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Updated: May 8, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
Published on: March 9, 2019
Mixed binary supporting electrolyte approach for enhanced synaptic functionality in one-shot integrable
Jiyun Lee1, Jaehoon Lee1, Hyeonsu Bang2
1SKKU Advanced Institute of Nanotechnology (SAINT) and Department of Nano Science and Technology, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea. bskang88@skku.edu.
Abstract:
The limitations of traditional von Neumann architectures have driven interest in organic mixed ionic-electronic conductors (OMIECs) for integrating memory and computation. Organic electrochemical synaptic transistors (OESTs) are particularly promising for emulating biological synaptic behaviors because they offer low power consumption, flexibility, and scalability. One-shot integrable electropolymerization (OSIEP) has emerged as a promising approach for fabricating OESTs owing to its simplicity and integrative capabilities. However, OSIEP-fabricated devices often exhibit inferior memory characteristics, largely due to suboptimal control of channel crystallinity-a key factor influencing memory retention. In this study, we addressed this challenge by fabricating poly(3,4-ethylenedioxythiphene) (PEDOT)-based OESTs using a mixed binary supporting electrolyte via the OSIEP method. A binary system comprising tetrabutylammonium tetrafluoroborate (BF4-) and 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (TFSI-) was adopted to balance crystallinity and ionic conductivity. PEDOT:Blend films achieved enhanced synaptic functionality by combining the high de-doping efficiency and charge transport of PEDOT:BF4 with the superior molecular orientation of PEDOT:TFSI. This synergistic approach significantly improved the long-term depression/potentiation characteristics and prolonged memory retention. PEDOT:Blend-based synaptic transistors achieved a recognition accuracy of 95.58% on the MNIST dataset, surpassing devices fabricated with single electrolytes. These findings highlight a scalable strategy for tuning the synaptic properties in OMIEC-based devices, thereby advancing their potential for neuromorphic computing applications.
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