Identification and application of current compliance failure phenomenon in RRAM device

Gao, Bo; Chang, Wei-Yao; Sun, Bing; Zhang, H. W.; Liu, L. F.; Liu, X. Y.; Han, Runze; Wu, Tai Bor; Kang, Jinfeng

doi:10.1109/vtsa.2010.5488912

Cited by 9 publications

(6 citation statements)

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“…The function of the top and bottom MLG stacks is to reduce atomic species exchange between the h-BN and the adjacent Ti (top) and Au (bottom) electrodes. Despite graphene is an excellent impermeable barrier, atomic exchange through the local defects of the MLG sheets (mainly GBs in the CVD-grown sheet) is possible [58,59]. From an RRAM point of view, this reduces the number of CFs in the device, leading to lower cur rents and cycleto-cycle variability.…”

Section: Methodsmentioning

confidence: 99%

Model for multi-filamentary conduction in graphene/hexagonal-boron-nitride/graphene based resistive switching devices

et al. 2017

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Despite the enormous interest raised by graphene and related materials, recent global concern about their real usefulness in industry has raised, as there is a preoccupying lack of 2D materials based electronic devices in the market. Moreover, analytical tools capable of describing and predicting the behavior of the devices (which are necessary before facing mass production) are very scarce. In this work we synthesize a resistive random access memory (RRAM) using graphene/hexagonal-boronnitride/graphene (G/h-BN/G) van der Waals structures, and we develop a compact model that accurately describes its functioning. The devices were fabricated using scalable methods (i.e. CVD for material growth and shadow mask for electrode patterning), and they show reproducible resistive switching (RS). The measured characteristics during the forming, set and reset processes were fitted using the model developed. The model is based on the nonlinear Landauer approach for mesoscopic conductors, in this case atomic-sized filaments formed within the 2D materials system. Besides providing excellent overall fitting results (which have been corroborated in log-log, log-linear and linear-linear plots), the model is able to explain the dispersion of the data obtained from cycle-tocycle in terms of the particular features of the filamentary paths, mainly their confinement potential barrier height.

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Section: Methodsmentioning

confidence: 99%

Model for multi-filamentary conduction in graphene/hexagonal-boron-nitride/graphene based resistive switching devices

et al. 2017

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“…As result of reducing redundant CFs inside TMO layer, larger portion of trimmed cells are showing Type A, evidence to less CFs. Besides, as shown in Figure 13(b), sharply current drops during reset process are also obtained in trimmed cells after minimizing redundant tiny paths [46]- [48]. As further demonstrated timing required of first reset operations in Figure 13(c), faster reset speed is obtained after the reset trimming treatment.…”

Section: Reset Trimming Schemementioning

confidence: 64%

“…However, no switch in time constants and 2 N current states of Type C, shown in Figure 4(a) and (c), contradict with findings in presented studies. Data in Figure 6 show that gradual reset transitions in Type B and Type C can be fully explained by existence of multiple CFs instead of multiple traps [46]- [48]. Type C cell is believed that includes multiple CFs with interactive processes between the trap states, where Vo can capture/emission electron from/to more than one conductive path, leading to irregular LFNs.…”

Section: Reset Speed Variation In Bcrram Arraymentioning

confidence: 99%

Reset Variability in Backfilled Resistive Random Access Memory and Its Correlation to Low Frequency Noise in Read

Kao

Lin

King

2020

IEEE J. Electron Devices Soc.

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Fast and stable switching between states is one of the key factors for the success resistive random access memory (RRAM) development. In an array, wide reset efficiency variation in RRAM cells is found to link to the characteristics of its low frequency noise (LFN) in bit-cell current. Through Monte Carlo simulation on randomly placing conductive filaments (CF), LFN characteristics correspond to the densities of the CF in the RRAM film. Further correlations between LFN features and the reset efficiency are found. In addition, CF topography are found to change after long term cycling tests. A trimming process is proposed to minimize the impacts of stochastic CF generation, leading to increase reset speed.INDEX TERMS Variability, resistive random access memory, low frequency noise, Monte Carlo simulation, conductive filament.

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“…Most of these memory candidates exhibit bi-polar switching, i.e., the switching behaviour depends on the polarity of applied electric field or current, primarily because of some spatial asymmetry in the device or material structure [104]. Also, for many device candidates, the magnitude of the on-state resistance is determined by the compliance limit of the programming current [47], but there are exceptions to this as well [113]. Most devices in the RRAM family require a forming process, where a substantially different programming condition is first applied to an as-fabricated device, before it exhibits memory switching effects [215].…”

Section: Resistive Rammentioning

confidence: 99%

Phase Change Memory: From Devices to Systems

Qureshi

Gurumurthi

Rajendran³

2011

Synthesis Lectures on Computer Architecture

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Identification and application of current compliance failure phenomenon in RRAM device

Cited by 9 publications

References 0 publications

Model for multi-filamentary conduction in graphene/hexagonal-boron-nitride/graphene based resistive switching devices

Model for multi-filamentary conduction in graphene/hexagonal-boron-nitride/graphene based resistive switching devices

Reset Variability in Backfilled Resistive Random Access Memory and Its Correlation to Low Frequency Noise in Read

Phase Change Memory: From Devices to Systems

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