Two-Terminal Structured Synaptic Device Using Ionic Electrochemical Reaction Mechanism for Neuromorphic System

Lee, Chuljun; Lee, Jaewon; Kim, Myung-Jun; Woo, Jiyong; Koo, Sang‐Mo; Oh, Jong‐Min; Lee, Daeseok

doi:10.1109/led.2019.2897777

Cited by 38 publications

(36 citation statements)

References 27 publications

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“…A synapse is a gap between axons (presynaptic; see Figure a) and dendrites (postsynaptic). [ 34 ] A two‐terminal Au/APP/ITO sandwich‐like device (Figure 1b,c) was fabricated [ 35 ] and employed to simulate synapses (detailed procedure shown in Figure S1, Supporting Information). In brief, APP powder consists of polyphosphate main chains and a lateral group of ammonia ions (Figure 1c).…”

Section: Resultsmentioning

confidence: 99%

All‐Inorganic Ionic Polymer‐Based Memristor for High‐Performance and Flexible Artificial Synapse

Zhao

Sun

Wang

et al. 2020

Adv Funct Materials

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The implementation of memristors that are wearable and transparent has attracted significant attention. However, the development of high-performance memristors that simultaneously possess high flexibility and environmental stability has remained a tremendous challenge suffering from limited choice of materials with both good ion-electron mobility and structural flexibility. Inspired by the unique poly-ionic nature of ammonium polyphosphate (APP), a novel Au/APP/ITO memristor with favorable flexibility and stability is prepared. Synaptic behaviors can be stimulated by voltage pulses that are 20 ns in width, 0.1 V in amplitude, and repeatable under 10 4 pulse cycles, thereby outperforming several other benchmark memristors. Further, the device, prepared on conductive silicone, can sustain its synaptic performance even under 360° bending. Furthermore, the device can sustain its synaptic behaviors even after exposure to fire for 60 s and 5.6 kGy of ionic irradiation. Additionally, APP is determined to be nontoxic, biodegradable, and transparent when compared with all the organics and inorganics used in previous memristors. The results of this study will inspire the development of more inorganic polymers for their utilization in future environmentally stable and flexible electronics.

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Section: Resultsmentioning

confidence: 99%

All‐Inorganic Ionic Polymer‐Based Memristor for High‐Performance and Flexible Artificial Synapse

Zhao

Sun

Wang

et al. 2020

Adv Funct Materials

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“…With the development of memristor research for about half a century, RRAM devices received considerable attention as the most typical memristor. Apart from research on device performance, recent research was directed toward the study of materials with resistive switching (RS) function, such as binary transition metal oxides (TiO x , AlO x , and NiO x ) [3,[107][108][109][110][111], perovskite compounds (CH 3 NH 3 PbI 3 and CsPbBr 3 ) [54,55,112], ferromagnetic materials [112,113], biological materials [114,115], and graphene-based materials (graphene and GO) [30,116].…”

Section: Memristormentioning

confidence: 99%

“…Stop voltages of the set and reset process are defined as V SET and V RESET . In general, two different switching types are defined as unipolar and bipolar [3,[107][108][109][110][111], as illustrated in Figure 2. The unipolar switching mode is defined by the amplitude of the applied voltage bias, while the bipolar switching depends on the polarity of the applied voltage bias.…”

Section: Rram Device Characteristicsmentioning

confidence: 99%

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Memristive Non-Volatile Memory Based on Graphene Materials

Shen

Zhao

et al. 2020

Micromachines

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Resistive random access memory (RRAM), which is considered as one of the most promising next-generation non-volatile memory (NVM) devices and a representative of memristor technologies, demonstrated great potential in acting as an artificial synapse in the industry of neuromorphic systems and artificial intelligence (AI), due its advantages such as fast operation speed, low power consumption, and high device density. Graphene and related materials (GRMs), especially graphene oxide (GO), acting as active materials for RRAM devices, are considered as a promising alternative to other materials including metal oxides and perovskite materials. Herein, an overview of GRM-based RRAM devices is provided, with discussion about the properties of GRMs, main operation mechanisms for resistive switching (RS) behavior, figure of merit (FoM) summary, and prospect extension of GRM-based RRAM devices. With excellent physical and chemical advantages like intrinsic Young’s modulus (1.0 TPa), good tensile strength (130 GPa), excellent carrier mobility (2.0 × 105 cm2∙V−1∙s−1), and high thermal (5000 Wm−1∙K−1) and superior electrical conductivity (1.0 × 106 S∙m−1), GRMs can act as electrodes and resistive switching media in RRAM devices. In addition, the GRM-based interface between electrode and dielectric can have an effect on atomic diffusion limitation in dielectric and surface effect suppression. Immense amounts of concrete research indicate that GRMs might play a significant role in promoting the large-scale commercialization possibility of RRAM devices.

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“…However, an inevitable bottleneck of the von Neumann architecture due to the data transfer between processing and memory elements has become a major factor causing significant latency and power consumption [2]. Neuromorphic system is a potential candidate for beyond von Neumann computing era to solve this issue by mimicking a massively parallel processing of biological nervous systems and has recently gained interest by demonstrating cognitive functions including pattern recognition [3][4][5][6][7][8][9][10][11][12][13]. Since synaptic devices play a key role of not only storing information but also constructing neural network and transferring signals, various kinds of artificial synaptic devices have been investigated and demonstrated including memristors and transistors [14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Digital and Analog Switching Characteristics of InGaZnO Memristor Depending on Top Electrode Material for Neuromorphic System

et al. 2020

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In this study, we demonstrate both of digital and analog memory operations in InGaZnO (IGZO) memristor devices by controlling the electrode materials for neuromorphic application. The switching properties of the devices are determined by the initial energy barrier characteristics between the metal electrodes and the IGZO switching layer. Digital switching characteristics are obtained after the forming process when Schottky junction occurs at both of top and bottom electrodes. On the other hands, analog resistive switching is achieved when Schottky and Ohmic junctions exist at each side because the applied voltage modulates the Schottky barrier height through the Ohmic contact. In addition, the weightupdate properties of the devices are verified depending on identical and incremental pulse schemes. The incremental pulse trains improve the linearity and variation of weight modulation, leading to the stable learning characteristics of neuromorphic system in terms of pattern recognition with MNIST handwritten digit images.

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Two-Terminal Structured Synaptic Device Using Ionic Electrochemical Reaction Mechanism for Neuromorphic System

Cited by 38 publications

References 27 publications

All‐Inorganic Ionic Polymer‐Based Memristor for High‐Performance and Flexible Artificial Synapse

All‐Inorganic Ionic Polymer‐Based Memristor for High‐Performance and Flexible Artificial Synapse

Memristive Non-Volatile Memory Based on Graphene Materials

Digital and Analog Switching Characteristics of InGaZnO Memristor Depending on Top Electrode Material for Neuromorphic System

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