Thermal Annealing for High Performance and Memory Behavior in n-Type Organic Electrochemical Transistors

N-type organic mixed ionic electronic conductors (n-OMIECs) struggle to match the performance of p-type counterparts, particularly in bioelectronics' flagship device, the organic electrochemical transistor. Enhancing n-type transistor performance typically necessitates the synthesis of new mate...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Advanced materials (Weinheim) 2024-12, p.e2411214
Hauptverfasser: Hidalgo Castillo, Tania Cecilia, Shan, Wentao, Ma, Guorong, Zhao, Haoyu, Wang, Yunfei, Druet, Victor, Saleh, Abdulelah, Gu, Xiaodan, Inal, Sahika
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:N-type organic mixed ionic electronic conductors (n-OMIECs) struggle to match the performance of p-type counterparts, particularly in bioelectronics' flagship device, the organic electrochemical transistor. Enhancing n-type transistor performance typically necessitates the synthesis of new materials. More sustainable post-synthetic treatments, known to improve organic devices in dry and oxygen-free conditions, are not applied to n-OMIECs. This study introduces thermal annealing to enhance n-OMIECs' electron mobility without sacrificing their ability to take up ionic charges. Annealing increases the crystallinity of p(gNDI-gT2), the first designed n-OMIEC, enhancing its transistor performance to compete with new-generation NDI-based materials. Annealing reduces passive and in operando electrolyte uptake without compromising the device threshold voltage, keeping the device power demand low. The microstructure obtained by annealing, combined with the film's strong near-infrared (NIR) absorption and reduced water swelling, enables the creation of a device that retains photocurrent generated upon frequency-dependent light training. This leads to a microscale, water-compatible memory device that emulates the learning process of biological neurons triggered by light. This simple device can be implemented in artificial neural networks and face recognition platforms and achieve vector-matrix multiplication when fabricated in an array form, showcasing the potential for innovative applications in bioelectronics.
ISSN:1521-4095
1521-4095
DOI:10.1002/adma.202411214