Electrical bistabilities behaviour of all-solution-processed non-volatile memories based on graphene quantum dots embedded in graphene oxide layers

Jaafar, Muhammad Musoddiq; Ooi, Poh Choon; Wee, M. F. Mohd Razip; Haniff, Muhammad Aniq Shazni Mohammad; Mohamed, Mohd Ambri; Chang, Edward Yi; Majlis, Burhanuddin Yeop; Dee, Chang Fu

doi:10.1007/s10854-019-02015-3

Cited by 7 publications

(6 citation statements)

References 17 publications

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“…When a negative voltage is applied to the upper electrode (Al), electrons are injected into the composite film from the upper electrode and captured by traps. The top electrode provides an electron source to continuously inject electrons, and electrons can reach the bottom electrode through randomly distributed trap centers [ 35 , 36 ]. At this time, a conductive path is formed inside the device, and the current sharply increases.…”

Section: Resultsmentioning

confidence: 99%

Dual-Tunable Memristor Based on Carbon Nanotubes and Graphene Quantum Dots

et al. 2021

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Nanocarbon materials have the advantages of biocompatibility, thermal stability and chemical stability and have shown excellent electrical properties in electronic devices. In this study, Al/MWCNT:GQD/ITO memristors with rewritable nonvolatile properties were prepared based on composites consisting of multiwalled carbon nanotubes (MWCNTs) and graphene quantum dots (GQDs). The switching current ratio of such a device can be tuned in two ways. Due to the ultraviolet light sensitivity of GQDs, when the dielectric material is illuminated by ultraviolet light, the charge capture ability of the GQDs decreases with an increasing duration of illumination, and the switching current ratio of the device also decreases with an increasing illumination duration (103–10). By exploiting the charge capture characteristics of GQDs, the trap capture level can be increased by increasing the content of GQDs in the dielectric layer. The switching current ratio of the device increases with increasing GQD content (10–103). The device can be programmed and erased more than 100 times; the programmable switching state can withstand 105 read pulses, and the retention time is more than 104 s. This memristor has a simple structure, low power consumption, and enormous application potential for data storage, artificial intelligence, image processing, artificial neural networks, and other applications.

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Section: Resultsmentioning

confidence: 99%

Dual-Tunable Memristor Based on Carbon Nanotubes and Graphene Quantum Dots

et al. 2021

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“…GO can be dispersed in a variety of solvents, which permits compatible processes with a wide range of commercially available flexible substrates. With various technologies like spin coating [164][165][166], drop casting [167][168][169], dip coating [170][171][172], and inkjet printing [157,173,174], GO dielectric layers can be deposited onto flexible substrates like polyethylene terephthalate (PET), polyether sulfone (PES), and polyimide [175][176][177][178][179][180]. In addition, the thickness of a single atomic layer and the excellent dispersibility in various solvents result in GO having enhanced compatibility with different commercial substrates [181][182][183].…”

Section: Application Of Graphene-based Memristors In Flexible Electromentioning

confidence: 99%

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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“…As the concentration of OCQDs in the active layer increased, the resistance value of the highresistance state (R HRS ) and the threshold voltage of the device increased. 25 A device fabricated by dispersing GOQDs in a polyvinyl alcohol (PVA) matrix exhibited write-once-readmany-times (WORM) switching behavior with a low set voltage of 0.9 V. 26 As a biomaterial, soybean (SY) contains 20 different amino acids, including lysine, leucine, phenylalanine, tyrosine, aspartic acid and glutamic acid. 27 PMMA is a kind of high polymer organic polymer with high transparency, insulation, easy processing, good light conductivity and other advantages and is often used in the insulation layer of organic electronic devices.…”

Section: Introductionmentioning

confidence: 99%

“…As the concentration of OCQDs in the active layer increased, the resistance value of the high-resistance state ( R HRS ) and the threshold voltage of the device increased. 25 A device fabricated by dispersing GOQDs in a polyvinyl alcohol (PVA) matrix exhibited write-once-read-many-times (WORM) switching behavior with a low set voltage of 0.9 V. 26…”

Section: Introductionmentioning

confidence: 99%