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Reduced Stochastic Resistive Switching in Organic‐Inorganic Hybrid Memristors by Vapor‐Phase Infiltration

Ashwanth Subramanian, Nikhil Tiwale, Kim Kisslinger, Chang‐Yong Nam

2022Advanced Electronic Materials17 citationsDOIOpen Access PDF

Abstract

Abstract Resistive random‐access memory (RRAM) is promising for next‐generation data storage and non‐von Neumann computing hardware. However, tuning device switching characteristics and particularly, controlling their stochastic variation remain as critical challenges. Here, new organic‐inorganic hybrid RRAM media are reported whose bipolar switching characteristics and stochasticity can be controlled by vapor‐phase infiltration (VPI), an ex situ hybridization technique derived from atomic layer deposition. Hybrid RRAMs based on AlO x ‐infiltrated SU‐8 feature facile tunability of device switching voltages, off‐state current, and on‐off ratio by adjusting the amount of infiltrated AlO x in the hybrid. Furthermore, a significant reduction in the stochastic, cycle‐to‐cycle variations of switching parameters is enabled by AlO x infiltration, driven by the infiltration‐induced changes in mechanical, dielectric, and chemical properties of organic medium and their influence on the dimension and formation characteristics of conductive filaments. Finally, multi‐level analog switching potentially useful for neuromorphic applications are demonstrated, along with direct, one‐step device patterning exploiting the negative‐tone resist feature of SU‐8. With the demonstrated control over switching characteristics and stochastic variation, combined with analog switching and one‐step patterning capabilities, the results not only present a novel hybrid medium for RRAM applications but also showcase the utility of VPI for developing new, high‐performance hybrid RRAM devices.

Topics & Concepts

Neuromorphic engineeringMaterials scienceResistive random-access memoryMemristorOptoelectronicsInfiltration (HVAC)Chemical vapor depositionVoltageNanotechnologyElectronic engineeringComputer scienceElectrical engineeringComposite materialArtificial neural networkArtificial intelligenceEngineeringAdvanced Memory and Neural ComputingTransition Metal Oxide NanomaterialsConducting polymers and applications