An Enthalpy-Entropy Compensated Ionogel With a Broadband Viscoelastic Plateau for Non-Invasive and High-Fidelity Neurointerfaces.

Abstract

Achieving non-invasive and high-fidelity electrophysiological recording, particularly electroencephalography (EEG), on dynamic and irregular human skin remains a central challenge in soft bioelectronics, as materials rarely reconcile liquid-like adaptability with solid-like stability. Here, we overcome this limitation by designing a viscoelastic ionogel governed by a dynamic enthalpy-entropy balance. Salt-bridge hydrogen bonds form a low-entropy and high-interaction network, intrinsically limiting the capacity for entropic energy storage. This network then self-organizes with a soft phase into a bicontinuous nanostructure. Acting as a mechanical parallel circuit, this architecture introduces a broad molecular relaxation spectrum, providing broadband enthalpic dissipation and realizing broadband enthalpy-entropy compensation. Consequently, the ionogel exhibits a frequency-independent viscoelastic plateau (G'≈G'') spanning over nine orders of magnitude in frequency (10^-4 to 10⁵ Hz) and a wide temperature range (-30°C to 40°C). The ionogel reduces skin-electrode impedance by more than an order of magnitude compared to commercial electrodes and maintains high-fidelity electrophysiological recordings during 72-h continuous wear. Integrated with a deep learning framework, it enables high-precision decoding of EEG signals, achieving 95% accuracy in classifying eight distinct emotional states. This work establishes a generalizable thermodynamic design principle for soft bioelectronic interfaces, offering broad potential for neural diagnostics, emotional monitoring, and wearable neuroprosthetics.