Harnessing glycol–alkyl copolymerization to realize nonvolatile and biologically relevant synaptic behaviors
Organic electrochemical synaptic transistors (OESTs) are attracting growing attention for neuromorphic computing, yet their long-term stability remains constrained by uncontrolled ion dynamics. Previous studies have incorporated glycol side chains to facilitate ionic transport, but a systematic understanding of how copolymerization with hydrophobic alkyl units governs ion doping and retention is still lacking. Here, we establish a rational backbone-side chain copolymer design strategy that precisely regulates ionic interactions, crystallinity, and charge transport. We also reveal clear correlations between copolymer structure, ion dedoping dynamics, and nonvolatile retention. These structural advantages enable the faithful emulation of key biological behaviors including paired-pulse facilitation, spike-timing dependent plasticity, and long-term potentiation/depression (LTP/D) with high linearity and stability. Based on these properties, the device achieved a high accuracy of 94.1% in ANN-based recognition simulations for MNIST handwritten digits. This work demonstrates that systematic glycol-alkyl copolymer engineering provides a robust and predictive design principle for high-performance neuromorphic synapses, moving beyond empirical side-chain modifications.
Authors
- Yong Ju Jang (ORCID: https://orcid.org/0000-0001-7631-0388)
- Eunho Lee (ORCID: https://orcid.org/0000-0002-8564-6999)
- Sein Chung (ORCID: https://orcid.org/0000-0003-3953-5208)
- Suhui Sim
- Jaewon Lee (ORCID: https://orcid.org/0000-0002-4626-0807)
- Sung Yun Son (ORCID: https://orcid.org/0000-0003-1563-5474)
- Minju Kim (ORCID: https://orcid.org/0000-0002-8011-4037)
- Maozhong An (ORCID: https://orcid.org/0000-0003-1215-0519)
- Junho Sung (ORCID: https://orcid.org/0009-0002-0513-2072)
- Young Un Jeon
Institutions
- Kumoh National Institute of Technology (KR)
- Seoul National University of Science and Technology (KR)
- Pohang University of Science and Technology (KR)
- Kwangwoon University (KR)
- Chungnam National University (KR)
Publication Details
- Journal
- Nanoscale Horizons
- Published
- 2025-11-21
- DOI
- https://doi.org/10.1039/d5nh00623f
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00