A Fully Solution‐Printed Photosynaptic Transistor Array with Ultralow Energy Consumption for Artificial‐Vision Neural Networks

Advanced Materials, Journal Year: 2022, Volume and Issue: 34(18)

Published: March 4, 2022

Photosynaptic organic field-effect transistors (OFETs) represent a viable pathway to develop bionic optoelectronics. However, the high operating voltage and current of traditional photosynaptic OFETs lead huge energy consumption greater than that real biological synapses, hindering their further development in new-generation visual prosthetics artificial perception systems. Here, fully solution-printed OFET (FSP-OFET) with substantial reduction is reported, where source Schottky barrier introduced regulate charge-carrier injection, which operates fundamentally different mechanism from devices. The FSP-OFET not only significantly lowers working but also provides extraordinary neuromorphic light-perception capabilities. Consequently, successfully emulates nervous responses external light stimuli ultralow 0.07-34 fJ per spike short-term plasticity 0.41-19.87 long-term plasticity, both approaching efficiency synapses (1-100 fJ). Moreover, an optic-neural network made 8 × array on flexible substrate shows excellent image recognition reinforcement abilities at low cost. designed offers opportunity realize photonic functionality extremely dissipation.

Language: Английский

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Artificial Neuron Devices

Chemical Reviews, Journal Year: 2023, Volume and Issue: 123(23), P. 13796 - 13865

Published: Nov. 17, 2023

Efforts to design devices emulating complex cognitive abilities and response processes of biological systems have long been a coveted goal. Recent advancements in flexible electronics, mirroring human tissue's mechanical properties, hold significant promise. Artificial neuron devices, hinging on artificial synapses, bioinspired sensors, actuators, are meticulously engineered mimic the systems. However, this field is its infancy, requiring substantial groundwork achieve autonomous with intelligent feedback, adaptability, tangible problem-solving capabilities. This review provides comprehensive overview recent devices. It starts fundamental principles synaptic explores sensory systems, integrating synapses sensors replicate all five senses. A systematic presentation nervous follows, designed emulate system functions. The also discusses potential applications outlines existing challenges, offering insights into future prospects. We aim for illuminate burgeoning inspiring further innovation captivating area research.

Language: Английский

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Retina‐Inspired Artificial Synapses with Ultraviolet to Near‐Infrared Broadband Responses for Energy‐Efficient Neuromorphic Visual Systems

Advanced Functional Materials, Journal Year: 2023, Volume and Issue: 33(32)

Published: April 21, 2023

Abstract Neuromorphic visual system with image perception, memory, and preprocessing functions is expected to simulate basic features of the human retina. Organic optoelectronic synaptic transistors emulating biological synapses may be promising candidates for constructing neural morphological system. However, sensing wavelength range organic usually limits their potential in artificial multispectral perception. Here, retina‐inspired that present broadband responses covering ultraviolet, visible, near‐infrared regions are demonstrated, which leverage wide‐range photoresponsive charge trapping layer heterostructure formed between PbS quantum dots semiconductor. Simplified neuromorphic arrays developed comprehensive functions. Benefitting from flexibility semiconductor layers, a flexible array can fabricated, having an ultralow power consumption 0.55 fJ per event under low operating voltage −0.01 V. More significantly, accelerating effect observed wide even beyond perception system, due gate‐adjustable plasticity. These devices highly implementing systems increasing processing efficiency, promoting development vision.

Language: Английский

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Tailoring neuroplasticity in flexible perovskite QDs-based optoelectronic synaptic transistors by dual modes modulation

Nano Energy, Journal Year: 2022, Volume and Issue: 95, P. 106987 - 106987

Published: Jan. 25, 2022

Language: Английский

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Essential Characteristics of Memristors for Neuromorphic Computing

Advanced Electronic Materials, Journal Year: 2022, Volume and Issue: 9(2)

Published: Oct. 25, 2022

Abstract The memristor is a resistive switch where its state programable based on the applied voltage or current. Memristive devices are thus capable of storing and computing information simultaneously, breaking Von Neumann bottleneck. Since first nanomemristor made by Hewlett‐Packard in 2008, advances so far have enabled nanostructured, low‐power, high‐durability that exhibit superior performance over conventional CMOS devices. Herein, development memristors different physical mechanisms reviewed. In particular, device stability, integration density, power consumption, switching speed, retention, endurance memristors, crucial for neuromorphic computing, discussed detail. An overview various neural networks with focus building memristor‐based spike network system then provided. Finally, existing issues challenges implementing such systems analyzed, an outlook brain‐like proposed.

Language: Английский

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Emerging MXene‐Based Memristors for In‐Memory, Neuromorphic Computing, and Logic Operation

Advanced Functional Materials, Journal Year: 2022, Volume and Issue: 33(1)

Published: Nov. 14, 2022

Abstract Confronted by the difficulties of von Neumann bottleneck and memory wall, traditional computing systems are gradually inadequate for satisfying demands future data‐intensive applications. Recently, memristors have emerged as promising candidates advanced in‐memory neuromorphic computing, which pave one way breaking through dilemma current architecture. Till now, varieties functional materials been developed constructing high‐performance memristors. Herein, review focuses on emerging 2D MXene materials‐based First, mainstream synthetic strategies characterization methods MXenes introduced. Second, different types MXene‐based memristive their widely adopted switching mechanisms overviewed. Third, recent progress data storage, artificial synapses, logic circuits is comprehensively summarized. Finally, challenges, development trends, perspectives discussed, aiming to provide guidelines preparation novel more engaging information technology

Language: Английский

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Bioinspired iontronic synapse fibers for ultralow-power multiplexing neuromorphic sensorimotor textiles

Proceedings of the National Academy of Sciences, Journal Year: 2024, Volume and Issue: 121(33)

Published: Aug. 7, 2024

Artificial neuromorphic devices can emulate dendric integration, axonal parallel transmission, along with superior energy efficiency in facilitating efficient information processing, offering enormous potential for wearable electronics. However, integrating such circuits into textiles to achieve biomimetic perception, and control motion feedback remains a formidable challenge. Here, we engineer quasi-solid-state iontronic synapse fiber (ISF) comprising photoresponsive TiO 2 , ion storage Co-MoS an transport layer. The resulting ISF achieves inherent short-term synaptic plasticity, femtojoule-range consumption, the ability transduce chemical/optical signals. Multiple ISFs are interwoven synthetic neural fabric, allowing simultaneous propagation of distinct optical signals transmitting information. Importantly, IFSs multiple input electrodes exhibit spatiotemporal integration. As proof concept, textile-based multiplexing sensorimotor system is constructed connect fibers artificial muscles, enabling preneuronal sensing postneuronal output coordinated motor muscles. proposed holds promise electronics, soft robotics, biomedical engineering.

Language: Английский

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Polymeric Memristor Based Artificial Synapses with Ultra‐Wide Operating Temperature

Advanced Materials, Journal Year: 2023, Volume and Issue: 35(23)

Published: March 27, 2023

Neuromorphic electronics, being inspired by how the brain works, hold great promise to successful implementation of smart artificial systems. Among several neuromorphic hardware issues, a robust device functionality under extreme temperature is particular importance for practical applications. Given that organic memristors synapse applications are demonstrated room temperature, achieving performance at extremely low or high still utterly challenging. In this work, issue addressed tuning solution-based polymeric memristor. The optimized memristor demonstrates reliable both cryogenic and high-temperature environments. unencapsulated shows memristive response test ranging from 77 573 K. Utilizing X-ray photoelectron spectroscopy (XPS) time-of-flight secondary-ion mass spectrometry (ToF-SIMS) depth profiling, working mechanism unveiled comparing compositional profiles fresh written memristors. A reversible ion migration induced an applied voltage contributes characteristic switching behavior Herein, achieved temperatures verified will remarkably accelerate development in

Language: Английский

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Reconfigurable Neuromorphic Computing: Materials, Devices, and Integration

Advanced Materials, Journal Year: 2023, Volume and Issue: 35(51)

Published: June 7, 2023

Abstract Neuromorphic computing has been attracting ever‐increasing attention due to superior energy efficiency, with great promise promote the next wave of artificial general intelligence in post‐Moore era. Current approaches are, however, broadly designed for stationary and unitary assignments, thus encountering reluctant interconnections, power consumption, data‐intensive that domain. Reconfigurable neuromorphic computing, an on‐demand paradigm inspired by inherent programmability brain, can maximally reallocate finite resources perform proliferation reproducibly brain‐inspired functions, highlighting a disruptive framework bridging gap between different primitives. Although relevant research flourished diverse materials devices novel mechanisms architectures, precise overview remains blank urgently desirable. Herein, recent strides along this pursuit are systematically reviewed from material, device, integration perspectives. At material device level, one comprehensively conclude dominant reconfigurability, categorized into ion migration, carrier phase transition, spintronics, photonics. Integration‐level developments reconfigurable also exhibited. Finally, perspective on future challenges is discussed, definitely expanding its horizon scientific communities.

Language: Английский

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Enhancing plasticity in optoelectronic artificial synapses: A pathway to efficient neuromorphic computing

Applied Physics Letters, Journal Year: 2024, Volume and Issue: 124(2)

Published: Jan. 8, 2024

The continuous growth in artificial intelligence and high-performance computing has necessitated the development of efficient optoelectronic synapses crucial for neuromorphic (NC). Ga2O3 is an emerging wide-bandgap semiconductor with high deep ultraviolet absorption, tunable persistent photoconductivity, excellent stability toward electric fields, making it a promising component synapses. Currently reported often suffer from complex fabrication processes potential room improvement due to plasticity. To address issue low device plasticity practical application scenarios, we present amorphous (α-GaOx) flexible synapse. This synapse modulates light stimulus signals using electron/oxygen vacancies optical stimulation operates as visual storage information processing. We investigate synapses' by controlling number oxygen via plasma treatment method demonstrate its effective three-layer backpropagation neural network handwritten digit classification. Under same conditions, synaptic weight samples treated Ar exhibits higher rate change, current levels increasing 2–3 orders magnitude, achieving greater improved achieved accuracy 93.34%/94%, demonstrating their solutions insights future applications NC chips.

Language: Английский

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