단일 벽 탄소 나노 튜브를 이용한 스위칭 레이어Al2O3/HfOx 기반의 멤리스터
Memristors based on Al2O3/HfOx for Switching Layer Using Single-Walled Carbon Nanotubes
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초록
최근 인간의 뇌를 모방한 스파이킹 뉴럴 네트워크(SNNs)의 뉴로모픽(Neuromorphic) 시스템이 주목을 받고 있다. 뉴로모픽 기술은 인지 응용과 처리 과정에서 속도가 빠르고 전력 소모가 적다는 장점이 있다. SNNs 기반의 저항성 랜덤 엑세스 메모리(RRAM) 은 병렬 연산을 위한 가장 효율적인 구조이며 스파이크 타이밍 종속 가소성(STDP)의 점진적인 스위칭 동작을 수행한다. 시냅스 소자 동작으로서의 RRAM은 저 전력 프로세싱과 다양한 메모리 상태를 표현한다. 하지만, RRAM 소자의 통합은 높은 스위칭 전압 및 전류를 유발하여 높은 전력 소비를 초래한다. RRAM의 동작 전압을 낮추기 위해서는 스위칭 레이어와 금속 전극의 신소재를 개발하는 것이 중요하다. 본 연구에서는 스위칭 전압을 낮추기 위해 전기적, 기계적 특성이 우수한 단일 벽 탄소나노튜브(SWCNTs)를 갖는 (Metal/Al2O3/HfOx/SWCNTs/N+silicon, MOCS)라는 최적화된 새로운 구조를 제안하였다. 따라서 SWCNTs기반 멤리스터의 점진적인 스위칭 동작 및 저 전력 I/V 곡선의 향상을 보여준다.
Abstract
Rencently, neuromorphic systems of spiking neural networks (SNNs) that imitate the human brain have attractedattention. Neuromorphic technology has the advantage of high speed and low power consumption in cognitiveapplications and processing. Resistive random-access memory (RRAM) for SNNs are the most efficient structure forparallel calculation and perform the gradual switching operation of spike-timing-dependent plasticity (STDP). RRAM as synaptic device operation has low-power processing and expresses various memory states. However, theintegration of RRAM device causes high switching voltage and current, resulting in high power consumption. Toreduce the operation voltage of the RRAM, it is important to develop new materials of the switching layer andmetal electrode. This study suggested a optimized new structure that is the Metal/Al2O3/HfOx/SWCNTs/N+silicon(MOCS) with single-walled carbon nanotubes (SWCNTs), which have excellent electrical and mechanical propertiesin order to lower the switching voltage. Therefore, we show an improvement in the gradual switching behaviorand low-power I/V curve of SWCNTs-based memristors.
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