We present a general strategy for enabling reversible shape transformation in semicrystalline shape memory (SM) materials, which integrates three different SM behaviors: conventional one-way SM, twoway reversible SM, and one-way reversible SM. While two-way reversible shape memory (RSM) is observed upon heating and cooling cycles, the one-way RSM occurs upon heating only. Shape reversibility is achieved through partial melting of a crystalline scaffold which secures memory of a temporary shape by leaving a latent template for recrystallization. This behavior is neither mechanically nor structurally constrained, thereby allowing for multiple switching between encoded shapes without applying any external force, which was demonstrated for different shapes including hairpin, coil, origami, and a robotic gripper. Fraction of reversible strain increases with cross-linking density, reaching a maximum of ca. 70%, and then decreases at higher cross-linking densities. This behavior has been shown to correlate with efficiency of securing the temporary shape.

Networks and gels are part of our everyday experience starting from automotive tires and rubber bands to biological tissues and cells. Biological and polymeric networks show remarkably high deformability at relatively small stresses and can sustain reversible deformations up to 10 times their initial size. A distinctive feature of these materials is highly nonlinear stress−strain curves leading to material hardening with increasing deformation. This differentiates networks and gels from conventional materials, such as metals and glasses, showing linear stress−strain relationship in the reversible deformation regime. Using theoretical analysis and molecular dynamics simulations, we propose and test a theory that describes nonlinear mechanical properties of a broad variety of biological and polymeric networks and gels by relating their macroscopic strain-hardening behavior with molecular parameters of the network strands. This theory provides a universal relationship between the strain-dependent network modulus and the network deformation and explains strain-hardening of natural rubber, synthetic polymeric networks, and biopolymer networks of actin, collagen, fibrin, vimentin, and neurofilaments.

Polymer nanocomposites (PNCs) are important materials that are widely used in many current technologies and potentially have broader applications in the future due to their excellent property tunability, light weight, and low cost. However, expanding the limits in property enhancement remains a fundamental scientific challenge. Here, we demonstrate that well-dispersed, small (diameter ∼1.8 nm) nanoparticles with attractive interactions lead to unexpectedly large and qualitatively different changes in PNC structural dynamics in comparison to conventional nanocomposites based on particles of diameters ∼10-50 nm. At the same time, the zero-shear viscosity at high temperatures remains comparable to that of the neat polymer, thereby retaining good processability and resolving a major challenge in PNC applications. Our results suggest that the nanoparticle mobility and relatively short lifetimes of nanoparticle-polymer associations open qualitatively different horizons in the tunability of macroscopic properties in nanocomposites with a high potential for the development of advanced functional materials.

We have developed a new model of nanoparticle adhesion which explicitly takes into account the change in the nanoparticle surface energy. Using combination of the molecular dynamics simulations and theoretical calculations we have showed that the deformation of the adsorbed nanoparticles is a function of the dimensionless parameter beta proportional, variant gamma(p)(GR(p))(-2/3)W(-1/3), where G is the particle shear modulus, R(p) is the initial particle radius, gamma(p) is the polymer interfacial energy, and W is the particle work of adhesion. In the case of small values of the parameter beta < 0.1, which is usually the case for strongly cross-linked large nanoparticles, the particle deformation can be described in the framework of the classical Johnson, Kendall, and Roberts (JKR) theory. However, we observed a significant deviation from the classical JKR theory in the case of the weakly cross-linked nanoparticles that experience large shape deformations upon particle adhesion. In this case the interfacial energy of the nanoparticle plays an important role controlling nanoparticle deformation. Our model of the nanoparticle adhesion is in a very good agreement with the simulation results and provides a new universal scaling relationship for nanoparticle deformation as a function of the system parameters.

No abstract