Local Multimodal Dynamics in Mixed Ionic-Electronic Conductors and Their Fingerprints in Organic Electrochemical Transistor Operation

TL;DR

This study uncovers how local electrochemical transitions in mixed ionic-electronic conductors influence organic electrochemical transistor behavior, revealing spatially resolved internal states through multimodal in-liquid microscopy and modeling.

Contribution

It introduces a novel operando multimodal microscopy approach and a physical model to map and interpret local dynamics in mixed conductors affecting device performance.

Findings

Transfer curves encode localized electrochemical transitions.

Region-specific electrochemical thresholds govern device regions.

Electrostatic force measurements reveal coupled multimodal dynamics.

Abstract

Mixed ionic-electronic conductors host tightly coupled interactions among mobile ions, electronic charges, and the polymer matrix, giving rise to complex multimodal responses spanning electrical, mechanical, and morphological transformations. These materials underpin organic electrochemical transistors (OECTs), which translate such interactions into low-voltage signal amplification and sensing for applications in bioelectronics, neuromorphic computing, and memory. Despite their central role, OECT current-voltage transfer characteristics are often treated phenomenologically, as both the local multimodal dynamics and their connection to global device response remain unresolved. Here, we reveal that the transfer curve encodes a cascade of spatially localized electrochemical transitions, each associated with distinct changes in conductivity, stiffness, and morphology, fundamentally redefining it as a spatially resolved fingerprint of device's internal state. Using automated operando multimodal in-liquid scanning dielectric microscopy, we directly map these dynamics and identify region-specific electrochemical thresholds governing the interplay between source, channel, and drain. We found that the local tip-sample electrostatic force serves as a remarkable mechanistic observable of coupled multimodal dynamics in mixed conductors. A physically grounded model links it to general material, interfacial, and geometric parameters, enabling mechanistic interpretation and predictive insights. Our work provides a new framework for probing and understanding mixed conduction in ion-electron coupled systems.