Asymmetric Effects Underlying Dynamic Heterogeneity in Miscible Blends of Poly(methyl methacrylate) with Poly(ethylene oxide)

TL;DR

This study uses all-atom MD to dissect dynamic heterogeneity in miscible PEO/PMMA blends across the full composition range and multiple temperatures. By linking local composition, free volume, and Rouse-mode relaxation, the authors reveal an asymmetric coupling: PEO mobility is highly sensitive to local PMMA environments and free-volume heterogeneity, while PMMA dynamics resemble a more uniform, $T_ ext{g}$-driven response and are less perturbed by local compositional fluctuations. Rouse-mode analysis shows PEO relaxation can approach neat-like behavior in PEO-rich domains, whereas PMMA experiences a composition-dependent uniform acceleration, suggesting a nanoscale facilitation of PMMA by PEO. The work provides a molecular framework connecting nanoscale heterogeneity to macroscopic dynamical asymmetry, with potential generalization to other flexible–rigid polymer pairs and guidance for tuning viscoelastic and transport properties via blend composition and morphology.

Abstract

The emergence of spatially variable local dynamics, or dynamic heterogeneity, is common in multicomponent polymer systems. Although often attributed to differences in the intrinsic dynamics of each component, the molecular origin of their coupling and its dependencies remain unclear. Here, we use molecular dynamics simulations of polyethylene oxide (PEO)/poly(methyl methacrylate) (PMMA) blends, across the full range of compositions and multiple thermal regimes, to characterize local fluctuations and sub-chain relaxations for both PEO and PMMA. By constructing probability distributions of local composition and computing entropic measures, we connect nanoscale heterogeneity to differences in mobility between PEO and PMMA, extending beyond mean-field treatments. While PMMA segmental fluctuations in blends broadly align with $T_\text{g}$-equivalent neat PMMA systems, PEO exhibits enhanced mobility correlated with increased free volume and broader, more diverse local compositions upon blending. Rouse-mode analysis, used to probe relaxation dynamics over different length scales, shows that PEO relaxation approaches neat-like behavior in PEO-rich domains, whereas PMMA relaxation accelerates uniformly across all mode numbers. Given the local mobility enhancement of PMMA by PEO, this uniform shift suggests a nanoscale facilitation process that extends PEO's influence beyond its immediate environment. These findings link the statistics of local compositional heterogeneity to dynamic asymmetry across length scales, provide physical insight into the behavior of this archetypal blend system, and establish a framework for analyzing dynamic coupling in others.

Figures (5)

• Figure 1: Dependence of apparent glass transition temperature ($T_\text{g}$) on blend composition. Markers represent simulated (filled) and experimental (empty) $T_\text{g}$ values for blends of PEO and PMMA. Experimental results are from Ref. wu1987 . Solid black lines are fits to the Fox equation. Error bars reflect standard errors calculated from three independent system configurations. Horizontal, colored bands provide visual reference to 500 K (red), 360 K (purple), and 220 K (blue), which are examined in subsequent figures. The color gradation within each band distinguishes blends at the same temperature but different compositions.
• Figure 2: Variation in relative segmental mobility based on local environment. Deviations for neat-polymer mobility for PEO at (A) 220 K, (B) 360 K, and (C) 500 K and for PMMA at (D) 220 K, (E) 360 K, and (F) 500 K. Data is shown for all blend compositions, with gradation from light (PMMA-rich) to dark (PEO-rich), as indicated by the color bars. Results for chains in blends with the most extreme compositions ($x^\text{(PEO)}=0.1$ and $0.9$) are outlined in black for visual clarity. Error bars reflect standard errors from three independent systems. Horizontal dashed lines provide a guide to the eye for the neat-polymer mobility. The gray shaded area around the dashed lines reflect standard deviations calculated from three independent neat systems.
• Figure 3: Characterization of local composition distributions around PEO. (A) Probability distributions of intermolecular PMMA volume fraction around PEO and (B) corresponding normalized Shannon entropies. Results are shown for systems at 500 K. The color gradient corresponds to a gradient in blend composition containing the most PEO (dark) to the least PEO (light). The dashed red line is provided as a guide to the eye.
• Figure 4: Characterization of local composition distributions for PMMA. (A) Probability distributions of intermolecular PMMA volume fraction around PMMA and (B) corresponding normalized Shannon entropies. Results are shown for systems at 500 K. The color gradient corresponds to a gradient in blend composition containing the most PEO (dark) to the least PEO (light). The black dashed line in (A) is the distribution of neat PMMA. The red dashed line in (B) is provided as a guide to the eye.
• Figure 5: Rouse mode analysis at 500 K for chains in blends of varying composition. The effective Rouse relaxation time $\tau^{\text{eff}}_p$ as a function of sub-chain length $N/p$ for (A) PEO and (B) PMMA. For $p>8$, symbols for data are only shown for every third value of $p$ for visual clarity. Dashed black lines are a guide to the eye to indicate the expected ideal scaling of $\tau_p \sim p^{-2}$. The position of the line is the same across panels and is set to align with the behavior of neat PEO. Results for chains in blends with the most extreme compositions are outlined in black for visual clarity of trends. Error bars reflect standard errors from three independent systems and are generally smaller than the symbol size. Transparent markers are used for $p$ corresponding to sub-chains equal to or less than an estimated Kuhn length. Deviations from the ideal $p^{-2}$ scaling are expected for modes shorter than the Rouse bead size, which is generally larger than a Kuhn length.