Highly Reliable and Uniform Synaptic Transistors Enabled by a Polymer-Engineered Semiconducting Nanotube Network

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Authors: Y.S. Kim, Jaemin Shin, S. K. OH, Yedam Kim, Ojun Kwon, Yejin Kim, Sanghyeon Park, Doyeon Won, Woojin Park, Bogyu Lim, Byungjin Cho
Cited by: 1
References: 72

Abstract

-dodecylfluorenyl-2,7-diyl) (PFDD)-wrapped semiconducting single-walled carbon nanotube (s-SWCNT) network. The PFDD polymer wrapping of the SWCNTs offers a synergistic combination for synaptic devices: high selectivity of sorting s-SWCNTs and energetically stable charge-trapping sites along the nanotube surface, enabling controlled conductance modulation. In addition, the simple polymer-SWCNT hybrid structure contributes to highly uniform electrical properties in the array. A reproducible conductance-tuning capability is demonstrated in a PFDD-SWCNT synaptic transistor, resulting in robust synaptic plasticity. Diverse synaptic functions, such as excitatory post-synaptic currents, short- and long-term memory, long-term potentiation (LTP) and depression (LTD), and paired-pulse facilitation, are emulated. The stable dynamic modulation of LTP/LTD in the PFDD-SWCNT synaptic device is validated over 10 000 pulse endurance cycles. Importantly, low nonlinearity values of 2.08 and 2.95 for potentiation and depression, respectively, with an asymmetric ratio of 63.8%, lead to a high recognition accuracy of 90.26% in the handwritten image classification task based on an artificial neural network simulation. The PFDD-SWCNT hybrid structure establishes a robust platform for high-precision and reliable neuromorphic circuitry.

Fields of Study & Subjects

Advanced Memory and Neural Computing Neural Networks and Reservoir Computing Advanced Sensor and Energy Harvesting Materials

Publication details

Journal / source
ACS Applied Materials & Interfaces
Publisher
American Chemical Society (ACS)
Volume
18
Issue
14
Pages
20877–20889
Publication date
1 April 2026
Language
EN