Wet Etching-Based WO3 Patterning for High-Performance Neuromorphic Electrochemical Transistors
WO3-based electrochemical transistors (ECTs) are recognized as candidates for three-terminal memristors due to their high on–off ratio, long retention time, and rapid switching speed. However, their patterned fabrication often relies on complex vacuum systems or extreme processing conditions, hindering cost-effective scalability. Here, we developed a novel wet etching technique integrated with sol–gel-derived WO3 channels, enabling ambient-air fabrication of Nafion-WO3 ECTs. The wet-etched devices achieve an on–off ratio of ~105, surpassing unetched and dry-etched counterparts by orders of magnitude. Furthermore, they exhibit exceptional paired-pulse facilitation and long-term stability, maintaining 12 distinct conductance states for 103 s, and an on–off ratio of ~102 over 25 read–write cycles. XPS result shows higher W5+ content and M-O-H bond proportion for wet-etched devices, revealing an optimized interface, with enhanced H+ injection efficiency. The simulated artificial neural network using this wet-etched ECT shows ~97% recognition accuracy for handwritten numerals. This approach offers a novel patterning strategy for developing cost-effective, high-performance neuromorphic devices.
Authors
- Xiaoci Liang (ORCID: https://orcid.org/0000-0002-7421-0153)
- Sixing Chen
- Songjia Han (ORCID: https://orcid.org/0000-0003-3358-9408)
- Yu Zhang (ORCID: https://orcid.org/0000-0001-8362-5871)
- Chuan Liu (ORCID: https://orcid.org/0000-0002-0695-592X)
- Liwei Zhang (ORCID: https://orcid.org/0000-0002-7674-9566)
- Li Zhang (ORCID: https://orcid.org/0000-0002-7601-6565)
- Mengye Wang (ORCID: https://orcid.org/0000-0002-8797-8196)
- Shaoming Fu
Institutions
- South China Agricultural University (CN)
- Sun Yat-sen University (CN)
Publication Details
- Journal
- Electronics
- Published
- 2025-03-18
- DOI
- https://doi.org/10.3390/electronics14061183
- Citations
- 3
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 2.19
Funders
- National Natural Science Foundation of China