Modulating Synaptic Plasticity of Analogue Memristor Based on Oxidized MXene Composited with ZrO 2 Quantum Dots
Source abstract
Abstract
As an emerging artificial synapse for emulating the human brain, the memristor is promising owing to its excellent ability to mimic synaptic functions. In this work, we report an analogue memristor based on a composite of hydrothermally oxidized Ti 3 C 2 T x MXene and ligand-exchanged ZrO 2 quantum dots (QDs), synthesized via a solution-based method using DMF at a 1:2 weight ratio. The resulting Ag/oxidized MXene-ZrO 2 QDs/FTO (fluorine-doped tin oxide) memristor exhibits a transition from digital to analogue resistive switching (RS) due to the integration of the ZrO 2 QDs. It supports 18 linearly modulated conductance levels, enabling multilevel memory storage beyond 4 bits. Its reliable and reconfigurable switching behavior supports synaptic weight modulation and image recognition tasks in an artificial neural network. The synergistic interaction between oxidized MXene and ZrO 2 QDs in the composite enables low-power operational analogue memristors with tunable synaptic plasticity, making it suitable for next-generation neuromorphic computing devices.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · MXene and MAX Phase Materials · Ferroelectric and Negative Capacitance Devices
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Materials Engineering and Convergence Technology
Gyeongsang National University
Division of Materials Engineering and Science, Hanyang University, 222, Wangsimni-ro, Seongdong-gu, Seoul 04763, Republic of Korea
Research Institute for Green Energy Convergence Technology
Advanced Institute of Convergence Technology
Seoul National University
Funding
Ministry of Education · National Research Foundation of Korea
References (33)
Show source-provided references
1. 10.1002/adfm.20110314810.1002/adfm.201103148 ↗
2. 10.1038/nature0693210.1038/nature06932 ↗
3. 10.1002/aelm.20220090810.1002/aelm.202200908 ↗
4. 10.1021/acsami.4c0136410.1021/acsami.4c01364 ↗
5. 10.1021/acsnano.4c0326410.1021/acsnano.4c03264 ↗
6. 10.1021/acsnano.2c0335110.1021/acsnano.2c03351 ↗
7. 10.1021/acs.jpcc.7b0049210.1021/acs.jpcc.7b00492 ↗
8. 10.1021/acssensors.2c0174810.1021/acssensors.2c01748 ↗
9. 10.1002/admi.20210194810.1002/admi.202101948 ↗
10. 10.1038/s41699-024-00522-410.1038/s41699-024-00522-4 ↗
11. 10.1016/j.trechm.2022.06.00410.1016/j.trechm.2022.06.004 ↗
12. 10.1002/eem2.1205810.1002/eem2.12058 ↗
13. 10.1021/acsami.3c1185710.1021/acsami.3c11857 ↗
14. 10.1002/aelm.20200086610.1002/aelm.202000866 ↗
15. 10.1002/cphc.20230018710.1002/cphc.202300187 ↗
16. 10.1016/j.compositesb.2022.11001410.1016/j.compositesb.2022.110014 ↗
17. 10.1021/acsanm.3c0500710.1021/acsanm.3c05007 ↗
18. 10.1039/D2CP05014E10.1039/D2CP05014E ↗
19. 10.1038/s41467-019-09998-x10.1038/s41467-019-09998-x ↗
20. 10.3390/nano1419157510.3390/nano14191575 ↗
21. 10.1038/s41598-023-35183-810.1038/s41598-023-35183-8 ↗
22. 10.1007/s10971-015-3881-310.1007/s10971-015-3881-3 ↗
23. 10.1631/FITEE.190036310.1631/FITEE.1900363 ↗
24. 10.1038/s41467-024-46372-y10.1038/s41467-024-46372-y ↗
25. 10.1186/s11671-017-2330-310.1186/s11671-017-2330-3 ↗
26. 10.1021/acsomega.3c0320010.1021/acsomega.3c03200 ↗
27. 10.1021/acsaelm.5c0013110.1021/acsaelm.5c00131 ↗
28. 10.3389/fnins.2021.63952610.3389/fnins.2021.639526 ↗
29. 10.3390/nano1219345510.3390/nano12193455 ↗
30. 10.1039/C6NR08024C10.1039/C6NR08024C ↗
31. 10.1021/acs.jpclett.4c0335310.1021/acs.jpclett.4c03353 ↗
32. 10.1186/s40580-023-00380-810.1186/s40580-023-00380-8 ↗
33. 10.1016/j.measurement.2025.11696010.1016/j.measurement.2025.116960 ↗