Demonstrates high sensitivity in wearable sensors, implying advancements in health monitoring technology.
MXene-based composite conductive aerogels have attracted considerable interest in wearable pressure-sensing applications owing to their large specific surface area and excellent electrical conductivity. However, insufficient structural regularity and mechanical stability continue to limit further improvements in the sensing performance. Here, an MXene/CNF/PVA/CNTs composite aerogel with a long-range ordered lamellar porous architecture was fabricated by integrating cellulose nanofibers (CNFs), poly(vinyl alcohol) (PVA), and carbon nanotubes (CNTs) through a bidirectional freezing strategy. Synergistic interactions among the multicomponent constituents enable the formation of well-defined hierarchical pore channels and continuous conductive networks, effectively suppressing MXene nanosheet restacking while enhancing the structural stability. Benefiting from this regulated microarchitecture, the resulting aerogel exhibits an ultralow density, excellent compressibility, high-pressure sensitivity, as well as fast and stable electrical responses. On this basis, a wearable pressure sensor was constructed that enabled high-fidelity acquisition of complex gestures and diverse physiological signals. Furthermore, combined with machine learning algorithms, the sensor system achieves intelligent recognition and abnormal discrimination of sleep-related breathing states, highlighting the potential of this material platform for high-sensitivity, intelligent wearable sensing and health-monitoring applications.
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Shen et al. (2026) studied this question.
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