Assembling graphene nanosheets into three dimensional aerogels has attracted considerable interest due to their unique properties and potential applications in many fields. Here, graphene aerogels constructed from interconnected graphene nanosheet-coated carbon fibers are fabricated by using cigarette filters as templates via a simple dip-coating method. The composite aerogels are ultralight (ρ = 7.6 mg cm⁻³) yet have high mechanical strength (0.07 MPa); when used as electromagnetic wave absorbers, they showed a minimum reflection loss value of −30.53 dB at 14.6 GHz and the bandwidth of reflection loss less than −10 dB (90% absorption) was 4.1 GHz. Furthermore, coating polypyrrole onto the composite aerogels can increase the minimum reflection loss value to −45.12 dB. Our results provide a promising approach to fabricate graphene-based composite aerogels with a strong electromagnetic wave absorption ability.

Electrical stimulation of shape-memory polymers (SMPs) has many advantages over thermal methods; creating an efficient conductive path through the bulk polymers is essential for developing high performance electroactive systems. Here, we show that a three-dimensional (3D) porous carbon nanotube sponge can serve as a built-in integral conductive network to provide internal, homogeneous, in situ Joule heating for shape-memory polymers, thus significantly improving the mechanical and thermal behavior of SMPs. As a result, the 3D nanocomposites show a fast response and produce large exerting forces (with a maximum flexural stress of 14.6 MPa) during shape recovery. We further studied the construction of a double-layer composite structure for bidirectional actuation, in which the shape change is dominated by the temperature-dependent exerting force from the top and bottom layer, alternately. An inchworm-type robot is demonstrated whose locomotion is realized by such bidirectional shape memory. Our large stroke shape-memory nanocomposites have promising applications in many areas including artificial muscles and bionic robots.