Anomalous resistive switching in memristors based on two-dimensional palladium diselenide using heterophase grain boundaries

Li, Yesheng; Loh, Leyi; Li, Sifan; Chen, Li; Li, Bochang; Bosman, Michel; Ang, Kah‐Wee

doi:10.1038/s41928-021-00573-1

Cited by 146 publications

(155 citation statements)

References 31 publications

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“…2a, the critical current to activate RESET and SET is in the order of 10 and 1 µA at voltages of 1 and − 1 V, respectively. The consequent threshold switching powers of approximately 10 and 1 µW at RESET and SET process are both signi cantly lower than that in normal but non-optimized lamentary memristors based on 2D materials [7][8][9][10][11][12][13][14][15] and metal oxide [28]. In particular, our achievements almost match the worldwide record of 2D-CBRAM via palladium laments in WS 2 , exhibiting a RESET and a SET power of 0.14 and 0.06 µW, respectively [10], and phase-changed memristors via lithiated MoS 2 exhibiting several tens of µW and about 1 µW at RESET and SET, respectively [16][17].…”

Section: Resultsmentioning

confidence: 99%

“…Among them, heterojunctions between metal oxide and graphene, one of the most promising two-dimensional (2D) layered materials, provided a simpler opportunity [5] and inspired following developments of RRAM based on 2D materials, including insulating hexagonal boron nitride [6] and semiconducting transition metal dichalcogenide (TMD) [7][8][9][10][11][12][13][14][15][16][17]. However, most demonstrations of 2D-materials-based RRAM still relied on the CBRAM principle [6][7][8][9][10][11][12][13][14][15] and faced similar challenges, such as the trade-off between on/off ratio and power consumption as those based on metal oxides. Hence, alternative works focus on specialized features and superiorities of 2D materials in order to replace CBRAM are essential.…”

Section: Introductionmentioning

confidence: 99%

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Rational Design on Polymorphous Phase Switching in Molybdenum Diselenide-based Memristor Assisted by All-Solid-State Reversible Intercalation Toward Neuromorphic Application

Lee

Chiang

Shen

et al. 2022

Preprint

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Synaptic devices based on non-volatile resistive random access memory (RRAM) have inspired increasing opportunities, including in-memory computing and neural engines, while typical filamentary-based RRAM is subjected to large switching current and causes huge power consumptions. In this work, a low-power memristor based on vertically stacked two-dimensional (2D) layered materials, achieved by plasma-assisted vapor reaction, as the switching material, with which the copper and gold metals as electrodes featured by reversible polymorphous phase changes from a conducting 1T-phase to a semiconducting 2H-one once copper cations interacted between vertical lamellar layers and vice versa was demonstrated. Here, molybdenum diselenide (MoSe2) was chosen as the switching material and the reversible polymorphous phase changes activated by the intercalation of Cu cations were confirmed by pseudo-operando Raman scattering, transmission electron microscopy and scanning photoelectron microscopy under high and low resistance states, respectively. The switching can be activated at about ± 1 V with critical currents less than 10 𝜇A with an on/off ratio of approaching 100 after 100 cycles and low power consumption of ~0.1 microwatt as well as linear weight updates controlled by the amount of intercalation. The work opens alternative feasibility of reversible and all-solid-state metal interactions, which benefits monolithic integrations of 2D materials into operative electronic circuits.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Rational Design on Polymorphous Phase Switching in Molybdenum Diselenide-based Memristor Assisted by All-Solid-State Reversible Intercalation Toward Neuromorphic Application

Lee

Chiang

Shen

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The retention of 2DM synapses is more frequently demonstrated compared to the variability. However, the reported retention properties are usually obtained from the DC-cycled high resistance and low resistance states that possess a much larger conductance change than those used in synaptic operations [76,80,111]. Analyzing the retention properties obtained by AC pulses is preferable.…”

Section: Reliability and Variability Propertiesmentioning

confidence: 99%

Two-dimensional materials for artificial synapses: toward a practical application

Wang

Chang

Chen

et al. 2022

Neuromorph. Comput. Eng.

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Combining the emerging two-dimensional materials (2DMs) and neuromorphic computing, 2DM-based synaptic devices (2DM synapse) are highly anticipated research topics with the promise of revolutionizing the present Si-based computing paradigm. Although the development is still in the early stage, the number of 2DM synapses reported is increased exponentially in the past few years. Nevertheless, most of them mainly focus on device-level synaptic emulations, and a practical perspective toward system-level applications is still lacking. In this review article, we discuss several important types of 2DM synapses for neuromorphic computing. Based on the cross-layer device-circuit-algorithm co-optimization strategy, non-ideal properties in 2DM synapses are considered for accelerating deep neural networks, and their impacts on system-level accuracy, power, and area are discussed. Finally, a development guideline of 2DM synapses is provided toward accurate online training and inference in the future.

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“…In recent years, two-dimensional (2D) materials have attracted tremendous research interest due to their unique intrinsic properties, such as the atomic structures, complementary metal-oxide-semiconductor (CMOS) compatibility, and superior electronic and optoelectronic properties [18][19][20][21][22]. Leveraging on these merits, high-performance artificial synapses based on 2D materials have been intensively developed [23][24][25][26][27][28]. In particular, they have been widely employed as active materials in diode-type artificial synapses via various mechanisms, such as the formation of filaments, the transformation of phases, vacancy migration, charge trapping, etc [29][30][31].…”

Section: Introductionmentioning

confidence: 99%

Ferroelectric memory based on two-dimensional materials for neuromorphic computing

Chen

Pam

et al. 2022

Neuromorph. Comput. Eng.

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Ferroelectric memory devices with fast-switching speed and ultra-low power consumption have been recognized as promising building blocks for brain-like neuromorphic computing. In particular, ferroelectric memories based on 2D materials are attracting increasing research interests in recent years due to their unique properties that are unattainable in conventional materials. Specifically, the atomically thin 2D materials with tunable electronic properties coupled with the high compatibility with existing complementary metal-oxide-semiconductor (CMOS) technology manifests their potential for extending state-of-the-art ferroelectric memory technology into atomic-thin scale. Besides, the discovery of 2D materials with ferroelectricity shows the potential to realize functional devices with novel structures. This review highlights the recent progress in ferroelectric memory devices based on 2D materials for neuromorphic computing. The merits of such devices and the range of 2D ferroelectrics being explored to-date are reviewed and discussed, which include two- and three-terminal ferroelectric synaptic devices based on 2D materials platform. Finally, current developments and remaining challenges in achieving high-performance 2D ferroelectric synapses are discussed.

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Anomalous resistive switching in memristors based on two-dimensional palladium diselenide using heterophase grain boundaries

Cited by 146 publications

References 31 publications

Rational Design on Polymorphous Phase Switching in Molybdenum Diselenide-based Memristor Assisted by All-Solid-State Reversible Intercalation Toward Neuromorphic Application

Rational Design on Polymorphous Phase Switching in Molybdenum Diselenide-based Memristor Assisted by All-Solid-State Reversible Intercalation Toward Neuromorphic Application

Two-dimensional materials for artificial synapses: toward a practical application

Ferroelectric memory based on two-dimensional materials for neuromorphic computing

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