Mechanical robust and highly conductive composite hydrogel reinforced by a combination of cellulose nanofibrils/polypyrrole toward high-performance strain sensor

Although conductive and elastic materials are increasingly required for strain or stress sensing application in wearable electronic devices, it remains a great challenge to achieve outstanding and balanced mechanical performance while retaining high conductivity. Herein, the development of an ionic/electronic conductive hydrogel with mechanically robustness for strain sensors is reported. A covalently cross-linked polymer network is highly enhanced by a synergy of nano-enhancement (cellulose nanofibrils) and dynamic interactions containing hydrogen bonding and ionic coordination, which is used to support the mechanical structure of the hydrogel. By decorating with polypyrrole molecules via Fe3+ induced in-situ polymerization, the integrity of network structure is further improved by constructing physical interactions and chain entanglement. Therefore, compared to virgin poly(acrylamide-co-acrylic acid) hydrogel, the obtained hydrogel exhibits prominent mechanical performance containing high tensile strength (2.54 MPa) and ultra-high toughness (17.71 MJ m-3) along with remarkable stretchability (925%). Apart from Establishing a fair balance among mechanical parameters, a hybrid conductive path composed of ionic and electronic mechanism is also constructed simultaneously that results in an improved conductivity (995 mS m-1), wide working range (approximate to 873%) and high sensitivity (maximum gauge factor: 25.6). Thus, the combination of outstanding mechanical performance and sensitive strain response makes the conductive hydrogel prepared herein apply for mechanically reliable and flexible strain sensor that can monitor diverse mechanical deformation (e.g., human joint movement) reflected by real-time resistance variation. Clearly, this work provides a new perspective for the design and fabrication of advanced gel-based materials aiming at high performance in human motion detection.