Low-Threshold and High-Sensitivity Hierarchical Sensing Film Based on Janus Nanoparticles for Monitoring Liquid...

Constructing an effective, continuous network with a low percolation threshold is a key challenge for fabricating a high-sensitivity sensor. In this study, Janus nanoparticles (JNPs) with an asymmetric structure were synthesized in seeded emulsion polymerization and employed to stabilize graphene featuring hydrophobic surfaces to build the conductive network in one pot. Owing to the self-stratification induced by JNPs, the graphene was deposited autonomously at the bottom to achieve a hierarchical structure consisting of a conductive network layer, flexible stretchable layer, and a strongly bonded interface. Excitingly, the confined conductive network layer effectively reduced the percolation threshold to only 0.06 wt.%. Due to the ultra-thin and variable nature of the as-formed conductive network layer, the sensitivity of this stratified composite film ranged from 224 to 6205. Then, it was used to sensitively distinguish water droplets with different falling heights and masses. It provided an ideal low-cost approach for the commercial production of high-performance graphene-based sensors.