Diverse synaptic weight adjustment of bio-inspired ZrOx-based memristors for neuromorphic systemopen access
- Authors
- Kim, Chaeun; Lee, Yunseok; Kim, Sunghun; Kang, Myounggon; Kim, Sungjun
- Issue Date
- Apr-2023
- Publisher
- Elsevier Ltd
- Keywords
- AI semiconductor; Neural network; Neuromorphic system; Memristor; Resistive switching
- Citation
- Materials Science in Semiconductor Processing, v.157, pp 1 - 6
- Pages
- 6
- Indexed
- SCIE
SCOPUS
- Journal Title
- Materials Science in Semiconductor Processing
- Volume
- 157
- Start Page
- 1
- End Page
- 6
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/21322
- DOI
- 10.1016/j.mssp.2023.107314
- ISSN
- 1369-8001
1873-4081
- Abstract
- In this article, we demonstrate the bio-inspired synaptic features of the TiN/ZrOx/Pt capacitor structure for neuromorphic engineering. The chemical and material compositions and the thicknesses of each of the layers are verified by using transmission electron microscopy (TEM) images and energy-dispersive X-ray spectroscopy (EDS) maps. Stable resistive switching with a low set voltage (-1 V) was determined by scanning the DC I-V curves of many cells. The DC endurance of-104 cycles and retention (10,000 s) in five states was achieved. Multi-level cells (MLC) characteristics were achieved based on the compliance current and reset stop voltage in DC sweep and pulses. Finally, we emulated paired-pulse facilitation (PPF), paired-pulse depression (PPD), electric excitatory postsynaptic current (EPSC), and spike-timing-dependent plasticity (STDP) of the artificial synapse by using the RRAM device.
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- Appears in
Collections - College of Engineering > Department of Electronics and Electrical Engineering > 1. Journal Articles

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