Academic Journal

Ferroelectric‐Gated Hybrid‐Layered Organic Field‐Effect Transistors for Multimode Signal Processing.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Ferroelectric‐Gated Hybrid‐Layered Organic Field‐Effect Transistors for Multimode Signal Processing.
Συγγραφείς: Liu, Jie, Zhang, Mengyun, Han, Wushuang, Du, Fan, Wu, Limin, Fang, Xiaosheng
Πηγή: Advanced Functional Materials; 1/15/2026, Vol. 36 Issue 5, p1-11, 11p
Θεματικοί όροι: Organic field-effect transistors, Adaptive signal processing, Neuromorphics, Ferroelectric crystals, Wearable technology, Storage, Photodetectors, Artificial intelligence
Περίληψη: The rapid development of intelligent systems has driven the urgent need for multifunctional devices within a unified framework through innovative design principles. Here, a ferroelectric‐gated organic field‐effect transistor (Fe‐OFET) is proposed, which synergistically combines light perception, data storage, and neuromorphic computing functionalities. The device features a hybrid‐layered channel with engineered organic molecule modification, improving photodetection performance via optimized exciton dissociation, electron trapping, and hole injection. This design yields exceptional photoresponsivity of 2.4 A W−1 and detectivity of 1.3 × 1013 Jones. Integration of the ferroelectric layer enables nonvolatile conductance modulation, exhibiting a wide memory window, robust switching endurance with an on/off ratio of >104 and long‐term data retention exceeding 4 × 103 s. Furthermore, the Fe‐OFET‐based synapse architecture demonstrates potential for wearable neuromorphic electronics, combining flexibility with cognitive functions. The device demonstrates accurate recognition and classification of electrocardiogram waveforms and handwritten digits, achieving accuracies up to 85% and 91%, respectively. This work establishes a hardware paradigm in multimode signal processing and adaptive edge intelligence, offering innovative solutions for next‐generation electronics targeting diverse application scenarios. [ABSTRACT FROM AUTHOR]
Copyright of Advanced Functional Materials is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Βάση Δεδομένων: Complementary Index
Περιγραφή
ISSN:1616301X
DOI:10.1002/adfm.202508765