Organic iontronic memristors for artificial synapses and bionic neuromorphic computing

Nanoscale, Год журнала: 2023, Номер 16(4), С. 1471 - 1489

Опубликована: Дек. 15, 2023

To tackle the current crisis of Moore's law, a sophisticated strategy entails development multistable memristors, bionic artificial synapses, logic circuits and brain-inspired neuromorphic computing. In comparison with conventional electronic systems, iontronic memristors offer greater potential for manifestation intelligence brain-machine interaction. Organic memristive materials (OIMs), which possess an organic backbone exhibit stoichiometric ionic states, have emerged as pivotal contenders realization high-performance memristors. this review, comprehensive analysis progress prospects OIMs is presented, encompassing their inherent advantages, diverse types, synthesis methodologies, wide-ranging applications in devices. Predictably, field OIMs, rapidly developing research subject, presents exciting opportunity highly efficient neuro-iontronic systems areas such in-sensor computing devices, human perception.

Язык: Английский

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Synaptic transistor based on reversible hydrogenation of graphene channel

Applied Physics Letters, Год журнала: 2025, Номер 126(1)

Опубликована: Янв. 2, 2025

Graphene transistors with a gate-controlled transition of neuromorphic functions between artificial neurons and synapses have attracted increasing attention because the atomic thickness could be easily modulated by different stimuli, which is very beneficial for synaptic applications. As modulation method, graphene electrolyte-gated transistor (EGT) has been proposed, in electrical conductance channel reversible electrochemical hydrogenation graphene. However, only sparse physically realized graphene-based H+-EGTs reported due to difficulty achieving high concentration protons at electrolyte–graphene interface. Here, we highly defective gel electrolyte [H3PO4/poly(vinyl alcohol)], based on dehydrogenation defected-graphene, performing similar as common transistors, good retention (<1% attenuation per minute), analog tunability (>200 nonvolatile states), precisely controllable resistance (∼0.4% step flipped event). In addition, cyclic voltammetry test was applied confirm channel. It expected that this principle can provide ideas designing enabling integrated in-memory computing sensing system.

Язык: Английский

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Electrodeposited Co - Ni layered double hydroxide film with tunable dielectric properties for resistive switching

Physical Review Applied, Год журнала: 2025, Номер 23(5)

Опубликована: Май 5, 2025

Язык: Английский

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Optimization Strategy of the Emerging Memristors: from Material Preparation to Device Applications

iScience, Год журнала: 2024, Номер 27(12), С. 111327 - 111327

Опубликована: Ноя. 6, 2024

Язык: Английский

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Toward Enhanced Biomimetic Artificial Visual Systems Based on Organic Heterojunction Optoelectronic Synaptic Transistors

Advanced Electronic Materials, Год журнала: 2024, Номер unknown

Опубликована: Сен. 17, 2024

Abstract Artificial visual systems, inspired by the human eye, hold significant potential in artificial intelligence. Optoelectronic synapses, integrating image perception, processing, and memory a single device, offer promising solutions. The eye exhibits different recognition accuracies for objects under varying light conditions. Therefore, more biomimetic system is needed to better fit actual application scenarios. Here, an organic heterojunction‐based optoelectronic synaptic transistor (OHOST) proposed enhance systems. By utilizing excellent carrier capture ability of core‐multi‐shell quantum dots (QDs) high exciton dissociation efficiency heterojunction interfaces, device achieves capability intensities closely resembling that eye. Under optimal intensity, accuracy modified national institute standards technology (MNIST) dataset can reach 91.52%. Nevertheless, both low intensities, drops level. This work pushes development systems toward higher levels biomimicry.

Язык: Английский

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Memristive Artificial Synapses Based on Brownmillerite for Endurable Weight Modulation

Small, Год журнала: 2024, Номер unknown

Опубликована: Окт. 29, 2024

Exploring a computing paradigm that blends memory and computation functions is essential for artificial synapses. While memristors synapses are widely studied due to their energy-efficient structures, random filament conduction in general makes them less preferred endurability long-term synaptic modulation. Herein, the topotactic phase transition (TPT) brownmillerite-phased (110)-SrCoO

Язык: Английский

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