Programmable Multilevel Memtransistors Based on van der Waals Heterostructures

Hyunik Park, Michael A. Mastro, Marko J. Tadjer, Jihyun Kim

    Research output: Contribution to journalArticlepeer-review

    26 Citations (Scopus)

    Abstract

    Neuromorphic computing that mimics the energy-efficient cortical neural network in the human brain is attractive because of its possibility to process complex and massive data sets and achieve fast computing capability. Herein, a heterosynaptic and programmable memtransistor architecture with high computing functionality is reported by monolithically integrating a hexagonal boron nitride (h-BN) memristor with a molybdenum disulfide (MoS2) transistor. Memristors consisting of a vertically stacked van der Waals materials (multilayer graphene (MLG) and h-BN) exhibit a stable bipolar resistive switching behavior with a memory window more than three orders of magnitude due to the formation and rupture of the metallic filament within the h-BN layer. By controlling the resistance state of the h-BN memristor, the behaviors of the memtransistor can be programmed with a high switching ratio of ≈104, showing ≈16 pW standby power consumption. A multistate computing window and tunable current on/off ratio can be achieved by controlling the synaptic weight of the memristor, demonstrating that the presented 2D architecture can be exploited as a logic inverter device. The results pave the way toward the development of highly functional neuromorphic systems for the next-generation in-memory computing.

    Original languageEnglish
    Article number1900333
    JournalAdvanced Electronic Materials
    Volume5
    Issue number10
    DOIs
    Publication statusPublished - 2019 Oct 1

    Bibliographical note

    Funding Information:
    The research at Korea University was supported by National Research Foundation of Korea funded by the Technology Development Program to Solve Climate Changes of the National Research Foundation funded by the Ministry of Science and ICT (2017M1A2A2087351) and the Korea Institute of Energy Technology Evaluation and Planning (KETEP), granted financial resource from the Ministry of Trade, Industry & Energy, Korea (20172010104830). The research at US Naval Research Laboratory was supported by the Office of Naval Research.

    Publisher Copyright:
    © 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

    Keywords

    • 2D materials
    • heterostructures
    • in-memory computing
    • memristors
    • memtransistors
    • neuromorphic

    ASJC Scopus subject areas

    • Electronic, Optical and Magnetic Materials

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