Physical simulation of Si-based resistive random-access memory devices

Sadi, Toufik; Wang, Liping; Gerrer, Louis; Asenov, A.

doi:10.1109/sispad.2015.7292340

Cited by 5 publications

(2 citation statements)

References 20 publications

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“…3. Two important aspects of the simulator need to be highlighted: (i) using a fundamental understanding of vacancy generation to extract important parameters such as activation energies and diffusion barriers (not used in our previous work [9], [10]), and (ii) integrating an advanced structure generator into the simulation framework, which allows the generation of a simulation structure of any arbitrary geometry and material profile. The structure editor is particularly useful when studying realistic SiO x RRAM structures incorporating siliconrich areas (defect rich areas or areas with Si nano-inclusions [2]) in the oxide, as is the case here.…”

Section: Simulation Methodsmentioning

confidence: 99%

Advanced physical modeling of SiO<inf>x</inf> resistive random access memories

Sadi

Wang

Gao

et al. 2016

2016 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)

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Abstract-We apply a three-dimensional (3D) physical simulator, coupling self-consistently stochastic kinetic Monte Carlo descriptions of ion and electron transport, to investigate switching in silicon-rich silica (SiO x ) redox-based resistive random-access memory (RRAM) devices. We explain the intrinsic nature of resistance switching of the SiO x layer, and demonstrate the impact of self-heating effects and the initial vacancy distributions on switching. We also highlight the necessity of using 3D physical modelling to predict correctly the switching behavior. The simulation framework is useful for exploring the little-known physics of SiO x RRAMs and RRAM devices in general. This proves useful in achieving efficient device and circuit designs, in terms of performance, variability and reliability.

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Section: Simulation Methodsmentioning

confidence: 99%

Advanced physical modeling of SiO<inf>x</inf> resistive random access memories

Sadi

Wang

Gao

et al. 2016

2016 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)

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“…This assumption has been tested by an extended version of the model presented in [8] towards the defect formation. The formation of point defects is included using the rate equation (1), see [15,16]. The simulation result changes then with a variable number of defects within the electrolyte, cf.…”

Section: Long Time Scale Investigationmentioning

confidence: 99%

An enhanced lumped element electrical model of a double barrier memristive device

Solan

Dirkmann

Hansen

et al. 2017

J. Phys. D: Appl. Phys.

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The massive parallel approach of neuromorphic circuits leads to effective methods for solving complex problems. It has turned out that resistive switching devices with a continuous resistance range are potential candidates for such applications. These devices are memristive systems -nonlinear resistors with memory. They are fabricated in nanotechnology and hence parameter spread during fabrication may aggravate reproducible analyses. This issue makes simulation models of memristive devices worthwhile.Kinetic Monte-Carlo simulations based on a distributed model of the device can be used to understand the underlying physical and chemical phenomena. However, such simulations are very time-consuming and neither convenient for investigations of whole circuits nor for real-time applications, e.g. emulation purposes. Instead, a concentrated model of the device can be used for both fast simulations and real-time applications, respectively. We introduce an enhanced electrical model of a valence change mechanism (VCM) based double barrier memristive device (DBMD) with a continuous resistance range. This device consists of an ultra-thin memristive layer sandwiched between a tunnel barrier and a Schottky-contact. The introduced model leads to very fast simulations by using usual circuit simulation tools while maintaining physically meaningful parameters.Kinetic Monte-Carlo simulations based on a distributed model and experimental data have been utilized as references to verify the concentrated model.

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Spinel ferrites for resistive random access memory applications

Gayakvad,

Somdatta,

Mathe

et al. 2023

emergent mater.

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Cutting edge science and technology needs high quality data storage devices for their applications in artificial intelligence and digital industries. Resistive random access memory (RRAM) is an emerging nonvolatile memory used for recording and reproducing the digital information. Earlier studies on RRAM applications suggest that spinel ferrite is a potential material. We envisage that the spinel ferrite prepared by a particular route, namely spin coating, will in future optimize the essential parameters for optimal functioning of RRAM. An assertion to our assumptions, few researchers have already obtained important findings for spin coated spinel ferrites. Spin coated spinel ferrites, namely zinc ferrite, nickel ferrite, cobalt ferrite and mixed spinel ferrites, have been investigated for their applications as switching layers in RRAM devices. Particularly, spin coated cobalt ferrite, nickel ferrite and doped nickel ferrite were widely used as resistive switching layers. However, it is noticed that there is a tremendous scope for synthesis and resistive switching characterization of spin coated pure and doped zinc ferrite. Proper doping of special element into spinel ferrite can enhance the resistive switching performance of RRAM devices. Insertion of nano structures and metal layers within switching layer uplifts the performance of spin coated spinel ferrite-based RRAM devices. Active layer in RRAM device synthesized by spin coating technique exhibited good resistive switching properties, namely retention of $$10^{3}$$ 10 3 to $$10^{5}$$ 10 5 s, endurance in the range of $$10^{2}$$ 10 2 to 22,500 cycles and memory window of $$10^{2}$$ 10 2 to $$10^{6}$$ 10 6 . This review article accounts for the optimized parameters obtained especially for the spinel ferrite-based active material synthesized by spin coating justifying the results with appropriate theory. A good co-relation between synthesis parameters and the RRAM functional parameter is separately discussed at the end of review article.

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Physical simulation of Si-based resistive random-access memory devices

Cited by 5 publications

References 20 publications

Advanced physical modeling of SiO<inf>x</inf> resistive random access memories

Advanced physical modeling of SiO<inf>x</inf> resistive random access memories

An enhanced lumped element electrical model of a double barrier memristive device

Spinel ferrites for resistive random access memory applications

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