Polymer Analog Memristive Synapse with Atomic-Scale Conductive Filament for Flexible Neuromorphic Computing System

Jang, Byung Chul; Kim, Sungkyu; Yang, Sang Yoon; Park, Jihun; Hwe, Jun; Oh, Jungyeop; Choi, Junhwan; Im, Sung Gap; Dravid, Vinayak P.; Choi, Sung‐Yool

doi:10.1021/acs.nanolett.8b04023

Cited by 159 publications

(156 citation statements)

References 64 publications

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“…When a device changes its resistance from high to low, it is usually known as “set”; the reverse change is known as “reset”. The QC effect is suitable to realize multiple levels in devices and has been studied in both electrochemical metallization type and valance change memory type gap‐less RRAM. In most cases, switching is the after‐effect of a stress dependent virginity breakdown, which can consolidate the CF for switching operations.…”

Section: Introductionmentioning

confidence: 99%

“…[6] Electronic switches with atomicsized functional building blocks are the main driving force of modern nanotechnology. The QC effect is suitable to realize multiple levels in devices and has been studied in both electrochemical metallization type [9][10][11][12][13][14] and valance change memory type [15,16] gap-less RRAM. Nevertheless, the origin of atomic contact in nanoscale architectures is being investigated.…”

mentioning

confidence: 99%

“…The design of atomic dimensional memory devices is limited by the lithographic bottleneck. [9][10][11][12][13][14] In another approach, single-atom memory has been proposed for mechanically controllable break junctions (MCBJs), [17] which are a kind of electronic device formed by two knife-edged metal wires placed with a nanometer sized gap, as shown in Figure 1a. [7] The conductive bridge RAM device with quantized conductance (QC) effect proposed by Terebe et al, [8] was based on the fabrication of a gap-type Pt/ nano-gap/Ag 2 S/Ag structure.…”

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confidence: 99%

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Quantized Conduction Device with 6‐Bit Storage Based on Electrically Controllable Break Junctions

Banerjee

Hwang

2019

Adv Elect Materials

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electron charge and h is the Planck constant. [6] Electronic switches with atomicsized functional building blocks are the main driving force of modern nanotechnology. The design of atomic dimensional memory devices is limited by the lithographic bottleneck. Nevertheless, the origin of atomic contact in nanoscale architectures is being investigated. [7] The conductive bridge RAM device with quantized conductance (QC) effect proposed by Terebe et al., [8] was based on the fabrication of a gap-type Pt/ nano-gap/Ag 2 S/Ag structure. A small operating voltage of ±600 mV can switch the device between the "OFF" and "ON" states. When a device changes its resistance from high to low, it is usually known as "set"; the reverse change is known as "reset". The QC effect is suitable to realize multiple levels in devices and has been studied in both electrochemical metallization type [9][10][11][12][13][14] and valance change memory type [15,16] gap-less RRAM. In most cases, switching is the after-effect of a stress dependent virginity breakdown, which can consolidate the CF for switching operations. Because the behavior of the CF of conductive bridge RAM is considered to be an example of atomic-switching, further discussion is mainly focused on conductive bridge RAM type devices. Higher initial stress injects more cations into the switching oxide layer that results in poor control over the reset process, resulting in abrupt state transition, and atomic conductance instability. [9][10][11][12][13][14] In another approach, single-atom memory has been proposed for mechanically controllable break junctions (MCBJs), [17] which are a kind of electronic device formed by two knife-edged metal wires placed with a nanometer sized gap, as shown in Figure 1a. MCBJs are well known as atomic or single molecular junction, and have even been investigated to in the context of control of quantum interferences in graphene. [18,19] In an MCBJ, when the two wires are curved, broadening the gap, the contact is broken, and the reverse order experiences an atomic-contact at the break junction. Break junctions are a possible approach to the fabrication of atomic switches. However, in reality, for an electronic device, such design is burdensome due to exorbitant lithographic processes. It is possible to prepare a break junction by electrically controlling the ion migration process in conductive bridge RAM devices, as the switching mechanism is driven by the formation of metallic wire like CF. Although the concept of QC in conductive bridge RAM has been investigated for over a decade, precise and reliable atomic-level control Atomic-level control of conductance in a Cu/Ti/HfO 2 /TiN-based electrically controllable break junction (ECBJ) is demonstrated. The ECBJ is designed through sophisticated stack engineering and refined electrical operation. Control over bias-induced ion migration is the key to forming the ECBJ. Precise atomic-level control is accomplished with an optimized high temperature forming (OHTF) scheme. OHTF-controlled single-atomic switch...

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Quantized Conduction Device with 6‐Bit Storage Based on Electrically Controllable Break Junctions

Banerjee

Hwang

2019

Adv Elect Materials

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“…Two‐terminal memristors with multiple intermediate conductance states are qualified synaptic devices that can resemble the brain synapse structure and perform a variety of synaptic plasticity tasks . Various types of memristors, for example, conductive filament memories, phase change memories (PCMs), resistive switching memories based on ion migration, and ferroelectric tunnel junctions (FTJs), have been proposed for achieving high performance such as nonvolatility, a gradual resistance change, a threshold feature, a simple structure, and energy efficiency . Among these devices, a promising candidate for mimicking artificial synaptic devices and performing neural network operations is FTJ, which is an ultrathin ferroelectric film sandwiched by two electrodes whose resistance depends on the polarization direction (Figure b) .…”

mentioning

confidence: 99%

Reproducible Ultrathin Ferroelectric Domain Switching for High‐Performance Neuromorphic Computing

et al. 2019

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Neuromorphic computing consisting of artificial synapses and neural network algorithms provides a promising approach for overcoming the inherent limitations of current computing architecture. Developments in electronic devices that can accurately mimic the synaptic plasticity of biological synapses, have promoted the research boom of neuromorphic computing. It is reported that robust ferroelectric tunnel junctions can be employed to design high‐performance electronic synapses. These devices show an excellent memristor function with many reproducible states (≈200) through gradual ferroelectric domain switching. Both short‐ and long‐term plasticity can be emulated by finely tuning the applied pulse parameters in the electronic synapse. The analog conductance switching exhibits high linearity and symmetry with small switching variations. A simulated artificial neural network with supervised learning built from these synaptic devices exhibited high classification accuracy (96.4%) for the Mixed National Institute of Standards and Technology (MNIST) handwritten recognition data set.

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“…It proves this cross-linked wool keratin based device possesses good elastic properties, high toughness, and excellent stability. [55] With the enhanced mechanical flexibility, this memristor can be used in 3D neuromorphic www.afm-journal.de www.advancedsciencenews.com…”

Section: (8 Of 11)mentioning

confidence: 99%

Flexible and Insoluble Artificial Synapses Based on Chemical Cross‐Linked Wool Keratin

Chen

Lan

Wang

et al. 2020

Adv Funct Materials

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Designing suitable material systems to construct artificial synapses and exploring novel synaptic functions is a crucial step toward the realization of efficient large-scale bioinspired neuromorphic systems. In this work, flexible and insoluble bio-memristor devices are fabricated by precisely engineering the molecular structures of wool keratin. This flexible Ag/ keratin/indium tin oxide-polyethylene naphthalate synaptic device possesses enhanced mechanical resistance, which is achieved by photocross-linking keratin molecules, and can withstand a bending radius of up to 1.2 mm. This device is promising for implantable applications because it is water-resistant. When modulated by triangle-wave DC voltages and pulsed voltages, this flexible electronic device emulates typical memristor characteristics and synaptic functions, including potentiation/depression, spike timing dependent plasticity, and long-term/short-term plasticity. Simulation results indicate that a memristor network made by this woolkeratin based device has ≈95.8% memory learning accuracy and capability for pattern learning. Combined, these features prove that the cross-linked wool-keratin based device has potential in wearable and flexible neuron computing systems.

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Polymer Analog Memristive Synapse with Atomic-Scale Conductive Filament for Flexible Neuromorphic Computing System

Cited by 159 publications

References 64 publications

Quantized Conduction Device with 6‐Bit Storage Based on Electrically Controllable Break Junctions

Quantized Conduction Device with 6‐Bit Storage Based on Electrically Controllable Break Junctions

Reproducible Ultrathin Ferroelectric Domain Switching for High‐Performance Neuromorphic Computing

Flexible and Insoluble Artificial Synapses Based on Chemical Cross‐Linked Wool Keratin

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