Computational Study of Mechanochemical Activation in Nanostructured Triblock Copolymers.

Force-driven chemical reactions have emerged as an attractive platform for diverse applications in polymeric materials. However, the microscopic chain conformations and topologies necessary for efficiently transducing macroscopic forces to the molecular scale are not well-understood. In this work, we use a coarse-grained model to investigate the impact of network-like topologies on mechanochemical activation in self-assembled triblock copolymers. We find that mechanochemical activation during tensile deformation depends strongly on both the polymer composition and chain conformation in these materials. Activation primarily occurs in the tie chains connecting different glassy domains and in loop chains that are hooked onto each other by physical entanglements. Activation also requires a higher stress in materials having a higher glassy block content. Overall, the lamellar samples show the highest percent activation at high stress. In contrast, at low stress, the spherical morphology, which has the lowest glassy fraction, shows the highest activation. Additionally, we observe a spatial pattern of activation, which appears to be tied to distortion of the self-assembled morphology. Higher activation is observed in the tips of the chevrons formed during deformation of lamellar samples as well as in the centers between the cylinders in the cylindrical morphology. Our work shows that changes in the network-like topology in different morphologies significantly impact mechanochemical activation efficiencies in these materials, suggesting that this area will be a fruitful avenue for further experimental research.