TY - GEN
T1 - Artificial synaptic behavior and its improvement of RRAM device with stacked solution-processed MXene layers
AU - Shen, Zongjie
AU - Zhao, Chun
AU - Liu, Yina
AU - Yang, Li
AU - Zhao, Cezhou
N1 - Funding Information:
ACKNOWLEDGMENT (HEADING 5) This research was funded in part by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China Program (19KJB510059), the Suzhou Science and Technology Development Planning Project: Key Industrial Technology Innovation (SYG201924), and the Key Program Special Fund in XJTLU (KSF-P-02, KSF-T-03, KSF-A-04, KSF-A-05, KSF-A-07).
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - In this work, an RRAM device with the structure of Ag/MXene/MXene/Pt was fabricated, and stacked solution-processed MXene layers acted as the resistive switching (RS) layer. The device exhibited bipolar RS performance with the operation voltage lower than 2.5 V and the switching ratio around 103. The multi-level states of conductance indicated the bionic synaptic characteristics of this device. A performance like long-Term potentiation and depression (LTP/LTD) response suggested the great potential of this device in the neuromorphic system. In addition, based on the MNIST dataset, the pattern recognition system with key parameters from LTP/LTD showed the result with 85% recognition accuracy. After modulation on non-linearity of LTP and LTD curves, higher recognition accuracy was obtained, which was around 93%.
AB - In this work, an RRAM device with the structure of Ag/MXene/MXene/Pt was fabricated, and stacked solution-processed MXene layers acted as the resistive switching (RS) layer. The device exhibited bipolar RS performance with the operation voltage lower than 2.5 V and the switching ratio around 103. The multi-level states of conductance indicated the bionic synaptic characteristics of this device. A performance like long-Term potentiation and depression (LTP/LTD) response suggested the great potential of this device in the neuromorphic system. In addition, based on the MNIST dataset, the pattern recognition system with key parameters from LTP/LTD showed the result with 85% recognition accuracy. After modulation on non-linearity of LTP and LTD curves, higher recognition accuracy was obtained, which was around 93%.
KW - MXene
KW - pattern recognition
KW - solution-processed
KW - synaptic behavior
UR - http://www.scopus.com/inward/record.url?scp=85123349762&partnerID=8YFLogxK
U2 - 10.1109/ISOCC53507.2021.9613944
DO - 10.1109/ISOCC53507.2021.9613944
M3 - Conference Proceeding
AN - SCOPUS:85123349762
T3 - Proceedings - International SoC Design Conference 2021, ISOCC 2021
SP - 187
EP - 188
BT - Proceedings - International SoC Design Conference 2021, ISOCC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th International System-on-Chip Design Conference, ISOCC 2021
Y2 - 6 October 2021 through 9 October 2021
ER -