A Nanophase Separation Strategy toward Organohydrogel Fibrous Sensors with Ultralow Detection Limit and High Strain Sensitivity

Engineering high-performance stretchable fibrous organohydrogels is of significant importance for precise motion monitoring in next-generation flexible and wearable soft strain sensors due to their stability in various harsh environments. However, owing to the uniformly distributed ion carriers throughout the entire materials, they suffer from an unsatisfactory limit of detection for subtle deformations. Herein, we design an efficient nanophase separation strategy to endow organohydrogels with unevenly distributed and breakable hydrogen bonding networks, serving as pathways for ionic transport, for achieving ultralow-detection-limit and high-stretch-sensitivity fibrous organohydrogels. These fibers consist of poly(vinyl alcohol) (PVA), tetraaniline (TANI), ethylene glycol (EG), and water abbreviated as PTOHF and are prepared using a coaxial wet-spinning combined with an orientational freezing approach. Such a nanophase-separated network features a 28 nm amorphous nanophase rigidly cross-linked by 5 nm nanocrystalline domains. The breakable intermolecular hydrogen bonds in the physical fixed amorphous nanophase facilitate the formation of molecular-scale cracks for an ultralow detection limit (0.005%, 8 μm), while those in the nanocrystalline domains provide PTOHF with high strain sensitivity under large deformation, with gauge factor values of 7.0 at a strain of 180–300% at room temperature and 9.5 at a strain of 140–200% at −40 °C. As a result, as-prepared anti-freezing PTOHF not only enables the detection of human motion and the capture of high-quality pulse waves for real-time healthcare monitoring but also transmits Morse code by detecting the minor deformation of the metacarpophalangeal joints of the fingers. This study opens up a new avenue for designing and fabricating high-performance organohydrogel fibers tailored for precise motion monitoring in next-generation wearable soft strain sensors.