Tunneling electroresistance effect in a Pt/Hf0.5Zr0.5O2/Pt structure

Ambriz-Vargas, Fabian; Kolhatkar, Gitanjali; Thomas, Reji; Nouar, Rafik; Sarkissian, A.; Gómez-Yáñez, Carlos; Gauthier, Marc A.; Ruediger, Andréas

doi:10.1063/1.4977028

Cited by 118 publications

(72 citation statements)

References 24 publications

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“…In Figure e, the peaks of Ag 3d at bottom electrode are at 368.2 and 374.2 eV. These results are consistent with theoretical results . The XPS curves for Zr, Hf, and O are plotted in Figure S1 (Supporting Information).…”

Section: Resultssupporting

confidence: 87%

Graphene Oxide Quantum Dots Based Memristors with Progressive Conduction Tuning for Artificial Synaptic Learning

Yan

Zhang

Chen

et al. 2018

Adv Funct Materials

253

160

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Memristors as electronic artificial synapses have attracted increasing attention in neuromorphic computing. Emulation of both "learning" and "forgetting" processes requires a bidirectional progressive adjustment of memristor conductance, which is a challenge for cutting-edge artificial intelligence. In this work, a memristor device with a structure of Ag/Zr 0.5 Hf 0.5 O 2 :graphene oxide quantum dots/Ag is presented with the feature of bidirectional progressive conductance tuning. The conductance of proposed memristor is adjusted through voltage pulse number, amplitude, and width. A series of voltage pulses with an amplitude of 0.6 V and a width of 30 ns is enough to modulate conductance. The impacts of pulses with different parameters on conductance modulation are investigated, and the potential relationship between pulse amplitude and energy is revealed. Furthermore, it is proved that the pulse with low energy can realize the almost linear conductance regulation, which is beneficial to improve the accuracy of pattern recognition. The bidirectional progressive conduction modulation mimics various plastic synapses, such as spike-timing-dependent plasticity and paired-pulse facilitation. This progressive conduction tuning mechanism might be attributed to the coexistence of tunneling effect and extrinsic electrochemical metallization effect. This work provides one way for memristor to attain attractive features such as bidirectional tuning, low-power consumption, and fast speed switching that is in urgent demand for further evolution of neuromorphic chips.

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Section: Resultssupporting

confidence: 87%

Graphene Oxide Quantum Dots Based Memristors with Progressive Conduction Tuning for Artificial Synaptic Learning

Yan

Zhang

Chen

et al. 2018

Adv Funct Materials

253

160

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“…Recently, ER in tunnel junctions involving ferroelectric HfO 2 barriers have been reported . However, available data do not allow indisputably to conclude if the observed ER is directly governed by polarization‐related effects or it results from electric‐field induced charge motion as commonly observed in non‐ferroelectric HfO 2 barriers .…”

Section: Introductionmentioning

confidence: 99%

Unraveling Ferroelectric Polarization and Ionic Contributions to Electroresistance in Epitaxial Hf_0.5Zr_0.5O₂ Tunnel Junctions

Sulzbach

Estandía

Long

et al. 2019

Adv Elect Materials

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Tunnel devices based on ferroelectric Hf 0.5 Zr 0.5 O 2 (HZO) barriers hold great promises for emerging data storage and computing technologies. The resistance state of the device can be changed by a suitable writing voltage. However, the microscopic mechanisms leading to the resistance change are an intricate interplay between ferroelectric polarization controlled barrier properties and defect-related transport mechanisms. Here is shown the fundamental role of the microstructure of HZO films setting the balance between those contributions. The oxide film presents coherent or incoherent grain boundaries, associated to the existence of monoclinic and orthorhombic phases in HZO films, which are dictated by the mismatch with the substrates for epitaxial growth. These grain boundaries are the toggle that allows to obtain either large (up to ≈ 450 %) and fully reversible genuine polarization controlled electroresistance when only the orthorhombic phase is present or an irreversible and extremely large (≈ 10 3 -10 5 %) electroresistance when both phases coexist.are the resistances after polarizing the junction with writing voltages V W + or V W and R min (V W +,-) is the minimum resistance among these states. Accordingly, binary high (OFF) and low resistance (ON) states can be written in a ferroelectric memory cell and read by probing its resistance. It has also been shown that by performing minor polarization loops, ferroelectric tunnel devices can store information in different resistive states, mimicking the functioning of a memristive element. [4,5] This approach has been successfully achieved by using ferroelectric perovskites such as BaTiO 3 , [6][7][8][9] Pb(Zr 0.2

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“…An FeFET is another promising solution to achieve high linearity of the synapse weight update because the device conductance is modulated through a gate electrode that does not interfere with a current-conducting channel 12,13 . However, the implementation of FeFETs using conventional perovskite-type oxide materials finds difficulty in securing CMOS process compatibility 14,15 .…”

Section: Introductionmentioning

confidence: 99%

Enhanced analog synaptic behavior of SiNx/a-Si bilayer memristors through Ge implantation

Kim

Park

et al. 2020

NPG Asia Mater

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Conductive bridging random access memory (CBRAM) has been considered to be a promising emerging device for artificial synapses in neuromorphic computing systems. Good analog synaptic behaviors, such as linear and symmetric synapse updates, are desirable to provide high learning accuracy. Although numerous efforts have been made to develop analog CBRAM for years, the stochastic and abrupt formation of conductive filaments hinders its adoption. In this study, we propose a novel approach to enhance the synaptic behavior of a SiNx/a-Si bilayer memristor through Ge implantation. The SiNx and a-Si layers serve as switching and internal current limiting layers, respectively. Ge implantation induces structural defects in the bulk and surface regions of the a-Si layer, enabling spatially uniform Ag migration and nanocluster formation in the upper SiNx layer and increasing the conductance of the a-Si layer. As a result, the analog synaptic behavior of the SiNx/a-Si bilayer memristor, such as the nonlinearity, on/off ratio, and retention time, is remarkably improved. An artificial neural network simulation shows that the neuromorphic system with the implanted SiNx/a-Si memristor provides a 91.3% learning accuracy mainly due to the improved linearity.

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Tunneling electroresistance effect in a Pt/Hf0.5Zr0.5O2/Pt structure

Cited by 118 publications

References 24 publications

Graphene Oxide Quantum Dots Based Memristors with Progressive Conduction Tuning for Artificial Synaptic Learning

Graphene Oxide Quantum Dots Based Memristors with Progressive Conduction Tuning for Artificial Synaptic Learning

Unraveling Ferroelectric Polarization and Ionic Contributions to Electroresistance in Epitaxial Hf_0.5Zr_0.5O₂ Tunnel Junctions

Enhanced analog synaptic behavior of SiNx/a-Si bilayer memristors through Ge implantation

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Tunneling electroresistance effect in a Pt/Hf0.5Zr0.5O2/Pt structure

Cited by 118 publications

References 24 publications

Graphene Oxide Quantum Dots Based Memristors with Progressive Conduction Tuning for Artificial Synaptic Learning

Graphene Oxide Quantum Dots Based Memristors with Progressive Conduction Tuning for Artificial Synaptic Learning

Unraveling Ferroelectric Polarization and Ionic Contributions to Electroresistance in Epitaxial Hf0.5Zr0.5O2 Tunnel Junctions

Enhanced analog synaptic behavior of SiNx/a-Si bilayer memristors through Ge implantation

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Unraveling Ferroelectric Polarization and Ionic Contributions to Electroresistance in Epitaxial Hf_0.5Zr_0.5O₂ Tunnel Junctions