A light/thermal cascaded-driven equipment for machine recognition inspired by water lilies using as multifunctional soft actuator.

[Display omitted] • A bilayer actuator was bionically designed by imitating the structure of water lily. • An efficient actuator with a unique light/thermal response mechanism was constructed. • The smart soft actuator was integrated with machine recognition capability. • Multiple networks and the MXene were synergized to enhance mechanical properties. Inspired by the natural stimulus–response of plants and animals, a range of soft equipment has been extensively developed and used in intelligent human–computer interaction, editable remote drives, and machine learning. Poly(N-isopropyl acrylamide) (PNIPAM) hydrogels have gained popularity thanks to their low phase transition temperature and excellent flexibility. However, the PNIPAM hydrogels suffer from poor mechanical properties, low electrical conductivity, and lack of self-responsiveness. Herein, a bilayer light/thermal cascaded-driven anisotropic poly acrylamide/poly(N-isopropylacrylamide-co-acrylamide)-polyvinyl alcohol-MXene (P/PP-M) actuator was prepared by a simple two-step polymerization method. The unique bionic light/thermal response mechanism enables rapid conversion of energy forms and the construction of remote editable actuators. Concretely, the mechanical properties of hydrogels (strain: 1014 %, stress: 94 KPa) have been greatly improved by copolymerizing MXene nanosheets and multiplex hydrogels through two-by-two interpenetrating molecular chains. MXene nanosheets formed dynamic networks conferring the hydrogel system with high conductivity and light/thermal conversion efficiency. The P/PP-M soft actuator features high sensitivity (Gauge factor = 3.62), fast response time (400 ms), and cycling durability (>500 cycles). Finally, the energy transfer mechanism from light to thermal energy to kinetic energy was corroborated by preparing a series of bionic equipment. Manual clips were prepared on this basis, which enables the transportation of objects and realizes the real-time reflection of the operating status of remotely driven soft manual clips through changes in electrical signals. Thus, the proposed efficient editable remote-driven machine recognition soft equipment provides new insights for developing intelligent flexible robots and wearable smart devices. [ABSTRACT FROM AUTHOR]