Decoupling the Retention-Energy Trade-Off Through Structural Reorganization of Synaptic Polyelectrolytes for Nonvolatile Neuromorphic Devices.

Electrolyte-gated synaptic transistors (EGSTs) are promising ion-mediated artificial synapses, but their performance is constrained by a retention-energy trade-off. Enhancing long-term memory (LTM) retention often requires enhanced ion accessibility, which can induce excessive ion accumulation and increase energy consumption. Herein, we resolve this physical dilemma by rationally engineering the spatial architecture of a poly(maleic acid)-poly(styrenesulfonate) (PMA-PSS) copolymer electrolyte. The density of the bulky, hydrophilic PSS blocks is increased to impose steric hindrance and thermodynamic mismatch against TFSI- ions, thereby limiting excessive ion influx while preserving the injected ions through a confined ion-polymer coupling pathway. Such spatial confinement triggers a localized, persistent doping-induced lattice expansion. This structural reorganization establishes a structural basis for suppressed TFSI- back-diffusion by creating a sterically constrained ion-polymer environment that stabilizes the doped state. Consequently, the minimized excessive ion accumulation and suppressed post-pulse ion back-diffusion enable the high-PSS-content EGSTs to achieve exceptional LTM retention, low energy consumption, and endurance over 8,000 programming cycles. System-level simulations reveal an image recognition accuracy of 87%, comparable to that of an ideal weight-update model, confirming that our polyanion-induced structural reorganization provides a promising blueprint for next-generation, high-fidelity artificial intelligence hardware.