Synaptic behaviors in flexible Au/WO /Pt/mica memristor for neuromorphic computing system

Zhang, Li; Tang, Zhenhua; Yao, Dijie; Fan, Zhao-Yuan; Hu, Songcheng; Sun, Qijun; Tang, Xin‐Gui; Jin, Yanping; Guo, Xiaobin; Huang, Mingqiang; Zhong, Gaokuo; Gao, J.

doi:10.1016/j.mtphys.2022.100650

Cited by 25 publications

(14 citation statements)

References 46 publications

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“…The bending length (2R) was 10 mm (original length was 15 mm), and the thickness ( t ) was 0.008 mm (mica substrate and film included). The film's strain value was calculated as 0.0008 according to the formula: [ 50 ]

\begin{equation}\varepsilon = \frac{{\rm{t}}}{{2R}}\ \end{equation}

TiN and ITO are promising materials for next‐generation transparent conducting electrodes, [ 51 ] possessing high optical transparency at visible wavelengths. Accordingly, the assembled TiN/ClSA‐CDs/ITO/mica structure showed excellent optical transparency (Figure 5c).…”

Section: Resultsmentioning

confidence: 99%

Ligand‐Triggered Self‐Assembly of Flexible Carbon Dot Nanoribbons for Optoelectronic Memristor Devices and Neuromorphic Computing

Pei

Song

et al. 2023

Advanced Science

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Carbon dots (CDs) are widely utilized in sensing, energy storage, and catalysis due to their excellent optical, electrical and semiconducting properties. However, attempts to optimize their optoelectronic performance through high-order manipulation have met with little success to date. In this study, through efficient packing of individual CDs in two-dimensions, the synthesis of flexible CDs ribbons is demonstrated technically. Electron microscopies and molecular dynamics simulations, show the assembly of CDs into ribbons results from the tripartite balance of 𝝅-𝝅 attractions, hydrogen bonding, and halogen bonding forces provided by the superficial ligands. The obtained ribbons are flexible and show excellent stability against UV irradiation and heating. CDs ribbons offer outstanding performance as active layer material in transparent flexible memristors, with the developed devices providing excellent data storage, retention capabilities, and fast optoelectronic responses. A memristor device with a thickness of 8 µm shows good data retention capability even after 10 4 cycles of bending. Furthermore, the device functions effectively as a neuromorphic computing system with integrated storage and computation capabilities, with the response speed of the device being less than 5.5 ns. These properties create an optoelectronic memristor with rapid Chinese character learning capability. This work lays the foundation for wearable artificial intelligence.

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\begin{equation}\varepsilon = \frac{{\rm{t}}}{{2R}}\ \end{equation}

Section: Resultsmentioning

confidence: 99%

Ligand‐Triggered Self‐Assembly of Flexible Carbon Dot Nanoribbons for Optoelectronic Memristor Devices and Neuromorphic Computing

Pei

Song

et al. 2023

Advanced Science

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“…Synaptic plasticity, which is further divided into short-term plasticity (STP) and long-term plasticity (LTP), allows for efficient modification of the strength of connections between neurons under purposeful stimulation. In the past, scientists have investigated and created artificial synaptic devices having both STP and LTP functionalities, such as metal oxide semiconductors [ 42 ] chalcogenides [ 43 ], nanoscale two-terminal memristors, and three terminal synaptic transistors [ 44 , 45 ]. The physical mechanism of the artificial synaptic device can be attributed to the controlled movement of ions in response to electrical stimulation, which leads to additional nonlinear conductance changes accompanied by the activation of post-synaptic currents (PSC) [ 46 ].…”

Section: Introductionmentioning

confidence: 99%

Mimicking biological synapses with a-HfSiOx-based memristor: implications for artificial intelligence and memory applications

et al. 2023

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Memristors, owing to their uncomplicated structure and resemblance to biological synapses, are predicted to see increased usage in the domain of artificial intelligence. Additionally, to augment the capacity for multilayer data storage in high-density memory applications, meticulous regulation of quantized conduction with an extremely low transition energy is required. In this work, an a-HfSiOx-based memristor was grown through atomic layer deposition (ALD) and investigated for its electrical and biological properties for use in multilevel switching memory and neuromorphic computing systems. The crystal structure and chemical distribution of the HfSiOx/TaN layers were analyzed using X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS), respectively. The Pt/a-HfSiOx/TaN memristor was confirmed by transmission electron microscopy (TEM) and showed analog bipolar switching behavior with high endurance stability (1000 cycles), long data retention performance (104 s), and uniform voltage distribution. Its multilevel capability was demonstrated by restricting current compliance (CC) and stopping the reset voltage. The memristor exhibited synaptic properties, such as short-term plasticity, excitatory postsynaptic current (EPSC), spiking-rate-dependent plasticity (SRDP), post-tetanic potentiation (PTP), and paired-pulse facilitation (PPF). Furthermore, it demonstrated 94.6% pattern accuracy in neural network simulations. Thus, a-HfSiOx-based memristors have great potential for use in multilevel memory and neuromorphic computing systems. Graphical Abstract

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“…Optoelectronic neuromorphic computing based on optoelectronic devices can possibly combine the advantages and compensate for the shortcomings of both photonics and electronics . Memristors, as emerging neuromorphic devices with the ability of simulating the cognitive and memory behavior of biological synapses, are regarded as key elements for neuromorphic computing due to their unique advantages such as simple structures, low power consumption, and good compatibility with CMOS circuits. − In particular, some optoelectronic memristors based on photoelectric materials can have a response to both external electrical and optical stimuli, which provides a promising pathway for building optoelectronic neuromorphic computing systems. ,− …”

Section: Introductionmentioning

confidence: 99%

Light-Induced Conductance Potentiation and Depression in an All-Optically Controlled Memristor

Li,

Fang,

Guo

et al. 2024

ACS Appl. Mater. Interfaces

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Optoelectronic memristors are new multifunctional devices with both electrically tunable and light-tunable synaptic plasticity, attracting great attention as key promising devices for optoelectronic neuromorphic computing systems. At present, the conductance modulation in most optoelectronic memristors is conducted in a hybrid photoelectric mode, suffering some problems such as heat generation and control complexity. Here, an optoelectronic memristor based on the p+-Si/n-ZnO heterojunction is proposed where the conductance can be reversibly modulated in an all-optically controlled mode. The electron detrapping/trapping mechanism at the p+-Si/n-ZnO interface barrier region is presented to explain the light-induced conductance potentiation/depression behavior. Furthermore, some synaptic functions, including excitatory postsynaptic current (EPSC), inhibitory postsynaptic current (IPSC), and paired-pulse facilitation (PPF), are successfully mimicked in the p+-Si/n-ZnO heterojunction memristor, instructing its application potential for optoelectronic neuromorphic computing.

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Synaptic behaviors in flexible Au/WO /Pt/mica memristor for neuromorphic computing system

Cited by 25 publications

References 46 publications

Ligand‐Triggered Self‐Assembly of Flexible Carbon Dot Nanoribbons for Optoelectronic Memristor Devices and Neuromorphic Computing

Ligand‐Triggered Self‐Assembly of Flexible Carbon Dot Nanoribbons for Optoelectronic Memristor Devices and Neuromorphic Computing

Mimicking biological synapses with a-HfSiOx-based memristor: implications for artificial intelligence and memory applications

Light-Induced Conductance Potentiation and Depression in an All-Optically Controlled Memristor

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