Molecular Tailoring to Achieve Long‐Term Plasticity in Organic Synaptic Transistors for Neuromorphic Computing

Author:

Kim Naryung1,Go Gyeong-Tak1,Park Hea-Lim12,Ahn Yooseong3,Kim Jingwan4,Lee Yeongjun1,Seo Dae-Gyo1,Lee Wanhee1,Kim Yun-Hi4,Yang Hoichang3,Lee Tae-Woo15ORCID

Affiliation:

1. Department of Materials Science and Engineering Seoul National University (SNU) 1 Gwanak-ro, Gwanak-gu Seoul 08826 Republic of Korea

2. Department of Materials Science and Engineering Seoul National University of Science and Technology 232 Gongneung-ro, Nowon-gu Seoul 01811 Republic of Korea

3. Department of Chemical Engineering Inha University Incheon 22212 Republic of Korea

4. Department of Chemistry Gyeongsang National University and Research Institute of Green Energy Convergence Technology (RIGET) Jinju 52828 Republic of Korea

5. School of Chemical and Biological Engineering Institute of Engineering Research Research Institute of Advanced Materials Soft Foundry Seoul National University 1 Gwanak-ro, Gwanak-gu Seoul 08826 Republic of Korea

Abstract

Organic synaptic transistors (OSTs) using intrinsic polymer semiconductors are demonstrated to be suitable for neuromorphic bioelectronics. However, diketopyrrolopyrrole (DPP)‐based copolymers are not applicable to neuromorphic computing systems because the DPP polymer film has demonstrated only short‐term plasticity with short retention (<50 ms) in synaptic devices because of their intrinsic difficulty of electrochemical doping. To expand their applications toward neuromorphic computing that requires long‐term plasticity, artificial synapses with extended retention time should be developed. Herein, molecular tailoring approach to extend the retention time in the ion‐gel‐gated OSTs that use DPP is suggested. The molecular structure is controlled by changing alkyl spacer lengths of side chains. As a result, the doping process is more favorable in DPP with long alkyl spacer, which is confirmed by high doping concentration and slow dedoping rate. Therefore, dedoping of ions is more suppressed in DPP with long alkyl side chain that exhibits extended retention time (≈800 s) of the OSTs. These optimized DPP‐based OSTs obtain high pattern recognition accuracy of ≈96.0% in simulations of an artificial neural network. Molecular tailoring strategies provide a guideline to overcome the intrinsic problem of short synaptic retention time of the OSTs for use in neuromorphic computing.

Funder

Ministry of Science, ICT and Future Planning

Seoul National University

Publisher

Wiley

Subject

General Medicine

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