| Autor: |
Ke-Jing Lee, Yu-Chuan Weng, Li-Wen Wang, Hsin-Ni Lin, Parthasarathi Pal, Sheng-Yuan Chu, Darsen Lu, Yeong-Her Wang |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Nanomaterials, Vol 12, Iss 18, p 3252 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2079-4991 |
| DOI: |
10.3390/nano12183252 |
| Popis: |
We enhanced the device uniformity for reliable memory performances by increasing the device surface roughness by exposing the HfO2 thin film surface to argon (Ar) plasma. The results showed significant improvements in electrical and synaptic properties, including memory window, linearity, pattern recognition accuracy, and synaptic weight modulations. Furthermore, we proposed a non-identical pulse waveform for further improvement in linearity accuracy. From the simulation results, the Ar plasma processing device using the designed waveform as the input signals significantly improved the off-chip training and inference accuracy, achieving 96.3% training accuracy and 97.1% inference accuracy in only 10 training cycles. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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