Natural lignocellulose fibers-based bio-dressing for accelerated wound healing and machine learning-assisted smart multimodal sensing

The integration of ultrasensitive smart human-machine interaction and well skin-like healing capabilities into the biomaterials-based dressing still remains great challenges. Herein, a sort of novel multifunctional lignocellulose dressing is proposed by combining ammonia-oxygen pretreatment with papermaking strategy, which promotes wound healing and achieves synchronous and resolvable self-powered quadruple sensing. In-situ aminated lignin within lignocellulose skeleton and the incorporated foreign natural tea polyphenols (TP) on outer wall synergistically enhanced the polarity of the lignocellulose, the optimized lignocellulose/TP TENG displayed the highest output performance, with the maximum output power of 210.43 mW/m², 890.72 % higher than that of pristine lignocellulose. Benefiting from the reinforced triboelectricity and abundant polar groups, the as-constructed bio-dressing is highly responsive to multiple stimuli with the assistance of machine learning, including pressure, humidity, and material types. Moreover, the unique three-dimensional interwoven networks of fibers and phenolic hydroxyl on TP endows the bio-dressing with high air permeability of 4.5 mm s⁻¹, excellent antibacterial and antioxidant properties, and high mechanical strength. After coating the lignocellulose-dressing, the wound recovery can be significantly accelerated within 12 days and the wound healing state can be monitored in single-electrode model. Our findings offered a reliable strategy to design and fabricate advanced biomaterials, boosting the development of future point-of-care applications. © 2025 Elsevier Ltd