistors. The four-port structure of DG TFT, which is compatible with flexible substrate, makes it a promising candidate as an artificial synapse (9).…”

Section: Ann For Neuromorphic Computingmentioning

confidence: 99%

50‐4: Invited Paper: Low‐Temperature Metal‐Oxide Thin‐Film Transistor Technology and the Realization of Electronic Systems on Flexible Substrates

Shi,

Hu,

Xie

et al. 2024

Symp Digest of Tech Papers

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A low‐temperature technology for fabricating thin‐film transistors (TFTs) is essential for the realization of electronic systems on flexible substrates. Presently reviewed are improved techniques for forming the source/drain regions and reducing the population of channel defects in a metal‐oxide TFT. These have been applied to the construction of different TFT structures, including ones with bottom gate, top gate, and dual gates. The utility of the improved 300‐°C technology has been demonstrated by the realization of a variety of electronic systems, such as a gate‐driver on array for active‐matrix displays, an analog front‐end for acquiring biopotential signals, and an artificial neural network for neuromorphic computing.

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Section: Ann For Neuromorphic Computingmentioning

confidence: 99%

50‐4: Invited Paper: Low‐Temperature Metal‐Oxide Thin‐Film Transistor Technology and the Realization of Electronic Systems on Flexible Substrates

Shi,

Hu,

Xie

et al. 2024

Symp Digest of Tech Papers

Self Cite

View full text Add to dashboard Cite

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An Ion‐Mediated Spiking Chemical Neuron based on Mott Memristor

Ren,

Li,

Wang

et al. 2024

Advanced Materials

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Artificial spiking neurons capable of interpreting ionic information into electrical spikes are critical to mimic biological signaling systems. Mott memristors are attractive for constructing artificial spiking neurons due to their simple structure, low energy consumption, and rich neural dynamics. However, challenges remain in achieving ion‐mediated spiking and biohybrid‐interfacing in Mott neurons. Here, a biomimetic spiking chemical neuron (SCN) utilizing an NbOx Mott memristor and oxide field‐effect transistor‐type chemical sensor is introduced. The SCN exhibits both excitation and inhibition spiking behaviors toward ionic concentrations akin to biological neural systems. It demonstrates spiking responses across physiological and pathological Na+ concentrations (1–200 × 10−3 m). The Na+‐mediated SCN enables both frequency encoding and time‐to‐first‐spike coding schemes, illustrating the rich neural dynamics of Mott neuron. In addition, the SCN interfaced with L929 cells facilitates real‐time modulation of ion‐mediated spiking under both normal and salty cellular microenvironments.

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A “Smart” Gas Sensing System Composed of Micro-Hotplates and Artificial Neural Network

Liu,

Hu,

Wang

et al. 2024

J. Microelectromech. Syst.

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An Artificial Neural Network Implemented Using Parallel Dual-Gate Thin-Film Transistors

Cited by 5 publications

References 15 publications

50‐4: Invited Paper: Low‐Temperature Metal‐Oxide Thin‐Film Transistor Technology and the Realization of Electronic Systems on Flexible Substrates

50‐4: Invited Paper: Low‐Temperature Metal‐Oxide Thin‐Film Transistor Technology and the Realization of Electronic Systems on Flexible Substrates

An Ion‐Mediated Spiking Chemical Neuron based on Mott Memristor

A “Smart” Gas Sensing System Composed of Micro-Hotplates and Artificial Neural Network

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