Flexible artificial Si-In-Zn-O/ion gel synapse and its application to sensory-neuromorphic system for sign language translation

Oh, Seyong; Cho, Jeong‐Ick; Lee, Byeong Hyeon; Seo, Seunghwan; Lee, Ju Hee; Choo, Hyongsuk; Heo, Keun; Lee, Sang Yeol; Park, Jin‐Hong

doi:10.1126/sciadv.abg9450

Cited by 55 publications

(27 citation statements)

References 73 publications

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“…The NL extraction method and LTP/LTD curves investigated under various pulse conditions are shown in Figures S13 and S14 (Supporting Information). [ 35 , 36 , 37 ] Finally, we demonstrate its applicability to hardware neural networks (HW‐NNs) using the “DNN+ NeuroSim” simulator. [ 38 ] The artificial neural network of the simulator was a CNN, and the Canadian Institute for Advanced Research‐10 (CIFAR‐10) image dataset was used for training (50 000 images) and inference (10 000 images) tasks.…”

Section: Resultsmentioning

confidence: 99%

Ferroelectric Field‐Effect‐Transistor Integrated with Ferroelectrics Heterostructure

Baek

Yoo

et al. 2022

Advanced Science

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To address the demands of emerging data-centric computing applications, ferroelectric field-effect transistors (Fe-FETs) are considered the forefront of semiconductor electronics owing to their energy and area efficiency and merged logic-memory functionalities. Herein, the fabrication and application of an Fe-FET, which is integrated with a van der Waals ferroelectrics heterostructure (CuInP 2 S 6 /𝜶-In 2 Se 3 ), is reported. Leveraging enhanced polarization originating from the dipole coupling of CIPS and 𝜶-In 2 Se 3 , the fabricated Fe-FET exhibits a large memory window of 14.5 V at V GS = ±10 V, reaching a memory window to sweep range of ≈72%. Piezoelectric force microscopy measurements confirm the enhanced polarization-induced wider hysteresis loop of the double-stacked ferroelectrics compared to single ferroelectric layers. The Landau-Khalatnikov theory is extended to analyze the ferroelectric characteristics of a ferroelectric heterostructure, providing detailed explanations of the hysteresis behaviors and enhanced memory window formation. The fabricated Fe-FET shows nonvolatile memory characteristics, with a high on/off current ratio of over 10 6 , long retention time (>10 4 s), and stable cyclic endurance (>10 4 cycles). Furthermore, the applicability of the ferroelectrics heterostructure is investigated for artificial synapses and for hardware neural networks through training and inference simulation. These results provide a promising pathway for exploring low-dimensional ferroelectronics.

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Section: Resultsmentioning

confidence: 99%

Ferroelectric Field‐Effect‐Transistor Integrated with Ferroelectrics Heterostructure

Baek

Yoo

et al. 2022

Advanced Science

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“…4 b) [ 19 ]. Park et al [ 20 ] reported an ion-gel transistor-type ES using an ion-gel electrolyte composed of EMIM-TFSI and a gel matrix (Fig. 4 c).…”

Section: Neuromorphic Vision Sensor For Near-sensor Vision Computingmentioning

confidence: 99%

“…4 c). The mechanical flexibility of the gel allowed for the reliable fabrication and operation of ion-gel-based ESs on plastic substrates [ 20 – 23 ]. With this flexible in-memory computing device, tactile information from the human hand could be preprocessed directly, without the aid of an external computer device.…”

Section: Neuromorphic Vision Sensor For Near-sensor Vision Computingmentioning

confidence: 99%

Progress of Materials and Devices for Neuromorphic Vision Sensors

Cho

Jo²,

Kim³

et al. 2022

Nano-Micro Lett.

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The latest developments in bio-inspired neuromorphic vision sensors can be summarized in 3 keywords: smaller, faster, and smarter. (1) Smaller: Devices are becoming more compact by integrating previously separated components such as sensors, memory, and processing units. As a prime example, the transition from traditional sensory vision computing to in-sensor vision computing has shown clear benefits, such as simpler circuitry, lower power consumption, and less data redundancy. (2) Swifter: Owing to the nature of physics, smaller and more integrated devices can detect, process, and react to input more quickly. In addition, the methods for sensing and processing optical information using various materials (such as oxide semiconductors) are evolving. (3) Smarter: Owing to these two main research directions, we can expect advanced applications such as adaptive vision sensors, collision sensors, and nociceptive sensors. This review mainly focuses on the recent progress, working mechanisms, image pre-processing techniques, and advanced features of two types of neuromorphic vision sensors based on near-sensor and in-sensor vision computing methodologies. "Image missing"

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“…The hardware neural networks made of silicon (Si) suffer from several drawbacks such as poor biocompatibility and rigidity and also require numerous circuit elements, making biointegration difficult. EDLTs are biocompatible, solution-processable, biodegradable, conformable, and soft, making them ideal for bioelectronic applications. ,− EDLTs modulated by a field-driven ion migration in the electrolyte layer could be operated with high transconductance, excellent stability of threshold voltage, linear weight updates, and strong ion-concentration-dependent switching properties, becoming a competitive alternative in this area. − However, to date, there is no report on a flexible EDLT that provides all the aforementioned performance characteristics.…”

Section: Introductionmentioning

confidence: 99%

Flexible Floating-Gate Electric-Double-Layer Organic Transistor for Neuromorphic Computing

Zheng

Liao

Wang

et al. 2022

ACS Appl. Mater. Interfaces

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The key to the study of flexible neuromorphic computing is the excellent weight update characteristic of neuromorphic devices. Electric-double-layer transistors (EDLTs) include high transconductance, excellent stability of threshold voltage, linear weight updates, and repetitive ion-concentration-dependent switching properties. However, up to now, there is no report on a flexible EDLT that provides all the aforementioned performance characteristics. Here, a planar flexible floating-gate EDLT including an excellent linear/symmetric weight update, a large number (>800) of conductance states, repetitive switching endurance (>100 cycles), and low variation in weight update is reported. After 800 signal stimulations, it is found that the nonlinearity values of LTP are between 0.20 and 0.85, those of LTD fall between 0.66 and 1.55, the symmetricity values are between 120.7 and 639.8, and the dynamic range is between 150 and 352 nS. The study of 8 × 8 flexible floating-gate EDLT arrays shows that the average deviation and standard deviation between the experimental and theoretical values are 1.36 and 1.93, respectively, indicating that the conductance regulation in the array has a relatively small deviation. The different bending angles and the mechanical stability of the floating-gate EDLT are also studied, which exhibit the excellent bending properties. Furthermore, we studied the recognition of MNIST handwritten digit images by a three-layer perceptron artificial neural network with the experimental weight update, and the maximal recognition accuracy is up to 87.8%.

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Flexible artificial Si-In-Zn-O/ion gel synapse and its application to sensory-neuromorphic system for sign language translation

Abstract: Flexible artificial synapses are fabricated with a SIZO/ion gel hybrid structure forming a polyimide substrate.

Cited by 55 publications

References 73 publications

Ferroelectric Field‐Effect‐Transistor Integrated with Ferroelectrics Heterostructure

Ferroelectric Field‐Effect‐Transistor Integrated with Ferroelectrics Heterostructure

Progress of Materials and Devices for Neuromorphic Vision Sensors

Flexible Floating-Gate Electric-Double-Layer Organic Transistor for Neuromorphic Computing

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