Carbon aerogels demonstrate wide applications for their ultralow density, rich porosity, and multifunctionalities. Their compressive elasticity has been achieved by different carbons. However, reversibly high stretchability of neat carbon aerogels is still a great challenge owing to their extremely dilute brittle interconnections and poorly ductile cells. Here we report highly stretchable neat carbon aerogels with a retractable 200% elongation through hierarchical synergistic assembly. The hierarchical buckled structures and synergistic reinforcement between graphene and carbon nanotubes enable a temperature-invariable, recoverable stretching elasticity with small energy dissipation (~0.1, 100% strain) and high fatigue resistance more than 10⁶ cycles. The ultralight carbon aerogels with both stretchability and compressibility were designed as strain sensors for logic identification of sophisticated shape conversions. Our methodology paves the way to highly stretchable carbon and neat inorganic materials with extensive applications in aerospace, smart robots, and wearable devices.

A computationally efficient mode space simulation method for atomistic simulation of a graphene nanoribbon field-effect transistor in the ballistic limits is developed. The proposed simulation scheme, which solves the nonequilibrium Green’s function coupled with a three dimensional Poisson equation, is based on the atomistic Hamiltonian in a decoupled mode space. The mode space approach, which only treats a few modes (subbands), significantly reduces the simulation time. Additionally, the edge bond relaxation and the third nearest neighbor effects are also included in the quantum transport solver. Simulation examples show that the mode space approach can significantly decrease the simulation cost by about an order of magnitude, yet the results are still accurate. This article also demonstrates that the effects of the edge bond relaxation and the third nearest neighbor significantly influence the transistor’s performance and are necessary to be included in the modeling.

Highly sensitive wearable strain sensors based on graphene and its derivatives have shown great potential to be applied in home monitoring and electronic skin. To date, it still remains a technical challenge to achieve a reliable performance with high responsiveness at a small elastic strain for graphene strain sensors. Here we demonstrate the fabrication of micro/nanocrack-based strain sensors by using a porous thin film composed of graphene nanowalls (GNWs), which showed ultrahigh sensitivity with a gauge factor up to ≈8.6 × 10⁴ at 4% strain. The ultrahigh gauge factor at such a small deformation can be attributed to the synergistic effect of micro/nanocrack evolution of GNW building blocks derived from the substrate's Poisson's ratio effect. This working mechanism is distinct from the general case where the cracks were created in an initially continuous film. The wearable GNW strain sensors were functionally presented as audio analog-to-digital converters for acoustic signature recognition and electronic skin devices to monitor physiological signals from the human body at high resolution.