Gelatin-hydrogel based organic synaptic transistor

Lai, Dengxiao; Li, Enlong; Yan, Yujie; Liu, Yaqian; Zhong, Jianfeng; Lv, Decheng; Ke, Yudan; Chen, Huipeng; Guo, Tao

doi:10.1016/j.orgel.2019.105409

Cited by 39 publications

(40 citation statements)

References 60 publications

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“…12 Hydrogels can be made using natural polymers such as alginate, chitosan, gelatin, starch, gellan gum, and cellulose. [13][14][15][16][17][18] In addition, hydrogels manufactured using synthetic polymers such as polyvinyl alcohol (PVA), polyvinyl pyrrolidone (PVP), polyethylene glycol (PEG), and polyacrylic acid (PAA) have the advantage of better mechanical properties. [19][20][21][22] PVA is the polymer most widely used for hydrogels because it can produce hydrogels with good mechanical properties and is biocompatible.…”

Section: Introductionmentioning

confidence: 99%

A freeze–thaw PVA hydrogel loaded with guava leaf extract: physical and antibacterial properties

et al. 2021

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Section: Introductionmentioning

confidence: 99%

A freeze–thaw PVA hydrogel loaded with guava leaf extract: physical and antibacterial properties

et al. 2021

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“…EDLbased memory devices can be gated using either ionic liquids or polymer electrolytes. The materials used for the channel layer include 2D transition-metal oxides (TMOs) [22] and dichalcogenides (TMDs), [23,33] conducting polymers, [14] and organic nanowire. [16] The use of 2D van der Waals (vdW) structures in synaptic devices for neuromorphic computing has provoked considerable interest because of the intriguing physical and chemical properties of these structures associated with their strictly defined low dimensionalities, [42,65] including their large surface-to-volume ratios, [33,66] dangling-bond-free surfaces, [65,67,68] and highly gatetunable bandgaps.…”

Section: Electric-double-layer Effectmentioning

confidence: 99%

“…EDL‐based memory devices can be gated using either ionic liquids or polymer electrolytes. The materials used for the channel layer include 2D transition‐metal oxides (TMOs) [ 22 ] and dichalcogenides (TMDs), [ 23,33 ] conducting polymers, [ 14 ] and organic nanowire. [ 16 ]…”

Section: Electric Field‐stimulated Switchingmentioning

confidence: 99%

“…The memristor was first demonstrated experimentally by Strukov and his colleagues [13] on a Pt/TiO 2−x /Pt cross-point device structure, in which the drift of the oxygen vacancies results in the observation of hysteresis behavior. Various materials (both organic [14][15][16][17][18] and inorganic [19][20][21][22] ) and structures (both planar [23][24][25] and vertical [26,27] ) have been used in synaptic devices, in attempts to imitate the operations of biological neural systems. To meet the requirement for high-density integration, miniaturization of the device dimensions represents the most direct and efficient approach.…”

Section: Introductionmentioning

confidence: 99%

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Stimuli‐Enabled Artificial Synapses for Neuromorphic Perception: Progress and Perspectives

Pan

Jin

Gao

et al. 2020

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Brain‐inspired neuromorphic computing is intended to provide effective emulation of the functionality of the human brain via the integration of electronic components. Recent studies of synaptic plasticity, which represents one of the most significant neurochemical bases of learning and memory, have enhanced the general comprehension of how the brain functions and have thereby eased the development of artificial neuromorphic devices. An understanding of the synaptic plasticity induced by various types of stimuli is essential for neuromorphic system construction. The realization of multiple stimuli‐enabled synapses will be important for future neuromorphic computing applications. In this Review, state‐of‐the‐art synaptic devices with particular emphasis on their synaptic behaviors under excitation by a variety of external stimuli are summarized, including electric fields, light, magnetic fields, pressure, and temperature. The switching mechanisms of these synaptic devices are discussed in detail, including ion migration, electron/hole transfer, phase transition, redox‐based resistive switching, and other mechanisms. This Review aims to provide a comprehensive understanding of the operating mechanisms of artificial synapses and thus provides the principles required for design of multifunctional neuromorphic systems with parallel processing capabilities.

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“…However, the monomer contained electrolyte and the irreversible polymerization process limits the potential of this approach. Another approach has been employed whereby a large bias (~5 V) is usually necessary to induce the heavily electrochemical doping in the active channel of the transistor, the slow ion migration kinetics, or even the irreversible electrochemical doping change the conductance of the transistor and enable the associative learning 31 – 33 . However, large write bias, incomplete reversibility, and limited retention time are drawbacks.…”

Section: Introductionmentioning

confidence: 99%

Mimicking associative learning using an ion-trapping non-volatile synaptic organic electrochemical transistor

et al. 2021

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Associative learning, a critical learning principle to improve an individual’s adaptability, has been emulated by few organic electrochemical devices. However, complicated bias schemes, high write voltages, as well as process irreversibility hinder the further development of associative learning circuits. Here, by adopting a poly(3,4-ethylenedioxythiophene):tosylate/Polytetrahydrofuran composite as the active channel, we present a non-volatile organic electrochemical transistor that shows a write bias less than 0.8 V and retention time longer than 200 min without decoupling the write and read operations. By incorporating a pressure sensor and a photoresistor, a neuromorphic circuit is demonstrated with the ability to associate two physical inputs (light and pressure) instead of normally demonstrated electrical inputs in other associative learning circuits. To unravel the non-volatility of this material, ultraviolet-visible-near-infrared spectroscopy, X-ray photoelectron spectroscopy and grazing-incidence wide-angle X-ray scattering are used to characterize the oxidation level variation, compositional change, and the structural modulation of the poly(3,4-ethylenedioxythiophene):tosylate/Polytetrahydrofuran films in various conductance states. The implementation of the associative learning circuit as well as the understanding of the non-volatile material represent critical advances for organic electrochemical devices in neuromorphic applications.

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Gelatin-hydrogel based organic synaptic transistor

Cited by 39 publications

References 60 publications

A freeze–thaw PVA hydrogel loaded with guava leaf extract: physical and antibacterial properties

A freeze–thaw PVA hydrogel loaded with guava leaf extract: physical and antibacterial properties

Stimuli‐Enabled Artificial Synapses for Neuromorphic Perception: Progress and Perspectives

Mimicking associative learning using an ion-trapping non-volatile synaptic organic electrochemical transistor

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