Recently, there is interest in triggering shape recovery of shape-memory polymers(SMPs) by novel non-external heating. In this paper, many hard works have been carried out to make SMP induced by solution. The main challenge in the development of such polymer systems is the conversion of solution-induced effects at the molecular level to macroscopic movement of working pieces. This paper presents a systematic study on the effects of solution on the glass transition temperature (Tg). The results reveal that the hydrogen bonding of shape memory polymer (SMP) was aroused by the absorbed solution that significantly reduces Tg of polymer. The mechanism behind it is solution firstly intenerates polymeric materials till the Tg of polymer lowered down to the temperature of ambient, then hydrogen bonding interaction improves the flexibility of polymeric macro-molecular chains. Thus, the shape memory effect (SME) can undergo solution-driven shape recovery. In addition, it provides a new approach that the SMP can be induced by applying non-energy stimulus. The Dynamic Mechanical Analyzer (DMA) results reveal that the modulus of polymer was softened gradually with immersion time increasing. The experimental result is approximate to the theory.

Graphene has been extensively explored to enhance functional and mechanical properties of metal matrix nanocomposites for wide-range applications due to their superior mechanical, electrical and thermal properties. This article discusses recent advances of key mechanisms, synthesis, manufacture, modelling and applications of graphene metal matrix nanocomposites. The main strengthening mechanisms include load transfer, Orowan cycle, thermal mismatch, and refinement strengthening. Synthesis technologies are discussed including some conventional methods (such as liquid metallurgy, powder metallurgy, thermal spraying and deposition technology) and some advanced processing methods (such as molecular-level mixing and friction stir processing). Analytical modelling (including phenomenological models, semi-empirical models, homogenization models, and self-consistent model) and numerical simulations (including finite elements method, finite difference method, and boundary element method) have been discussed for understanding the interface bonding and performance characteristics between graphene and different metal matrices (Al, Cu, Mg, Ni). Key challenges in applying graphene as a reinforcing component for the metal matrix composites and the potential solutions as well as prospectives of future development and opportunities are highlighted.