Phase behavior of AB/CD diblock copolymer blends via coarse-grained simulation

The phase diagram of equimolar blends of AB and CD diblock copolymers has been studied using dissipative particle dynamics. All unlike blocks interacted with the same χ, except for the B-C interaction, for which χ_BC < 0 in order to prevent macrophase separation. The BC interaction was able to prevent macrophase separation except for low volume fractions of B and C (φ_BC⪅ 0.1) and relatively equal fractions of A and D. For high φ_BC (φ_BC⪆ 0.92), a disordered state was obtained. For all microphase separated states the shapes/morphologies were described by the ratios of the eigenvalues of the radius of gyration tensor and their sphericity. These were used to classify the domains as forming sphere, cylinders, lamellae, or branched/gyroidal structures. For φ_BC < 0.5 the BC domains acted as an interfacial region which compatibilized the A and D domains, while for φ_BC > 0.5 the BC domain filled in the space between A and D domains. Several interesting structures were formed including a novel connected/branched spheres morphology, hierarchical lamellae, concentric spheres/cylinders, and a combination of cylinders/lamellae. Comparisons are made with the linear diblock and linear triblock phase diagrams.

High enthalpy storage thermoset network with giant stress and energy output in rubbery state

Low output in stress and energy in rubbery state has been a bottleneck for wide-spread applications of thermoset shape memory polymers (SMPs). Traditionally, stress or energy storage in thermoset network is through entropy reduction by mechanical deformation or programming. We here report another mechanism for energy storage, which stores energy primarily through enthalpy increase by stretched bonds during programming. As compared to entropy-driven counterparts, which usually have a stable recovery stress from tenths to several MPa and energy output of several tenths MJ/m³, our rubbery network achieved a recovery stress of 17.0 MPa and energy output of 2.12 MJ/m³ in bulk form. The giant stress and energy release in the rubbery state will enhance applications of thermoset SMPs in engineering structures and devices.

Body temperature-responsive two-way and moisture-responsive one-way shape memory behaviors of poly(ethylene glycol)-based networks

In this work, crosslinked shape-memory polymer networks were prepared by thermally induced free-radical polymerizations of methacrylate-terminated poly(ethylene glycol) (PEG) and n-butyl acrylate (BA), which integrate thermal-responsive two-way and moisture-responsive one-way shape memory effects (SME).

Cyclic behaviors of amorphous shape memory polymers

Cyclic loading conditions are commonly encountered in the applications of shape memory polymers (SMPs), where the cyclic characteristics of the materials determine their performance during the service life, such as deformation resistance, shape recovery speed and shape recovery ratio. Recent studies indicate that in addition to the physical damage or some other irreversible softening effects, the viscoelastic nature could also be another possible reason for the degraded cyclic behavior of SMPs. In this paper, we explore in detail the influence of the viscoelastic properties on the cyclic tension and shape memory (SM) behavior of an epoxy based amorphous thermosetting polymer. Cyclic experiments were conducted first, which show that although the epoxy material does not have any visible damage or irreversible softening effect during deformation, it still exhibits obvious degradation in the cyclic tension and SM behaviors. A linear multi-branched model is utilized to assist in the prediction and understanding of the mechanical responses of amorphous SMPs. Parametric studies based on the applied model suggest that the shape memory performance can be improved by adjusting programming and recovery conditions, such as lowering the loading rate, increasing the programming temperature, and reducing the holding time.

Shape Memory Assisted Self-Healing Coating

In this communication, we report the preparation and characterization of new shape memory assisted self-healing (SMASH) coatings. The coatings feature a phase-separated morphology with electrospun thermoplastic poly(ε-caprolactone) (PCL) fibers randomly distributed in a shape memory epoxy matrix. Mechanical damage to the coating can be self-healed via heating, which simultaneously triggers two events: (1) the shape recovery of the matrix to bring the crack surfaces in spatial proximity, and (2) the melting and flow of the PCL fibers to rebond the crack. In controlled healing experiments, damaged coatings not only heal structurally, but also functionally by almost completely restoring the corrosion resistance. We envision the wide applicability of the SMASH concept in designing the next-generation self-healing materials.

Healable thermoset polymer composite embedded with stimuli-responsive fibres

Severe wounds in biological systems such as human skin cannot heal themselves, unless they are first stitched together. Healing of macroscopic damage in thermoset polymer composites faces a similar challenge. Stimuli-responsive shape-changing polymeric fibres with outstanding mechanical properties embedded in polymers may be able to close macro-cracks automatically upon stimulation such as heating. Here, a stimuli-responsive fibre (SRF) with outstanding mechanical properties and supercontraction capability was fabricated for the purpose of healing macroscopic damage. The SRFs and thermoplastic particles (TPs) were incorporated into regular thermosetting epoxy for repeatedly healing macroscopic damages. The system works by mimicking self-healing of biological systems such as human skin, close (stitch) then heal, i.e. close the macroscopic crack through the thermal-induced supercontraction of the SRFs, and bond the closed crack through melting and diffusing of TPs at the crack interface. The healing efficiency determined using tapered double-cantilever beam specimens was 94 per cent. The self-healing process was reasonably repeatable.