(649k) Segmental Dynamics of Poly(ethylene oxide) Rings in Melts Slightly Contaminated with Linear Analogues

Recent state-of-the-art measurements based on neutron spin echo experiments (Kruteva et al., 2020a) have suggested that the microscopic (segmental) dynamics of large ring molecules at scales below the elementary loop size follows quite well ring Rouse motion while at larger scales the dynamics is self-similar following the predictions of the self-consistent fractal loopy globule model (Ge et al., 2016). Motivated by these findings, we have employed molecular dynamics (MD) simulations with a rather accurate forcefield (Tsalikis and Mavrantzas, 2020) to probe microscopic dynamics in melts of ring poly(ethylene oxide) (PEO) melts, either pure or slightly contaminated with linear analogues. Our emphasis is on the effect of linear contamination on observables such as segmental dynamics, ring center-of-mass diffusivity, Kratky plots, and normalized single-chain dynamic structure factor that are experimentally accessible by techniques such as SANS (Kruteva et al. 2020b), NSE, and PFG-NMR (Kruteva et al, 2021). To enable a one-to-one comparison with such measured data, the simulations have been performed with PEO melts of exactly the same molar mass as those used in the experimental studies (i.e., between 10,000 and 40,000 g/mol). The mass fraction φ_­L of the linear contaminant has been kept below φ_­L= 0.1. In the simulations, we have accessed times on the order of several microseconds.

Segmental and diffusion dynamics are examined in terms of the mean square displacement of ring segments and entire chains, respectively. We have also computed the dynamic structure factor S(q,t) as well as the rate of decay of several autocorrelation functions probing dynamics at several length scales. The simulations indicate changes in all of these observables for melts of rings containing linear chains in mole fractions as low as φ_L= 0.03. For example, a linear contamination of φ_L= 0.05 seems to supress segmental and diffusion dynamics strongly. We also study how the linear contamination can induce dynamic heterogeneity in the melt due to threading events. This is examined by subjecting the accumulated MD trajectories to a detailed geometric analysis (Tsalikis et al., 2016) that helps identify ring-ring and ring-linear (Figure 1) penetrations and quantify their strength and characteristic time scales.

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