Quantifying the Impacts of Junction Functionality on Primary Loop Formation in Linear Polymers and Polymer Networks

Abstract

Abstract Most polymer networks formed from flexible precursors contain elastically inactive primary loops that significantly impact macroscopic material properties. While primary loop formation is known to decrease with increasing strand concentration and length, the role of junction functionality (f), defined by the number of strands connected to each junction, remains poorly understood. Here, we use network disassembly spectrometry (NDS) to experimentally quantify primary loops in end-linked poly(ethylene glycol) (PEG) networks with f = 3–6 as well as linear step-growth polymers (f = 2). Our results reveal that f governs the sensitivity of primary loop formation to synthesis conditions. Step-growth polymerizations (f = 2) show the strongest dependence, with 1° loop formation strongly suppressed at high concentrations and chain lengths. As f increases, sensitivity to concentration and chain length decreases progressively, showing an initial odd–even effect that plateaus at the highest functionality investigated (f = 6). Comparing against four different computational simulation algorithms, Kinetic Monte Carlo (KMC) simulations and Annable’s coarse-grained model are shown to agree best with NDS results. These findings establish junction functionality as a key parameter for engineering the cyclic topology of polymeric materials and provide experimental guidance that informs the selection of computational models for the design and prediction of polymer network topology in the future.