Detachable and Reusable: Reinforced π‐Ion Film for Modular Synaptic Reservoir Computing
Organic electrochemical transistors (OECTs) show significant promise for bioelectronics and neuromorphic computing applications due to their low operating voltage, biocompatibility, and ion-mediated charge transport. However, conventional OECTs with permanently fixed organic semiconductor (OSC) layers lack modularity and reusability for sustainable electronics with e-waste reduction. Here, a novel reinforced π-ion film OECT featuring a detachable and reusable OSC layer that creates a unified composite with dielectric and gate components, establishing a new paradigm for modular device architectures is proposed. Through solvent exchange and mesh-supported gelation, π-ion film exhibits enhanced mechanical stability, detachability, and superior electrical performance. The OECTs demonstrate remarkable 35-day air stability, 50-day storage lifetime, and over 80% performance retention after 600 electrical cycles. Furthermore, the π-ion film OECTs exhibit synaptic behavior with paired-pulse facilitation of 167% and long-term memory retention of 34% maintained synaptic current after 250 s. These characteristics enable reservoir computing applications with a 4-bit encoding scheme for image recognition, processing 16 × 16 pixelated input patterns, demonstrating reliable state differentiation and stable signal retention. Even at lab-scale development, reinforced π-ion film OECTs represent a promising eco-friendly platform for modular, reusable components in next-generation neuromorphic computing systems, aligning with electronic waste reduction policies by enabling component reuse.
Authors
- G. Woo
- Won‐Woo Lee (ORCID: https://orcid.org/0000-0002-5347-9591)
- Chang Min Lee (ORCID: https://orcid.org/0000-0003-2567-5533)
- Eun Kwang Lee (ORCID: https://orcid.org/0000-0001-5727-5716)
- Hocheon Yoo (ORCID: https://orcid.org/0000-0003-0772-3327)
- Seung Min Lee (ORCID: https://orcid.org/0000-0002-3419-3336)
- Yong Hee Kim
- Min Ju Jung
Institutions
- Hanyang University (KR)
- Pukyong National University (KR)
Publication Details
- Journal
- Advanced Materials
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1002/adma.202506729
- Citations
- 5
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 3.65
Funders
- National Research Foundation
- Pukyong National University
- Ministry of Trade, Industry and Energy
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea
- Industry-Academic Cooperation Foundation of Kyungnam University
- Institute for Information and Communications Technology Promotion