Characterization of Oxygen Accumulation in Indium-Tin-Oxide for Resistance Random Access Memory

Zhang, Rui; Chang, Kuan‐Chang; Chang, Ting‐Chang; Tsai, Tsung‐Ming; Huang, Syuan-Yong; Chen, Wen-Jen; Chen, Kai-Huang; Lou, Jen‐Chung; Chen, Jung‐Hui; Young, Tai‐Fa; Chen, Min-Chen; Chen, Hsin-Lu; Liang, Shu-Ping; Syu, Yong-En; Sze, Simon M.

doi:10.1109/led.2014.2316806

Cited by 60 publications

(33 citation statements)

References 16 publications

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“…In addition, ITO possesses a tunable electrical characteristic where its conductivity can be modified from insulator to conductor by modulating its oxygen concentration through process conditions. According to our previous study, in which an ITO layer was used as the electrode of a RRAM device, the electrical characteristics (e.g., programing voltage, power consumption, and endurance) of RRAM can be improved by combining the metal doping layer and ITO electrode [31]- [35]. Because of the oxygen deficient properties of ITO, the corresponding influence of its high oxygen absorption ability during resistive switching process for ITO RRAM is worthy of investigation.…”

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confidence: 99%

Resistive Switching Mechanism of Oxygen-Rich Indium Tin Oxide Resistance Random Access Memory

Tsai

Chang

et al. 2016

IEEE Electron Device Lett.

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This letter investigates the double-ended resistive switching characteristics of indium tin oxide (ITO) resistance random access memory (RRAM). Resistive switching can be achieved around both the active TiN electrode and the inert Pt electrode. In addition, complementary resistance switching (CRS) characteristics can be observed without current compliance during dc voltage sweep operations. Electrical measurement data fitting results indicate that the oxygen-rich ITO near top and bottom electrodes works as a double-ended resistive switching layer. Based on the analysis of the current conduction mechanism, we propose a physical model to interpret the CRS behaviors in ITO RRAM devices.

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confidence: 99%

Resistive Switching Mechanism of Oxygen-Rich Indium Tin Oxide Resistance Random Access Memory

Tsai

Chang

et al. 2016

IEEE Electron Device Lett.

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“…A linear relationship between ln( I ) and ( V ) 1/2 indicates the Schottky emission conduction mechanism. The behavior is related to the energy barrier between the conducting filament and electrode . Thus, resistive switching model is proposed for the present bilayered memristor, as shown in Figure c.…”

Section: Resultsmentioning

confidence: 99%

Bilayered Oxide‐Based Cognitive Memristor with Brain‐Inspired Learning Activities

Xiong

Zhu

et al. 2019

Adv Elect Materials

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our brain would solve this dilemma, that is, the von Neumann bottleneck. Thus, neuromorphic engineering comes into being. Basically, data-driven neuromorphic engineering needs to complete a large number of data processing tasks. Presently, one of the main tasks in the state-ofthe-art neuromorphic computing system is to optimize neuromorphic algorithm. Due to the use of von Neumann architecture, such neuromorphic systems always consume extremely high energy. In fact, our brain nervous system is consisted of ≈10 11 neurons connected by ≈10 15 synapses. [3] Neurons and synapses are basic units in brain information processing. Brain cognitive behaviors occur through synaptic responses and neural functions. And the synaptic plasticity is the most important characteristics of synapse. Such architecture makes our brain operate in extremely high energy efficiency with certain fault tolerance to respond to our surroundings. Thus, brain-inspired neuromorphic devices have been proposed for mimicking biological synaptic responses and neural functions. [4][5][6] It is getting a new branch for neuromorphic engineering.Recently, with the developments of microelectronics, optoelectronics, and material technologies, solid-state neuromorphic devices have been proposed to mimic biological synaptic functions. Such devices include two-terminal resistance change memory devices [7][8][9][10] and field-effect transistor based neuromorphic transistors. [11][12][13][14][15] Due to the simple sandwich structure, two-terminal memristors have the inherent priority in 3D integrity. They have been widely investigated for high density storage applications. [16,17] With nonlinear electrical characteristics and nonvolatile resistance modulation effects, two-terminal memristors are very suitable for neuromorphic device applications. Such devices include ferroelectric random access memory (FeRAM), phase change random access memory (PCRAM), resistive random access memory (RRAM), etc. [18][19][20][21][22] In fact, most of the recent reported neuromorphic devices are based on two-terminal memristors. Especially with the deep understanding of the operation mechanisms of memristors, neural operation and typical Modified National Institute of Standards and Technology (MNIST) pattern recognition have also been demonstrated by using memristor arrays. [23][24][25] In addition, energy consumption is another important index in neuromorphic device applications. Recently, several works have been reported on neuromorphic device with low energy consumption. [26][27][28][29][30] Xu et al. [26] obtained organic nanowire synaptic transistors with energy consumption of ≈1.23 fJ per Recently, neuromorphic devices have attracted great attention due to their potential to overcome the von Neumann bottleneck. Due to their nonlinear electrical characteristics and nonvolatile resistance, memristors have been proposed for use in neuromorphic device applications. Bilayered HfO 2 /TiO x -based cognitive memristors are proposed. They demonstrate conductance-modulation capabilit...

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“…For reset process state, a gradual current decrease was presented in LRS to HRS for the bias to positive over the reset voltage. For inverted set/reset state properties of the Gd:SiO 2 RRAM devices, we suggested the transferred electron early captured by the lots of oxygen vacancy in top ITO electrode and formed the oppositely metallic filament [ 22 ]. The operation current of the Gd:SiO 2 RRAM devices for using SCF-treated ITO electrode was lower than that for the nontreated electrode of others.…”

Section: Resultsmentioning

confidence: 99%

Improvement of Bipolar Switching Properties of Gd:SiOx RRAM Devices on Indium Tin Oxide Electrode by Low-Temperature Supercritical CO2 Treatment

Chen

Chang

et al. 2016

Nanoscale Res Lett

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Bipolar switching resistance behaviors of the Gd:SiO2 resistive random access memory (RRAM) devices on indium tin oxide electrode by the low-temperature supercritical CO2-treated technology were investigated. For physical and electrical measurement results obtained, the improvement on oxygen qualities, properties of indium tin oxide electrode, and operation current of the Gd:SiO2 RRAM devices were also observed. In addition, the initial metallic filament-forming model analyses and conduction transferred mechanism in switching resistance properties of the RRAM devices were verified and explained. Finally, the electrical reliability and retention properties of the Gd:SiO2 RRAM devices for low-resistance state (LRS)/high-resistance state (HRS) in different switching cycles were also measured for applications in nonvolatile random memory devices.

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Characterization of Oxygen Accumulation in Indium-Tin-Oxide for Resistance Random Access Memory

Cited by 60 publications

References 16 publications

Resistive Switching Mechanism of Oxygen-Rich Indium Tin Oxide Resistance Random Access Memory

Resistive Switching Mechanism of Oxygen-Rich Indium Tin Oxide Resistance Random Access Memory

Bilayered Oxide‐Based Cognitive Memristor with Brain‐Inspired Learning Activities

Improvement of Bipolar Switching Properties of Gd:SiOx RRAM Devices on Indium Tin Oxide Electrode by Low-Temperature Supercritical CO2 Treatment

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