Advancement in Soft Iontronic Resistive Memory Devices and Their Application for Neuromorphic Computing

Muhammad Umair Khan, Jungmin Kim, Mahesh Y. Chougale, Rayyan Ali Shaukat, Qazi Muhammad Saqib, Swapnil R. Patil, Baker Mohammad, Jinho Bae

    Research output: Contribution to journalReview articlepeer-review

    22 Scopus citations

    Abstract

    The aqueous electrolyte can be a deformable and stretchable liquid material for iontronic resistive memory devices. An aqueous medium makes a device closer to the brain-like system with the movement of ions. This review paper proposes advances in liquid resistive memories and neuromorphic computing behavior to emulate electronic synapses. Primarily, the aqueous iontronic resistive memories can be used to study electrode and active layer materials and different device structures. Hence, herein, a timely and comprehensive study of these devices using ionic liquids, hydrogels, salt solutions, and soft electrodes to classify the device mechanism is presented. The filament formation is discussed in detail based on ion concentration polarization, electrode metallization, and movements of ions and charged molecules, which result in the formation of the metal dendrite. To manufacture a higher-performance memory, device parameters should be optimized based on aqueous electrolytes, electrode materials, and other device design parameters. Aqueous electrolytes have smooth neurotransmission ability to fabricate brain-inspired resistive memories with stable performance and device repeatability with smooth ion transmission. Aqueous electrode materials can be reliable for neural interface activities to compute electronic synapsis with electrical and chemical properties to ensure device reliability for a longer time period.

    Original languageBritish English
    Article number2200281
    JournalAdvanced Intelligent Systems
    Volume5
    Issue number2
    DOIs
    StatePublished - Feb 2023

    Keywords

    • aqueous electrolytes
    • brain inspired
    • ionic liquids
    • neuromorphic computing
    • resistive memory devices

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