Facile Preparation of a 3D Porous Aligned Graphene-Based Wall Network Architecture by Confined Self-Assembly with Shape Memory for Artificial Muscle, Pressure Sensor, and Flexible Supercapacitor.

Abstract

The development of a novel preparation strategy for 3D porous network structures with an aligned channel or wall is always in challenge. Herein, a 3D porous network composed of an aligned graphene-based wall is fabricated by a confined self-assembly strategy in which holey reduced graphene oxide (HrGO)/lignin sulfonate (Lig) composites are orientedly anchored on the framework of the Lig/single-wall carbon nanotube (Lig/SWCNT) hydrogel by vacuum-assisted filtration accompanied with confined self-assembly and followed with hydrothermal treatment. After freeze drying, the obtained ultralight Lig/SWCNT/HrGOal aerogel exhibits excellent shape memory properties and can roll back to the original shape even if suffering from a high compressive strain of 86.2%. Furthermore, the as-prepared aerogel used as a water-driven artificial muscle shows powerful driving force and can lift ultrahigh weight cargo that is 1030.6 times its own weight. When the prepared Lig/SWCNT/HrGOal aerogel is used as a pressure sensor, it also exhibits high sensitivity (2.28 kPa-1) and a wide detection region of 0.27-14.1 kPa. Additionally, the symmetric flexible supercapacitor assembled with as-prepared aerogel films shows superior stored energy performance that can tolerate 5000 cycles of bending. The present work not only fabricates a high-performance multifunctional material but also develops a new strategy for the preparation a wood-like 3D porous aligned wall network structure.