Journal
NANOTECHNOLOGY
Volume 29, Issue 11, Pages -Publisher
IOP Publishing Ltd
DOI: 10.1088/1361-6528/aaa733
Keywords
conductance linearity; neuromorphic system; resistive random access memory (RRAM); synapse device; TaOx
Funding
- Ministry of Trade, Industry Energy [10067794]
- Korea Semiconductor Research Consortium
- Korea Evaluation Institute of Industrial Technology (KEIT) [10067794] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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To improve the classification accuracy of an image data set (CIFAR-10) by using analog input voltage, synapse devices with excellent conductance linearity (CL) and multi-level cell (MLC) characteristics are required. We analyze the CL and MLC characteristics of TaOx-based filamentary resistive random access memory (RRAM) to implement the synapse device in neural network hardware. Our findings show that the number of oxygen vacancies in the filament constriction region of the RRAM directly controls the CL and MLC characteristics. By adopting a Ta electrode (instead of Ti) and the hot-forming step, we could form a dense conductive filament. As a result, a wide range of conductance levels with CL is achieved and significantly improved image classification accuracy is confirmed.
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