No abstract

A hierarchical (triple scale) simulation methodology is presented for the prediction of the dynamical and rheological properties of high molecular-weight entangled polymer melts. The methodology consists of atomistic, moderately coarse-grained (mCG), and highly coarse-grained slip-spring (SLSP) simulations. At the mCG level, a few chemically bonded atoms are lumped into one coarse-grained bead. At this level, the chemical identity of the underlying atomistic system and the interchain topological constraints (entanglements) are preserved. The mCG interaction potentials are derived by matching local structural distributions of the mCG model to those of the atomistic model through iterative Boltzmann inversion. For matching mCG and atomistic dynamics, the mCG time is scaled by a time scaling factor, which compensates for the lower monomeric friction coefficient of the mCG model than that of the atomistic one. At the SLSP level, multiple Kuhn segments of a polymer chain are represented by one coarse-grained bead. The very soft nonbonded interactions between beads do not prevent chain crossing and, hence, can not capture entanglements. The topological constraints are represented by slip-springs, restricting the lateral motion of polymer chains. A compensating pair potential is used in the SLSP model to keep the static macromolecular properties unaltered upon the introduction of slip-springs. The static and kinetic parameters of the SLSP model are determined based on the lower-level simulation models. Particularly, matching the orientational autocorrelation of the end-to-end vector, we determine the number of slip-springs and calibrate the timescale of the SLSP model. As a test case, the hierarchical methodology is applied to cis-1,4-polybutadiene (cPB) at 413 K. Dynamical single-chain and linear viscoelastic properties of cPB melts are calculated for a broad range of molecular weights, ranging from unentangled to well-entangled chains. The calculations are compared, and found in good agreement, with experimental data from the literature.

We present large-scale computer simulations of entangled polymers with symmetric star-like and Cayley tree-like architectures. Unlike the usual observation for repational behaviour of linear chains, the simulated systems exhibit a strong dispersion, over several decades, of the relaxation times after the local reptative ('Rouse in tube') regime. Relaxation is dramatically slowed down by approaching the branch point from the outer segments. This is consistent with the expected retraction mechanism for strongly entangled branched polymers. In order to describe fluctuations around the branch point, we introduce a Rouse-like model adapted to star-like polymers and incorporate entanglements by means of localizing springs. Model predictions for localization of the branch point are compared with simulations with fixed arm ends, which suppress retraction and tube dilution. Strikingly, the simulations reveal a localization of the branch point weaker than expected. This suggests the presence of early constraint-release effects that are not captured by the standard mechanism of tube dilution. We quantify, as a function of time, the strength of such effects and the fraction of relaxed material directly from the simulations with free ends. This allows us to renormalize the tube diameter and entanglement time in our model as time-dependent quantities. With this renormalization, the model provides an excellent description of the early relaxation of the branch point.

We present computer simulations of concentrated solutions of unknotted nonconcatenated semiflexible ring polymers. Unlike in their flexible counterparts, shrinking involves a strong energetic penalty, favoring interpenetration and clustering of the rings. We investigate the slow dynamics of the centers-of-mass of the rings in the amorphous cluster phase, consisting of disordered columns of oblate rings penetrated by bundles of prolate ones. Scattering functions reveal a striking decoupling of self- and collective motions. Correlations between centers-of-mass exhibit slow relaxation, as expected for an incipient glass transition, indicating the dynamic arrest of the cluster positions. However, self-correlations decay at much shorter time scales. This feature is a manifestation of the fast, continuous exchange and diffusion of the individual rings over the matrix of clusters. Our results reveal a novel scenario of glass formation in a simple monodisperse system, characterized by self-collective decoupling, soft caging, and mild dynamic heterogeneity.

Single-chain nanoparticles (SCNPs) constructed via reversible bonds are versatile stimuli-responsive soft nanoobjects with potential use in nanomedicine, bioimaging, biosensing and catalysis applications. In recent years, many different types of reversible SCNPs have been reported involving intra-chain hydrogen bonding, host-guest interactions and metal complex formation, among other reversible bonds. As illustrated in this work, reversible SCNPs in solution with similar nature, molar mass and amount of reactive groups than irreversible (covalentbonded) SCNPs display, on average, a lower level of chain compaction. We follow herein a Flory-like argument to obtain a simple expression providing the expected size reduction upon folding single chains of size R 0 to SCNPs of size R with reversible interactions. Accurate estimation of R is of outmost importance for developing practical applications of responsive SCNPs based on structure-property relationships. For precursor chains having a fraction of groups x involved in reversible bonds, the expected size upon intra-chain folding of the precursor chains to SCNPs is given by R = R 0 (1 − x) 0.6. We perform a comparison of the size reduction predicted by the former expression with extensive literature data for SCNPs constructed via reversible bonds (65 SCNPs, 16 reversible interactions). The overall agreement between theoretical and experimental data is excellent, hence allowing a valuable a priori estimation of the size reduction upon folding single chains to single-chain nanoparticles via reversible interactions.