Intrinsically Stretchable Vertical Organic Electrochemical Transistor Featuring Sub-Nanometer-Roughness Electrodes for High Transconductance and Stretchability
Stretchable organic electrochemical transistors (S-OECTs) are known for their high transconductance, low operating voltage, and excellent mechanical compliance. Despite advancements in molecular design and geometric engineering, achieving both high transconductance and stable performance under a large strain remains a challenge. This study demonstrates high-transconductance intrinsically stretchable vertical OECTs, fabricated via a smooth stretchable bilayer electrode and a stretchable organic semiconductor. The combination of a smooth evaporated Au layer and transfer printing of Ag NWs endows the electrode with sub-nanometer surface roughness and high conductivity under stretching, ensuring the devices with both high transconductance (∼55 mS) and stretchability (100%). Under 100% strain, the devices successfully demonstrate rich synaptic functionalities and achieve a remarkably high paired-pulse facilitation (PPF) index of 319.82%. When configured into a reservoir computing network, the system achieves 91.76% accuracy in handwritten digit recognition under 100% strain, showcasing significant potential for wearable neuromorphic electronics applications.
Authors
- Enbo Xue (ORCID: https://orcid.org/0009-0006-6955-1806)
- Kun Qiao (ORCID: https://orcid.org/0000-0002-9111-0381)
- Jing Wu (ORCID: https://orcid.org/0009-0006-4814-761X)
- Tao Chen (ORCID: https://orcid.org/0000-0001-9704-9545)
- Bo Wang (ORCID: https://orcid.org/0000-0002-4400-8800)
- Shuai Lü (ORCID: https://orcid.org/0000-0002-0169-349X)
- Yueping Lai (ORCID: https://orcid.org/0009-0003-5747-1698)
- Xu Feng (ORCID: https://orcid.org/0000-0002-9048-7144)
- Sun Xiao
- Bangzhe Zhang
- Liang-Wen Feng
Institutions
- Sichuan University (CN)
- Southeast University (BD)
- Green Chemistry (PL)
- Southeast University (CN)
Publication Details
- Journal
- Nano Letters
- Published
- 2026-03-13
- DOI
- https://doi.org/10.1021/acs.nanolett.6c00353
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00