Multimodal Tuning of Synaptic Plasticity Using Persistent Luminescent Memitters

Bian, Hongyu; Qin, Xian; Wu, Yiming; Yi, Zhigao; Liu, Sirui; Wang, Yu; Brites, Carlos D. S.; Carlos, Luís D.; Liu, Xiaogang

doi:10.1002/adma.202101895

Cited by 42 publications

(35 citation statements)

References 49 publications

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“…Short-term synaptic plasticity contains facilitation, short-term depression (STD) and short-term potentiation (STP). [164][165][166][167][168] Paired-impulse facilitation (PPF) is one typical feature of short-term synaptic plasticity. PPF means that under the stimulation of a pair of pulses, the intensity of the second conductance response is greater than that of the first response, which is defined as PPF = (G2 − G1)/G1 × 100%, where G1 and G2 represent the Reproduced with permission.…”

Section: Artificial Synapsesmentioning

confidence: 99%

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

Ling

Zhang

et al. 2022

Adv Funct Materials

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

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Section: Artificial Synapsesmentioning

confidence: 99%

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

Ling

Zhang

et al. 2022

Adv Funct Materials

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“…Generally, the typical “learning‐experience” behavior usually includes three processes, that is, the learning, forgetting, and relearning processes. [ 56 ] Through the learning process, people can steadily improve their cognitive level. Then, over time without learning, people will gradually forget the remembered things (forgetting process).…”

Section: Resultsmentioning

confidence: 99%

High‐Performance Memristor Based on 2D Layered BiOI Nanosheet for Low‐Power Artificial Optoelectronic Synapses

Lei

Duan

Qin

et al. 2022

Adv Funct Materials

110

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Artificial optoelectronic synapses with both electrical and light‐induced synaptic behaviors have recently been studied for applications in neuromorphic computing and artificial vision systems. However, the combination of visual perception and high‐performance information processing capabilities still faces challenges. In this work, the authors demonstrate a memristor based on 2D bismuth oxyiodide (BiOI) nanosheets that can exhibit bipolar resistive switching (RS) performance as well as electrical and light‐induced synaptic plasticity eminently suitable for low‐power optoelectronic synapses. The fabricated memristor exhibits high‐performance RS behaviors with a high ON/OFF ratio up to 105, an ultralow SET voltage of ≈0.05 V which is one order of magnitude lower than that of most reported memristors based on 2D materials, and low power consumption. Furthermore, the memristor demonstrates not only electrical voltage‐driven long‐term potentiation, depression plasticity, and paired‐pulse facilitation, but also light‐induced short‐ and long‐term plasticity. Moreover, the photonic synapse can be used to simulate the “learning experience” behaviors of human brain. Consequently, not only the memristor based on BiOI nanosheets shows ultra‐low SET voltage and low‐power consumption, but also the optoelectronic synapse provides new material and strategy to construct low‐power retina‐like vision sensors with functions of perceiving and processing information.

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“…Then, the application of a negative voltage turned the switch off. In the voltage sweeping, the minimum current is observed at nonzero voltage, which is related to the uneven distribution of ions inside the polymer, as previously observed. ,, When using a pure PEO film without doping Li + salt, lower ionic conductivity due to the highly crystalline PEO chains could not allow the switching in a planar device having a gap of ∼1 μm, under the same test conditions (see Figures S1–3 in the Supporting Information).…”

Section: Results and Discussionmentioning

confidence: 99%

Resistive Switching Memristor: On the Direct Observation of Physical Nature of Parameter Variability

Wang

Xiao

Yang

et al. 2021

ACS Appl. Mater. Interfaces

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Ion-based memristive switching has attracted widespread attention from industries owing to its outstanding advantages in storage and neuromorphic computing. Major issues for achieving brain-inspired computation of highly functional memory in redox-based ion devices are relatively large variability in their operating parameters and limited cycling endurance. In some devices, volatile and nonvolatile operations often replace each other without changing operating conditions. To address these issues, it is important to observe directly what is happening in repeated operations. Herein, we use a planar device that enables direct capturing of microscopic behaviors in the nucleation and growth of metal whiskers under repeated switching to verify the microscopic origin of the large parameter variability. We report direct observations that reveal the physical origin for the large cycle-to-cycle and device-to-device variability in memristive switching, which was achieved using planar polymer atomic switches with a gap >1 μm. We find that the deposition location of metal atoms is closely related to the crystallinity of the ion transport layer (solid polymer electrolyte, SPE). The filament variability (shape, position, quantity, etc.) during different cycles and devices is indeed the main reason for the observed variability in the operating characteristics. The results shed unique light on the complexity of the operation of the ion device, that is, the evolution of the dielectric layer and metal filament must be considered.

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Multimodal Tuning of Synaptic Plasticity Using Persistent Luminescent Memitters

Cited by 42 publications

References 49 publications

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

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

High‐Performance Memristor Based on 2D Layered BiOI Nanosheet for Low‐Power Artificial Optoelectronic Synapses

Resistive Switching Memristor: On the Direct Observation of Physical Nature of Parameter Variability

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