Highly Stretchable Synaptic Transistors Based On Phase-Separated P3HT–SEBS Networks for Adaptative Neuromorphic Computation
Recent advancements in organic electronics highlight the potential of stretchable organic field-effect transistors for neuromorphic applications. However, maintaining a high electrical performance under mechanical strain remains a critical challenge. Here, we present a stretchable organic synaptic transistor with a phase-separating method. By blending poly(3-hexylthiophene) (P3HT) with styrene–ethylene–butylene–styrene (SEBS), P3HT–SEBS phase-separated films were obtained that combine high mechanical stretchability with good charge transport property. The organic synaptic transistors (OSTs) were able to withstand a mechanical strain of greater than 80%. Remarkably, by combining SEBS-induced stress dissipation with ionic gel-driven synaptic modulation, the OSTs were able to mimic synaptic dynamics under strain, facilitating neurobiological behaviors. Our work addresses the critical need for strain-resilient organic devices in next-generation human–machine collaboration.
Authors
- Junbiao Peng (ORCID: https://orcid.org/0000-0003-1671-2750)
- Jiayi Pan (ORCID: https://orcid.org/0000-0002-6835-1400)
- Huimin Su
- Jintao Xu (ORCID: https://orcid.org/0000-0003-2546-2255)
- Yutian Liu (ORCID: https://orcid.org/0000-0001-6932-5207)
- Baozhong Chen
- Yang Lü (ORCID: https://orcid.org/0000-0002-9280-2718)
- Jiale Huang (ORCID: https://orcid.org/0000-0002-5743-0461)
- Linfeng Lan (ORCID: https://orcid.org/0000-0002-6477-2830)
- Qi Zhou (ORCID: https://orcid.org/0000-0002-8275-3721)
- Bo Huang
- Shanshan Gong (ORCID: https://orcid.org/0000-0002-0132-0730)
- Jiajun Lin
Institutions
- Japan Display (Japan) (JP)
- Advanced Materials and Devices (United States) (US)
- University of Hong Kong (HK)
- South China University of Technology (CN)
Publication Details
- Journal
- ACS Applied Electronic Materials
- Published
- 2025-08-27
- DOI
- https://doi.org/10.1021/acsaelm.5c01357
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00