Unraveling Polymer–Ion Interactions in Electrochromic Polymers for their Implementation in Organic Electrochemical Synaptic Devices

Owing to low-power, fast and highly adaptive operability, as well scalability, electrochemical random-access memory (ECRAM) technology is one of the most promising approaches for neuromorphic computing based on artificial neural networks. Despite recent advances, practical implementation ECRAMs remains challenging due several limitations including high write noise, asymmetric weight updates, insufficient dynamic ranges. Here, inspired by similarities in structural functional requirements between electrochromic devices ECRAMs, high-performance, single-transistor polymers (ECPs) are demonstrated. To effectively translate electrochromism into ion polymers, this study systematically investigates polymer–ion interactions, redox activity, mixed ionic–electronic conduction, stability ECPs both experimentally computationally using select electrolytes. The best-performing ECP-electrolyte combination then implemented an ECRAM device further explore synaptic plasticity behaviors. resulting exhibits linearity symmetric conductance modulation, range (≈1 mS or ≈6x), training accuracy (>84% within five cycles a standard image recognition dataset), comparable existing state-of-the-art ECRAMs. This offers approach discover design novel polymer materials organic demonstrates potential applications, taking advantage mature knowledge basis devices.