Controlling the Formation of Conductive Pathways in Memristive Devices

Eilhardt, Robert; Zintler, Alexander; Petzold, Stephan; Piros, Eszter; Kaiser, Nico; Vogel, Tobias; Nasiou, Déspina; McKenna, Keith P.; Molina‐Luna, Leopoldo; Alff, Lambert

doi:10.1002/advs.202201806

Cited by 9 publications

(10 citation statements)

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“…The gradual sharpening of the peak could be due to the migration of oxygen vacancies to the grain boundary during recovery stress. [23] In addition to including the recovered domains that were fixed during fatigue, the switching domains also include wake-up domains that did not work under fatigued stress from the beginning. If further recovery stress cycles are applied, domain pinning or dielectric breakdown may occur owing to the stronger stress.…”

Section: Resultsmentioning

confidence: 99%

Investigation of Recovery Phenomena in Hf_0.5Zr_0.5O₂-Based 1T1C FeRAM

Okuno¹,

Yonai²,

Kunihiro³

et al. 2023

IEEE J. Electron Devices Soc.

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We have previously studied fatigue and its recovery phenomenon on 64 kbits hafnium-based one-transistor and onecapacitor (1T1C) ferroelectric random-access memory (FeRAM) with PVD-TiN (30 nm)/ALD-Hf0.5Zr0.5O2 (8 nm)/CVD-TiN (50 nm) capacitors. In this study, we characterized a single large capacitor fabricated using the same process as the 1T1C FeRAM to clearly understand the recovery mechanism and comprehensively qualify the recovery effect. The results reveal that the recovery effect is caused by domain depinning and new domains switching owing to a redistribution of oxygen vacancy. Furthermore, it is evident from recovery voltage and recovery pulse width dependence of the recovery effect that the recovery voltage can be reduced by applying a longer recovery pulse width. This enables a more flexible circuit design of 1T1C FeRAM when the recovery method is applied to enhance the cycling endurance.

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Section: Resultsmentioning

confidence: 99%

Investigation of Recovery Phenomena in Hf_0.5Zr_0.5O₂-Based 1T1C FeRAM

Okuno¹,

Yonai²,

Kunihiro³

et al. 2023

IEEE J. Electron Devices Soc.

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“…Therefore, this particular set of grain boundaries is an ideal precursor for the formation of a conductive filament. 33 The understanding and control of complex defects and their interaction is a key to manipulate conductive filament toward multiple resistive states. While HfO x is one of the mostly used materials in VCM, other materials like Y 2 O 3 with a high amount of intrinsic oxygen vacancies might be even more suited to control the transition between a large number of resistive states.…”

Section: Memristive Behaviors Of Various Materials and Devicesmentioning

confidence: 99%

“…It turns out that the symmetric grain boundary attracts to larger extent oxygen vacancies which, in turn, lead to a higher concentration of electronic states in the band gap of HfO 2 close to the Fermi level. Therefore, this particular set of grain boundaries is an ideal precursor for the formation of a conductive filament . The understanding and control of complex defects and their interaction is a key to manipulate conductive filament toward multiple resistive states.…”

Section: Memristive Behaviors Of Various Materials and Devicesmentioning

confidence: 99%

“…(c) Devices with (010) textured HfO 2 (pink) have an increased average forming voltage of V̅ f = −5.3 V compared to devices with (111̅) HfO 2 having V̅ f = −1.9 V as shown by the cumulative distribution function measured from 50 30 × 30 μm 2 devices. Reprinted with permission under a Creative Commons CC BY License from ref . Copyright 2022 John Wiley & Sons.…”

Section: Memristive Behaviors Of Various Materials and Devicesmentioning

confidence: 99%

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Recent Advances and Future Prospects for Memristive Materials, Devices, and Systems

et al. 2023

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Memristive technology has been rapidly emerging as a potential alternative to traditional CMOS technology, which is facing fundamental limitations in its development. Since oxide-based resistive switches were demonstrated as memristors in 2008, memristive devices have garnered significant attention due to their biomimetic memory properties, which promise to significantly improve power consumption in computing applications. Here, we provide a comprehensive overview of recent advances in memristive technology, including memristive devices, theory, algorithms, architectures, and systems. In addition, we discuss research directions for various applications of memristive technology including hardware accelerators for artificial intelligence, in-sensor computing, and probabilistic computing. Finally, we provide a forward-looking perspective on the future of memristive technology, outlining the challenges and opportunities for further research and innovation in this field. By providing an up-to-date overview of the state-of-the-art in memristive technology, this review aims to inform and inspire further research in this field.

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“…For example, in ref. [150], Winkler et al found that the orientation of the crystal structure in HfO 2 played a significant role in the forming voltage and the memristor's variability. They suggest that the grain boundaries within the HfO 2 control the energy and orientation required to form conductive filaments, and thus proposed controlling the grain boundaries in memristive devices for improved performance.…”

Section: Device Level Issuesmentioning

confidence: 99%

A Review of Graphene‐Based Memristive Neuromorphic Devices and Circuits

Walters

Jacob

Amirsoleimani

et al. 2023

Advanced Intelligent Systems

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As data processing volume increases, the limitations of traditional computers and the need for more efficient computing methods become evident. Neuromorphic computing mimics the brain's low‐power and high‐speed computations, making it crucial in the era of big data and artificial intelligence. One significant development in this field is the memristor, a device that exhibits neuromorphic tendencies. The performance of memristive devices and circuits relies on the materials used, with graphene being a promising candidate due to its unique properties. Researchers are investigating graphene‐based memristors for large‐scale, sustainable fabrication. Herein, progress in the development of graphene‐based memristive neuromorphic devices and circuits is highlighted. Graphene and its common fabrication methods are discussed. The fabrication and production of graphene‐based memristive devices are reviewed and comparisons are provided among graphene‐ and nongraphene‐based memristive devices. Next, a detailed synthesis of the devices utilizing graphene‐based memristors is provided to implement the basic building blocks of neuromorphic architectures, that is, synapses, and neurons. This is followed by reviewing studies building graphene memristive spiking neural networks (SNNs). Finally, insights on the prospects of graphene‐based neuromorphic memristive systems including their device‐ and network‐level challenges and opportunities are given.

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Controlling the Formation of Conductive Pathways in Memristive Devices

Abstract: including the URL of the record and the reason for the withdrawal request.

Cited by 9 publications

References 53 publications

Investigation of Recovery Phenomena in Hf_0.5Zr_0.5O₂-Based 1T1C FeRAM

Investigation of Recovery Phenomena in Hf_0.5Zr_0.5O₂-Based 1T1C FeRAM

Recent Advances and Future Prospects for Memristive Materials, Devices, and Systems

A Review of Graphene‐Based Memristive Neuromorphic Devices and Circuits

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Controlling the Formation of Conductive Pathways in Memristive Devices

Abstract: including the URL of the record and the reason for the withdrawal request.

Cited by 9 publications

References 53 publications

Investigation of Recovery Phenomena in Hf0.5Zr0.5O2-Based 1T1C FeRAM

Investigation of Recovery Phenomena in Hf0.5Zr0.5O2-Based 1T1C FeRAM

Recent Advances and Future Prospects for Memristive Materials, Devices, and Systems

A Review of Graphene‐Based Memristive Neuromorphic Devices and Circuits

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Product

Resources

About

Investigation of Recovery Phenomena in Hf_0.5Zr_0.5O₂-Based 1T1C FeRAM

Investigation of Recovery Phenomena in Hf_0.5Zr_0.5O₂-Based 1T1C FeRAM