Regionally controlled ion-doping of organic electrochemical transistors for computing-memory co-integrated neuromorphic systems
Abstract Organic electrochemical transistors (OECTs), endued with processing and memory functionalities, present a remarkable potential for neuromorphic electronics. However, integrating processing and memory cores for neuromorphic systems is complicated by heterogeneous material compatibility and device architecture constraints. Here, we demonstrate a versatile regionally controlled ion-doping strategy for modulating the operational mode of OECTs between high-performance computing and non-volatile memory, without varying the materials or operating conditions. The key to this method is the use of inkjet-printed electrolytes with programmable 3D architectures, which can be precisely deposited onto the OECT channel, achieving a tunable thickness ranging from 100 nm to several tens of micrometers. By engineering the electrolyte’s spatial structure, we demonstrate two complementary OECT configurations: ion-rich OECTs with multilayer electrolytes achieve high stimulus-resolution capability of 1 ms for dynamic computation, and ion-deficient OECTs with single-layer electrolytes establish stable ion-trapping memristive states (300 s retention). Moreover, the integration of ion-rich and ion-deficient OECTs enables a neuromorphic circuit capable of simultaneous encoding and storage of alphanumeric information. This study presents a simple yet effective strategy that overcomes material compatibility constraints and simplifies circuit design, paving the way for highly integrated neuromorphic systems based on OECTs.
Authors
- C. Liu (ORCID: https://orcid.org/0009-0002-2689-974X)
- Xiaoci Liang (ORCID: https://orcid.org/0000-0002-7421-0153)
- Songjia Han (ORCID: https://orcid.org/0000-0003-3358-9408)
- Mancheng Li
- Wenjing Zhang (ORCID: https://orcid.org/0000-0002-0301-178X)
- Mengye Wang (ORCID: https://orcid.org/0000-0002-8797-8196)
- X. Y. Lv
- Chen Chen (ORCID: https://orcid.org/0000-0002-2501-5968)
Institutions
- South China Agricultural University (CN)
- Sun Yat-sen University (CN)
- National University of Defense Technology (CN)
Publication Details
- Journal
- npj Flexible Electronics
- Published
- 2025-12-17
- DOI
- https://doi.org/10.1038/s41528-025-00511-7
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Hunan Province