Natural electrochemical synaptic transistors (OESTs) are attracting rising consideration for neuromorphic computing, but their lengthy‐time period stability stays constrained by uncontrolled ion dynamics. Earlier research have included glycol aspect chains to facilitate ionic transport, however a scientific understanding of how copolymerization with hydrophobic alkyl models governs ion doping and retention remains to be missing. Right here, we set up a rational spine–aspect chain copolymer design technique that exactly regulates ionic interactions, crystallinity, and cost transport. We additionally reveal clear correlations between copolymer construction, ion dedoping dynamics, and nonvolatile retention. These structural benefits allow the devoted emulation of key organic behaviors together with paired-pulse facilitation, spike-timing dependent plasticity, and long-term potentiation/melancholy (LTP/D) with excessive linearity and stability. Primarily based on these properties, the gadget achieved a excessive accuracy of 94.1% in ANN-based recognition simulations for MNIST handwritten digits. This work demonstrates that systematic glycol–alkyl copolymer engineering offers a strong and predictive design precept for high-performance neuromorphic synapses, transferring past empirical side-chain modifications.
