Litcius/Paper detail

Synaptic Plasticity and Quantized Conductance States in TiN-Nanoparticles-Based Memristor for Neuromorphic System

Chandreswar Mahata, Muhammad Ismail, Myounggon Kang, Sungjun Kim

2022Nanoscale Research Letters23 citationsDOIOpen Access PDF

Abstract

Abstract Controlled conductive filament formation in the resistive random access memory device is an essential requirement for analog resistive switching to develop artificial synapses. In this work, we have studied Au/Ti/HfAlO x /TiN-NP/HfAlO x /ITO RRAM device to demonstrate conductance quantization behavior to achieve the high-density memory application. Stepwise change in conductance under DC and pulse voltage confirms the quantized conductance states with integer and half-integer multiples of G 0 . Reactive TiN-NPs inside the switching layer helps to form and rupture the atomic scale conductive filaments due to enhancing the local electric field inside. Bipolar resistive switching characteristics at low SET/RESET voltage were obtained with memory window > 10 and stable endurance of 10 3 cycles. Short-term and long-term plasticities are successfully demonstrated by modulating the pre-spike number, magnitude, and frequency. The quantized conductance behavior with promising synaptic properties obtained in the experiments suggests HfAlO x /TiN-NP/HfAlO x switching layer is suitable for multilevel high-density storage RRAM devices.

Topics & Concepts

Resistive random-access memoryNeuromorphic engineeringConductanceMaterials scienceMemristorTinOptoelectronicsNanotechnologyQuantization (signal processing)VoltageNon-volatile memoryCondensed matter physicsPhysicsComputer scienceQuantum mechanicsMachine learningMetallurgyArtificial neural networkComputer visionAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeuroscience and Neural Engineering