Cellulose Ionogels: Unraveling Structure–Property Relationships Through Multiscale In-Situ Characterization and Theoretical Modeling

Abstract

Cellulose ionogels have emerged as promising functional soft materials for flexible electronics, energy storage, and biosensing owing to their inherent biocompatibility and unique ionic conductivity. However, establishing precise structure–property relationships remains a fundamental challenge due to the complex, non-equilibrium dynamic processes—such as transient solvation, competing hydrogen-bonding networks, and mesoscopic phase separation—that occur during dissolution and gelation. Traditional static and post-mortem characterizations fail to capture these spatiotemporally dynamic behaviors, creating a critical knowledge gap. To overcome this bottleneck, the integration of real-time in situ/operando characterization techniques with multiscale computational simulations has established a novel, synergistic paradigm. This review comprehensively synthesizes recent advances in decoding the multiscale architectures of cellulose ionogels. We systematically analyze how molecular-scale calculations and time-resolved vibrational/electronic spectroscopies reveal interfacial solvation mechanisms and dynamic bond cleavage/reconstruction. We further evaluate how mesoscopic scattering, nanomechanical mapping, and rheological tools resolve network topology and structural heterogeneity. By bridging these multiscale diagnostics with macroscopic transport and mechanics, the dynamic coupling/decoupling mechanisms governing ionic conductivity, mechanical toughness, and thermal stability are critically decoded. Finally, key technical bottlenecks and future trajectories—including physics-informed machine learning, operando multi-field coupling probes, and AI-driven inverse material design—are outlined, providing theoretical guidelines and technical blueprints for next-generation sustainable ionogels.