3D-Printed Intrinsically Stretchable Organic Electrochemical Synaptic Transistor Array

• Published in: ACS applied materials & interfaces Vol. 15; no. 35; pp. 41656 - 41665
• Main Authors: Li, Xiaohong, Bi, Ran, Ou, Xingcheng, Han, Songjia, Sheng, Yu, Chen, Guoliang, Xie, Zhuang, Liu, Chuan, Yue, Wan, Wang, Yan, Hu, Weijie, Guo, Shuang-Zhuang
• Format: Journal Article
• Language: English
• Published: American Chemical Society 06.09.2023
• Subjects: cost effectiveness; electrochemistry; hardness; hydrophilicity; Organic Electronic Devices; plasticity; synapse; transistors; wettability; artificial synapse; 3D printing; microstructured hydrophilic substrate; stretchable organic electrochemical transistor; organic electrochemical transistor
• ISSN: 1944-8244; 1944-8252; 1944-8252
• DOI: 10.1021/acsami.3c07169

Organic electrochemical transistors (OECTs) for skin-like bioelectronics require mechanical stretchability, softness, and cost-effective large-scale manufacturing. However, developing intrinsically stretchable OECTs using a simple and fast-response technique is challenging due to limitations in functional materials, substrate wettability, and integrated processing of multiple materials. In this regard, we propose a fabrication method devised by combining the preparation of a microstructured hydrophilic substrate, multi-material printing of functional inks with varying viscosities, and optimization of the device channel geometries. The resulting intrinsically stretchable OECT array with synaptic properties was successfully manufactured. These devices demonstrated high transconductance (22.5 mS), excellent mechanical softness (Young’s modulus ∼ 2.2 MPa), and stretchability (∼30%). Notably, the device also exhibited artificial synapse functionality, mimicking the biological synapse with features such as paired-pulse depression, short-term plasticity, and long-term plasticity. This study showcases a promising strategy for fabricating intrinsically stretchable OECTs and provides valuable insights for the development of brain-computer interfaces.