Causes and consequences of the stochastic aspect of filamentary RRAM

Degraeve, R.; Fantini, A.; Raghavan, Nagarajan; Goux, L.; Clima, Sergiu; Govoreanu, B.; Belmonte, Attilio; Linten, Dimitri; Jurczak, M.

doi:10.1016/j.mee.2015.04.025

Cited by 112 publications

(66 citation statements)

References 15 publications

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“…RRAMs will be a key technology for future non-volatile memory circuits [1][2][3][4][5][6][7] . Applications of RS devices can also be found in the neuromorphic and hardware security circuit realms 5,8,9 .…”

Section: Introductionmentioning

confidence: 99%

“…Applications of RS devices can also be found in the neuromorphic and hardware security circuit realms 5,8,9 . A continuous growth of the publications linked to resistive memories in all the research facets has been driven by both industry and academia in the last few years due to the outstanding features of these devices in connection to their fast read/writing speed, low power consumption, good retention and endurance characteristics, and their CMOS technology compatibility 5,6,7,10,11 .…”

Section: Introductionmentioning

confidence: 99%

“…Filamentary conduction through CFs is the most common operation mechanism: it is based on the stochastic formation and destruction processes of ohmic conductive filaments that shunt the electrodes 1,2,5,6,7,11,12,13,14,15 . These processes are linked to localized high temperature regions (generated by Joule heating) in which thermally based mechanisms are triggered 11,16,17 .…”

Section: Introductionmentioning

confidence: 99%

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Thermal study of multilayer resistive random access memories based on HfO2 and Al2O3 oxides

Cazorla

Aldana

Maestro

et al. 2019

Journal of Vacuum Science &Amp; Technology B, Nanotechnology and Microelectronics: Materials, Processing, Measurement, and Phen

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An in-depth analysis including both simulation and experimental characterization of Resistive RAMs (RRAMs) with dielectric stacks composed of two layers of HfO2 and Al2O3 stacked in different order is presented. The simulator, that includes the electrodes in the simulation domain, solves the 3D heat equation and calculates the device current. The results are employed to analyze thermal effects in bilayer HfO2 and Al2O3-based RRAMs with electrodes of Ni and Si-n+ during resistive switching (RS) operation. According to our simulations and the experimental data, the narrow part of the conductive filaments (CF) is formed in the HfO2 layer in all the cases and, therefore, no important differences are found in terms of reset voltage if the oxide stack order is changed with respect to the electrodes. This result is attributed to the fact that the heat flux in the Al2O3 is higher than

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Thermal study of multilayer resistive random access memories based on HfO2 and Al2O3 oxides

Cazorla

Aldana

Maestro

et al. 2019

Journal of Vacuum Science &Amp; Technology B, Nanotechnology and Microelectronics: Materials, Processing, Measurement, and Phen

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“…We can consider the CF as a 1D parameter because the material resistivity is area independent. It is very important to note that in CF programmable devices, there exist a variability problem because not all filaments are equal or similar [5].…”

Section: One Dimensional Models For Resistive Switching Materialsmentioning

confidence: 99%

“…Ielmini et al showed, from experimental data, that necessary power for the setting process (P SET ) is directly proportional to R À0. 5 , which means that [4]:…”

Section: Thermochemical Oxygen Diffusion Modelmentioning

confidence: 99%

Physical Models for Resistive Switching Devices

Procel‐Moya¹

2018

Memristor and Memristive Neural Networks

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We present a classification and description of the principal resistive switching and transport mechanisms in chalcogonides materials. We classify the model according to how many material dimensions are involved in the resistive switching mechanism. In this way, we describe the phase change model (3D), the interface modulation model (2D) and models where the switching mechanism depends on the formation of a conduction filament (1D). Among the conduction filament models, we include the thermochemical oxygen diffusion mechanism, the oxidation/reduction mechanism and the quantum point effect.

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Versatile NbOx‐Based Volatile Memristor for Artificial Intelligent Applications

Ju,

Kim

2024

Adv Funct Materials

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To achieve cost‐effectiveness, researchers are exploring various memristors for their adaptation in neuromorphic computing. Recent studies have focused on developing versatile functioning singular memristors, such as those involved in on‐receptor computing, which integrates sensory functions into current neuromorphic computing paradigms. Additionally, adaptations like reservoir computing are being investigated for computing systems. In this study, a memristor composed of a stack of Ti/NbOx/Pt layers is fabricated to explore multifunctional behaviors within a single memristor. By applying bias toward the top Ti electrode, gradual current changes with volatile features are demonstrated, revealing an ion‐migration‐based nonfilamentary switching memristor. Leveraging this volatile functionality, an artificial nociceptor is first implemented, demonstrating key functions of biological nociceptors including thresholding, relaxation, no‐adaptation, and sensitization. Subsequently, synapse emulation akin to the biological brain is achieved through easy conductance potentiation and depression with diverse synapse functions, enabling the memristor to mimic learning activities with spike firing. Lastly, computational applications are explored by adapting edge computing and multi‐bit reservoir computing, expanding the memristor's applications across diverse fields with versatile behaviors.

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Causes and consequences of the stochastic aspect of filamentary RRAM

Cited by 112 publications

References 15 publications

Thermal study of multilayer resistive random access memories based on HfO2 and Al2O3 oxides

Thermal study of multilayer resistive random access memories based on HfO2 and Al2O3 oxides

Physical Models for Resistive Switching Devices

Versatile NbOx‐Based Volatile Memristor for Artificial Intelligent Applications

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