Advanced Intelligent Systems (Sep 2023)

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

  • Naryung Kim,
  • Gyeong-Tak Go,
  • Hea-Lim Park,
  • Yooseong Ahn,
  • Jingwan Kim,
  • Yeongjun Lee,
  • Dae-Gyo Seo,
  • Wanhee Lee,
  • Yun-Hi Kim,
  • Hoichang Yang,
  • Tae-Woo Lee

DOI
https://doi.org/10.1002/aisy.202300016
Journal volume & issue
Vol. 5, no. 9
pp. n/a – n/a

Abstract

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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.

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