Neuromorphic nanoelectronic materials

Nature Nanotechnology, Год журнала: 2020, Номер 15(7), С. 517 - 528

Опубликована: Март 2, 2020

Язык: Английский

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Bridging Biological and Artificial Neural Networks with Emerging Neuromorphic Devices: Fundamentals, Progress, and Challenges

Advanced Materials, Год журнала: 2019, Номер 31(49)

Опубликована: Сен. 24, 2019

As the research on artificial intelligence booms, there is broad interest in brain-inspired computing using novel neuromorphic devices. The potential of various emerging materials and devices for has attracted extensive efforts, leading to a large number publications. Going forward, order better emulate brain's functions, its relevant fundamentals, working mechanisms, resultant behaviors need be re-visited, understood, connected electronics. A systematic overview biological neural systems given, along with their related critical mechanisms. Recent progress reviewed and, more importantly, existing challenges are highlighted hopefully shed light future directions.

Язык: Английский

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A comprehensive review on emerging artificial neuromorphic devices

Applied Physics Reviews, Год журнала: 2020, Номер 7(1)

Опубликована: Фев. 24, 2020

The rapid development of information technology has led to urgent requirements for high efficiency and ultralow power consumption. In the past few decades, neuromorphic computing drawn extensive attention due its promising capability in processing massive data with extremely low Here, we offer a comprehensive review on emerging artificial devices their applications. light inner physical processes, classify into nine major categories discuss respective strengths weaknesses. We will show that anion/cation migration-based memristive devices, phase change, spintronic synapses have been quite mature possess excellent stability as memory device, yet they still suffer from challenges weight updating linearity symmetry. Meanwhile, recently developed electrolyte-gated synaptic transistors demonstrated outstanding energy efficiency, linearity, symmetry, but scalability need be optimized. Other structures, such ferroelectric, metal–insulator transition based, photonic, purely electronic also limitations some aspects, therefore leading further developing high-performance devices. Additional efforts are demanded enhance functionality neurons while maintaining relatively cost area power, it significance explore intrinsic neuronal stochasticity optimize driving capability, etc. Finally, by looking correlations between operation mechanisms, material systems, device performance, provide clues future selections, designs, integrations neurons.

Язык: Английский

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Recent Advances in Transistor‐Based Artificial Synapses

Advanced Functional Materials, Год журнала: 2019, Номер 29(42)

Опубликована: Авг. 9, 2019

Abstract Simulating biological synapses with electronic devices is a re‐emerging field of research. It widely recognized as the first step in hardware building brain‐like computers and artificial intelligent systems. Thus far, different types have been proposed to mimic synaptic functions. Among them, transistor‐based advantages good stability, relatively controllable testing parameters, clear operation mechanism, can be constructed from variety materials. In addition, they perform concurrent learning, which weight update performed without interrupting signal transmission process. Synergistic control one device also implemented synapse, opens up possibility developing robust neuron networks significantly fewer neural elements. These unique features make them more suitable for emulating functions than other devices. However, development still its very early stages. Herein, this article presents review recent advances order give guideline future implementation transistors. The main challenges research directions are presented.

Язык: Английский

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A MoS₂/PTCDA Hybrid Heterojunction Synapse with Efficient Photoelectric Dual Modulation and Versatility

Advanced Materials, Год журнала: 2018, Номер 31(3)

Опубликована: Ноя. 28, 2018

Just as biological synapses provide basic functions for the nervous system, artificial synaptic devices serve fundamental building blocks of neuromorphic networks; thus, developing novel is essential computing. By exploiting band alignment between 2D inorganic and organic semiconductors, first multi-functional transistor based on a molybdenum disulfide (MoS2 )/perylene-3,4,9,10-tetracarboxylic dianhydride (PTCDA) hybrid heterojunction, with remarkable short-term plasticity (STP) long-term (LTP), reported. Owing to elaborate design energy structure, both robust electrical optical modulation are achieved through carriers transfer at interface heterostructure, which still challenging task this day. In modulation, inhibition excitation can be simultaneously in same device by gate voltage tuning. Notably, minimum 3% maximum facilitation 500% obtained increasing number, response different frequency signals indicates dynamic filtering characteristic. It exhibits flexible tunability STP LTP weight changes up 60, far superior previous work modulation. The fully MoS2 /PTCDA heterojunction synapse opens whole new path urgent need computation devices.

Язык: Английский

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Flexible Neuromorphic Electronics for Computing, Soft Robotics, and Neuroprosthetics

Advanced Materials, Год журнала: 2019, Номер 32(15)

Опубликована: Сен. 26, 2019

Flexible neuromorphic electronics that emulate biological neuronal systems constitute a promising candidate for next-generation wearable computing, soft robotics, and neuroprosthetics. For realization, with the achievement of simple synaptic behaviors in single device, construction artificial synapses various functions sensing responding integrated to mimic complicated sensing, is prerequisite. Artificial have learning ability can perceive react events real world; these abilities expand applications toward health monitoring cybernetic devices future Internet Things. To demonstrate flexible successfully, it essential develop nerves replicating functionalities counterparts satisfying requirements constructing elements such as flexibility, low power consumption, high-density integration, biocompatibility. Here, progress addressed, from basic backgrounds including characteristics, device structures, mechanisms nerves, Finally, research directions are suggested this emerging area.

Язык: Английский

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Disulfide Bond-Driven Oxidation- and Reduction-Responsive Prodrug Nanoassemblies for Cancer Therapy

Nano Letters, Год журнала: 2018, Номер 18(6), С. 3643 - 3650

Опубликована: Май 4, 2018

Disulfide bonds have been widely used to develop reduction-responsive drug-delivery systems (DDS) for cancer therapy. We propose that disulfide might be also as an oxidation-responsive linkage just like thioether bonds, which can oxidized hydrophilic sulfoxide or sulphone in the presence of oxidation stimuli. To test our hypothesis, we design three novel paclitaxel–citronellol conjugates linked via different lengths disulfide-bond-containing carbon chain. The prodrugs self-assemble into uniform-size nanoparticles with impressively high drug loading (>55%). As expected, disulfide-bond-bridged prodrug show redox dual-responsive release. More interestingly, position chain has profound impacts on dual responsiveness, thereby affecting release, cytotoxicity, pharmacokinetics, biodistribution, and vivo antitumor efficacy nanoassemblies. mechanism is elucidated, how affects responsiveness efficiency nanoassemblies clarified. Our findings give new insight stimuli provide a good foundation development DDS

Язык: Английский

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The Future of Memristors: Materials Engineering and Neural Networks

Advanced Functional Materials, Год журнала: 2020, Номер 31(8)

Опубликована: Ноя. 13, 2020

Abstract From Deep Blue to AlphaGo, artificial intelligence and machine learning are booming, neural networks have become the hot research direction. However, due size limit of complementary metal–oxide–semiconductor (CMOS) transistors, von Neumann‐based computing systems facing multiple challenges (such as memory walls). As number transistors required by network increases, development based on Neumann computer is limited volume energy consumption. fourth basic circuit element, memristor shines in field neuromorphic computing. The new architecture widely considered a substitute for has great potential deal with big data era challenge. This article reviews existing materials structures memristors, neurophysiological simulations applications memristor‐based networks. feasibility advancement implementing using memristors discussed, difficulties that need be overcome at this stage put forward, their prospects faced also discussed.

Язык: Английский

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A flexible ultrasensitive optoelectronic sensor array for neuromorphic vision systems

Nature Communications, Год журнала: 2021, Номер 12(1)

Опубликована: Март 19, 2021

Abstract The challenges of developing neuromorphic vision systems inspired by the human eye come not only from how to recreate flexibility, sophistication, and adaptability animal systems, but also do so with computational efficiency elegance. Similar biological these circuits integrate functions image sensing, memory processing into device, process continuous analog brightness signal in real-time. High-integration, flexibility ultra-sensitivity are essential for practical artificial that attempt emulate processing. Here, we present a flexible optoelectronic sensor array 1024 pixels using combination carbon nanotubes perovskite quantum dots as active materials an efficient system. device has extraordinary sensitivity light responsivity 5.1 × 10 7 A/W specific detectivity 2 16 Jones, demonstrates reinforcement learning training weak pulse 1 μW/cm .

Язык: Английский

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Retina‐Inspired Carbon Nitride‐Based Photonic Synapses for Selective Detection of UV Light

Advanced Materials, Год журнала: 2020, Номер 32(11)

Опубликована: Янв. 27, 2020

Abstract Photonic synapses combine sensing and processing in a single device, so they are promising candidates to emulate visual perception of biological retina. However, photonic with wavelength selectivity, which is key property for perception, have not been developed far. Herein, organic that selectively detect UV rays process various optical stimuli presented. The use carbon nitride (C 3 N 4 ) as an UV‐responsive floating‐gate layer transistor geometry. C nanodots dominantly absorb light; this trait the basis selectivity these synapses. presented devices consume only 18.06 fJ per synaptic event, comparable energy consumption Furthermore, situ modulation exposure light demonstrated by integrating transmittance modulators. These smart systems can be further detection dose‐calculation determine how when decrease preventive health care.

Язык: Английский

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