Nanocellulose-based intelligent hydrogels for flexible sensing: Design strategies, responsive mechanisms, and artificial intelligence-enabled functionalities.

Nanocellulose (NC)-based hydrogels have attracted increasing attention for flexible sensors due to their renewability, biocompatibility, and tunable chemistry. However, conventional hydrogel sensors still suffer from insufficient mechanical robustness, slow response, and poor long-term stability. Integrating NC into dynamic networks offers an effective strategy to overcome these limitations, yet challenges remain in achieving uniform dispersion, strong interfacial interactions, and precise network regulation. This review presents a systematic framework connecting NC hydrogel design, sensing mechanisms, and performance evaluation. A classification strategy based on signal modes and response orthogonality is proposed, along with a hierarchical intelligence framework covering passive response, adaptive regulation, and computational functions. Artificial intelligence further enables formulation optimization, structure-property prediction, and signal interpretation, accelerating the shift toward data-driven materials design. Emerging applications in wearable electronics, biosensing, and information encryption are discussed, while challenges including data scarcity, signal interference, and model interpretability are highlighted. Future efforts should focus on standardized databases, physics-informed modeling, and autonomous material discovery. This review provides insights into the rational design of advanced NC hydrogel sensors for next-generation flexible electronics.