Xi Zeng, Chengyuan Peng, Wenpei Shi, Shengjie Hu, Yushi Cao, Huan Wei, Ping-An Chen, Jiangnan Xia, Jiaqi Ding, Yu Zhang, Zhenqi Gong, Huajie Chen, Naiyan Lu, Rong Li, Yuanyuan Hu
{"title":"An Interlayer Strategy for Low-Voltage Thin-Film Organic Electrochemical Transistors.","authors":"Xi Zeng, Chengyuan Peng, Wenpei Shi, Shengjie Hu, Yushi Cao, Huan Wei, Ping-An Chen, Jiangnan Xia, Jiaqi Ding, Yu Zhang, Zhenqi Gong, Huajie Chen, Naiyan Lu, Rong Li, Yuanyuan Hu","doi":"10.1002/smtd.202500322","DOIUrl":null,"url":null,"abstract":"<p><p>Solid-state organic electrochemical transistors (SS-OECTs) are promising candidates for next-generation wearable and bioelectronic applications due to their high transconductance and low-voltage operation. However, conventional SS-OECTs rely on ion gels with high ionic liquid concentrations, which compromise mechanical robustness and scalability. This study addresses these limitations by developing thin-film OECTs (TF-OECTs) using solid electrolytes with significantly reduced ionic liquid concentrations and introducing a doped organic semiconductor film (DOSCF) as an interlayer between the gate and electrolyte. This strategy enables TF-OECTs to achieve film-like mechanical properties while maintaining high performance, including a maximum transconductance (g<sub>m</sub>) of 5.05 mS, operational voltages below 1 V, and exceptional stability over 1000 switching cycles. The devices also exhibit superior flexibility, enduring over 2000 bending cycles with minimal performance degradation. Their potential is demonstrated in ferric ion sensing, achieving an ultralow detection limit of 15 nm with a high selectivity of 0.7 mA dec<sup>-1</sup>, and in neuromorphic computing, where they emulate synaptic behaviors and achieve a 96.7% image recognition accuracy after training with artificial neural networks (ANN). These results highlight the transformative potential of TF-OECTs for integration into advanced, multifunctional electronic systems, combining high performance, mechanical robustness, and scalability.</p>","PeriodicalId":229,"journal":{"name":"Small Methods","volume":" ","pages":"e2500322"},"PeriodicalIF":10.7000,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Small Methods","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1002/smtd.202500322","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Solid-state organic electrochemical transistors (SS-OECTs) are promising candidates for next-generation wearable and bioelectronic applications due to their high transconductance and low-voltage operation. However, conventional SS-OECTs rely on ion gels with high ionic liquid concentrations, which compromise mechanical robustness and scalability. This study addresses these limitations by developing thin-film OECTs (TF-OECTs) using solid electrolytes with significantly reduced ionic liquid concentrations and introducing a doped organic semiconductor film (DOSCF) as an interlayer between the gate and electrolyte. This strategy enables TF-OECTs to achieve film-like mechanical properties while maintaining high performance, including a maximum transconductance (gm) of 5.05 mS, operational voltages below 1 V, and exceptional stability over 1000 switching cycles. The devices also exhibit superior flexibility, enduring over 2000 bending cycles with minimal performance degradation. Their potential is demonstrated in ferric ion sensing, achieving an ultralow detection limit of 15 nm with a high selectivity of 0.7 mA dec-1, and in neuromorphic computing, where they emulate synaptic behaviors and achieve a 96.7% image recognition accuracy after training with artificial neural networks (ANN). These results highlight the transformative potential of TF-OECTs for integration into advanced, multifunctional electronic systems, combining high performance, mechanical robustness, and scalability.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.