Tailoring Side Chain in Organic Donor‐Pi‐Acceptor Copolymeric Mixed Conductors for Efficient and Extremely Stable Artificial Synapses

作者：Hanmei Tang, Zhaoyang Qin, Jiandong Jiang, J. S. Tan, Zhichao Xie, Riping Liu, Yujun Fu, Qiming Liu, Hailiang Liao, Yue Wan, Qi Wang, Deyan He · 发表于：Small · 年份：2025 · DOI：10.1002/smll.202505310 · 被引用次数：4 · 研究领域：Advanced Memory and Neural Computing、Neural Networks and Reservoir Computing、Perovskite Materials and Applications

Environmentally stable, thermally robust, and computationally efficient organic synapses are crucial for advancing neuromorphic electronics. However, achieving these features in devices remains challenging due to the absence of ideal polymeric conductors. Herein, it is designed and synthesized two novel donor-pi-acceptor (D-π-A) copolymers with tailored side-chain length, using them as channels for artificial synapses. The incorporation of alkyl chains with varying length, terminated with Boc (t-butyloxycarbonyl) group in the acceptor moiety regulates crystalline phase in bulk films, enabling self-assembles at elevated temperature. Meanwhile, the inclusion of ethylene glycol (EG) groups in the donor moieties enhances ion migration, promoting synergistic ion behavior, synaptic functionality, and stability. Under ambient conditions, devices with longer side chain demonstrated impressive non-volatile time constant (τ) of 9399.9 s, enlarged dynamic range of ≈91×, 16-week operational durability. Remarkably, this polymer exhibited exceptional thermal resilience, maintaining performance even after annealing at 280 °C, making them highly compatible with large-scale hardware integration. Leveraging the devices' outstanding stability, a reliable reservoir computing system that maintained a computing error within 1% over a 4-week span and 2% after annealing is constructed. This work underscores that strategic molecular design can significantly improve neuromorphic device performance, en...