Polymers with embedded dynamic bonds can form reversibly crosslinked networks that exhibit a range of exciting and functional material properties (e.g., self-healing or stimuli-responsive). Controlling the ordering and assembly of the dynamic bonds in these networks (a strategy ubiquitously employed by nature) provides an additional mechanism to tune material properties for targeted applications. Here, we report the design of linear, flexible polymer chains with periodically-placed and directional dynamic bonds that collectively assemble into supramolecular nanofibers. Interestingly, we only observe fiber formation in chains with an overall molecular weight (Mn) below the critical entanglement molecular weight (Mc). Moreover, despite longer chains exhibiting rapid terminal flow at elevated temperatures, we show that shorter chains when assembled into nanofibers exhibit delayed terminal flow by more than 100°C. We validate these experimental results with a general coarse-grained molecular dynamics simulation, independent of the specific chemistries used in this work, and discuss the thermodynamic and kinetic considerations related to this self-assembly process. We then expand upon the key molecular design principles to design a shape memory polymer with record-high energy density (18.9 MPa) based on the formation of strain-induced supramolecular nanostructures. While initially polymer chains adopt an amorphous structure (Mn &gt; Mc), during strain the polymer chains align and form strong directional dynamic bonds, which trap the stretched polymer chains in a highly elongated state. In all cases, we discuss how the interplay of molecular design and processing conditions can influence self-assembly. This work highlights the potential to use ordered supramolecular networks formed from polymers with well-defined backbone periodicity to enhance and control material properties.

Kinetically trapped or thermodynamically stable? Controlling self-assembly in periodic dynamic polymers for functional materials design

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ACS Fall 2022

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