Unveiling the Potential of HfO2/WS2 Bilayer Films: Robust Analog Switching and Synaptic Emulation for Advanced Memory and Neuromorphic Computingopen access
- Authors
- Ismail, Muhammad; Rasheed, Maria; Kim, Sunghun; Mahata, Chandreswar; Kang, Myounggon; Kim, Sungjun
- Issue Date
- Oct-2023
- Publisher
- American Chemical Society
- Keywords
- Atoms; Energy Utilization; Green Computing; Hafnium Oxides; High Resolution Transmission Electron Microscopy; Image Recognition; Memristors; Multilayer Neural Networks; Network Layers; Oxygen; Tungsten Compounds; X Ray Photoelectron Spectroscopy; Artificial Synapse; Bi-layer Films; Devices Integration; High-k Oxides; High-vacuum Conditions; Low Energy Consumption; Neuromorphic Computing; Non-volatile Memory; Nonvolatile Memory; Two-dimensional Materials; Atomic Layer Deposition
- Citation
- ACS Materials Letters, v.5, no.11, pp 3080 - 3092
- Pages
- 13
- Indexed
- SCIE
SCOPUS
- Journal Title
- ACS Materials Letters
- Volume
- 5
- Number
- 11
- Start Page
- 3080
- End Page
- 3092
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/20531
- DOI
- 10.1021/acsmaterialslett.3c00600
- ISSN
- 2639-4979
2639-4979
- Abstract
- Nonvolatile memories using two-dimensional materials and high-k oxides have gained attention for their potential to achieve robust analog switching, easy memristive device integration, and low-energy consumption. In this study, we fabricated Pt/TiN/HfO2/WS2/Pt memristive devices. To implement these devices, a WS2 film was thermally evaporated under high vacuum conditions followed by HfO2 growth using atomic layer deposition at 400 degrees C. Detailed analysis using high-resolution transmission electron microscopy and X-ray photoelectron spectroscopy revealed diffusion of W and S atoms within the HfO2 layer and extraction of oxygen by W atoms, thus resulting in a multilayer structure (HfWOySx, Wx-1OySx, and W1-xOySx) with varying ratios of oxygen, tungsten, and sulfur atoms (x and y). The fabricated devices demonstrated consistent and stable analogue switching over numerous cycles, with exceptional endurance (2000 cycles) and retention (10(3) s). They exhibited high cycle-to-cycle consistency, as evidenced by the low-coefficient of variation (3.5% and 4.0% for the set and reset voltages, respectively). By modulating the reset stop voltage, we achieved five-level resistance states, thus making these devices capable of being used in artificial synapses. Furthermore, we observed analog switching with gradual resistance changes under different current compliance conditions by incrementally adjusting the reset-stop voltage. The memristor-based artificial synapses exhibited fundamental synaptic functions, such as long-term potentiation, long-term depression, paired-pulse facilitation, paired-pulse depression, and spike-timing-dependent plasticity for long-term and short-term plasticity. Moreover, we employed a three-layer artificial neural network for image recognition, achieving 94% accuracy using identical pulse amplitudes. These findings highlight the potential of HfO2/WS2 bilayer films, enable controllable analogue switching, and simulate synaptic functions. They hold promise for future data storage memory and neuromorphic computing systems.
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Collections - College of Engineering > Department of Electronics and Electrical Engineering > 1. Journal Articles

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