Microscopic Structure, Conformation, and Dynamics of Ring and Linear Poly(ethylene oxide) Melts from Detailed Atomistic Molecular Dynamics Simulations: Dependence on Chain Length and Direct Comparison with Experimental Data

Tsalikis, Dimitrios G.; Koukoulas, Thanasis; Mavrantzas, Vlasis G.; Pasquino, Rossana; Vlassopoulos, Dimitris; Pyckhout‐Hintzen, Wim; Wischnewski, A.; Monkenbusch, M.; Richter, D.

doi:10.1021/acs.macromol.6b02495

Cited by 57 publications

(90 citation statements)

References 51 publications

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“…Our conjecture is therefore that τ 1 and τ 2 are associated with the fast loop relaxation dynamics and the slower loop migration mechanism, respectively. Atomistic simulations have also shown [20] that the saturation times for loop dynamics increase substantially with the M w of the ring, which is fully consistent with the differences observed in the values of τ 1 and τ 2 between R-2k and R-5k melts. Another important remark is that the three individual characteristic relaxation times τ 1 , τ 2 and τ 3 exhibit an almost quadratic dependence on M w .…”

Section: Systemsupporting

confidence: 81%

“…We further hypothesize that the two faster relaxation modes (i = 1 and i = 2) are related to the early time motion of the loops formed by small segments along the ring molecule as, e.g., is visualized by the lattice animal picture model [28,29]). Indeed, SANS measurements [30] validated by MD simulations [20] have revealed that at short times the dynamics of rings are governed by the internal relaxation dynamics of such loops, while at intermediate time scales loop migration prevails. At times on the order of the Rouse relaxation time, these contributions get saturated, and the translational motion of the entire molecule starts dominating ring dynamics [30].…”

Section: Systemmentioning

confidence: 99%

“…For each one of these systems, we simulated mixtures at molar fraction ϕ L of the L component in the range between 0.1 and 0.7 (see Table 1). The MD simulations were performed with GROMACS [17] using the modified TraPPE (=Transferable Potential for Phase Equilibria) united-atom (UA) force field [18,19] for which several simulations in the last years have shown that it can predict quite accurately the equilibrium conformation and dynamics of PEO rings both in their pure melts and in blends with linear analogs judging from their comparison against experimentally measured data with state-of-the-art techniques [14,16,20].…”

Section: Systems Studied and Simulation Detailsmentioning

confidence: 99%

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Dynamic Heterogeneity in Ring-Linear Polymer Blends

et al. 2020

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We present results from a direct statistical analysis of long molecular dynamics (MD) trajectories for the orientational relaxation of individual ring molecules in blends with equivalent linear chains. Our analysis reveals a very broad distribution of ring relaxation times whose width increases with increasing ring/linear molecular length and increasing concentration of the blend in linear chains. Dynamic heterogeneity is also observed in the pure ring melts but to a lesser extent. The enhanced degree of dynamic heterogeneity in the blends arises from the substantial increase in the intrinsic timescales of a large subpopulation of ring molecules due to their involvement in strong threading events with a certain population of the linear chains present in the blend. Our analysis suggests that the relaxation dynamics of the rings are controlled by the different states of their threading by linear chains. Unthreaded or singly-threaded rings exhibit terminal relaxation very similar to that in their own melt, but multiply-threaded rings relax much slower due to the long lifetimes of the corresponding topological interactions. By further analyzing the MD data for ring molecule terminal relaxation in terms of the sum of simple exponential functions we have been able to quantify the characteristic relaxation times of the corresponding mechanisms contributing to ring relaxation both in their pure melts and in the blends, and their relative importance. The extra contribution due to ring-linear threadings in the blends becomes immediately apparent through such an analysis.

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Section: Systemsupporting

confidence: 81%

Section: Systemmentioning

confidence: 99%

Section: Systems Studied and Simulation Detailsmentioning

confidence: 99%

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Dynamic Heterogeneity in Ring-Linear Polymer Blends

et al. 2020

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“…Simulations and later measurements have uncovered another surprise about ring melts quantified by the mass scaling exponent ν for the radius of gyration, R g . The “Flory theorem,” stating that polymers in the melt are nearly “ideal,” in the specific sense that they should have similar excluded volume (EV) interactions as polymers at their theta point, i.e., ν = 1/2, simply does not hold for ring melts.…”

Section: Introductionmentioning

confidence: 99%

Relation between Polymer Conformational Structure and Dynamics in Linear and Ring Polyethylene Blends

Jeong

Douglas

2017

Macro Theory & Simulations

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Flory theorem," stating that polymers in the melt are nearly "ideal," [28] in the specific sense that they should have similar excluded volume (EV) interactions as polymers at their theta point, i.e., ν = 1/2, simply does not hold for ring melts. Instead, ν for ring melts has often been reported to be near 2/5 [11,12,21,24] which is consistent with the theoretical estimate of Cates and Deutsch. [29] Recent computational studies [16][17][18]30,31] have suggested that very long rings in the melt should be in a collapsed globular state for which ν equals 1/3. On the other hand, Lang et al. [32] have argued for a value of ν = 3/8 for high mass rings, an exponent close, but not equal to the value for collapsed chains. Despite the uncertainty in the exact exponent value, it seems safe to conclude that ν is significantly less than 1/2 so that the conformation of melt rings does not conform to random walk (RW) chains with screened excluded volume interactions.The absence of screening of excluded volume in rings implies that the addition of solvents and linear polymers to ring melts should lead to different effects than adding these molecular species to linear polymer chain melts. This phenomenon has been considered in previous work, [33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48] but the nature of this swelling process is not yet entirely clear, and the present work is devoted to further elucidating this problem from a new perspective not relying on the reptation model. There have admittedly been numerous arguments, [29,33,34] experiments, [33][34][35][36][37][38][39][40][41] and simulations [42][43][44][45][46][47][48] pertaining to the configurational properties and dynamics of rings diluted by linear chains. Originally, Cates and Deutsch [29] suggested that the topologically induced EV interactions in the ring melt are relieved upon diluting the rings by linear chains so that the rings in the melt should become "ideal" upon dilution by linear chains. Recent simulations [44][45][46][47][48] and experiments [40,41] on ring-linear polymer blends have reported that rings increase their size upon the dilution and their conformational structure resembles ideal rings in a theta solvent, clearly supporting a change in the EV interactions in ring melts upon adding linear chains. Moreover, the rate of diffusion of tracer ring polymers in the melt was found to be greatly slowed by adding linear chains, an effect interpreted as arising from the ring-linear polymer threadings. [33,[35][36][37][38][39]43,48] Although there have been many attempts at quantifying this physically appealing "threading effect," [7,[35][36][37][38][43][44][45][46]48] the validity of the threading model has not yet been established. In this communication, we consider an alternative explanation of the slowing down of Ring-Linear Chain BlendsAtomistic molecular dynamics simulations of ring-linear polyethylene blends are employed to understand the relationship between chain conformational structure and the melt dynamics of these blends. As o...

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“…Moreover, the PEO is technically important in many fields. As one consequence, various PEO systems (including melts, solutions, blends, and composites) have been extensively studied using AA MD simulations. In particular, I have previously simulated glass transition behaviors of various PEO systems (bulks, films, and isolated chain), validating the employed force field .…”

Section: Computational Detailsmentioning

confidence: 99%

Multiscale Modeling Scheme for Simulating Polymeric Melts: Application to Poly(Ethylene Oxide)

2017

Macro Theory & Simulations

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polyolefins, from which the volumetric expansive coefficients and glass transition temperatures (T g ) could be determined. Up to now, this method has been extensively applied to complex polymers, [4] including dendrimers [5,6] and crosslinked networks, [7,8] to examine effects of various factors (i.e., molecular weight, [9] tacticity, [10] confinement [11] ) on the volumetric properties.However, in order to achieve repeatable results, adequate thermodynamics equilibrium should be usually attained in these AA MD simulations. Although a great variety of schemes have been proposed to improve the sampling efficiency, restrained by the current computational power, the productive AA MD simulations are only generally suitable for investigating short-term behaviors of small short-chain polymer (namely, oligomer) systems. To study specific polymer systems at the wide timeand space-scales, one of quite promising schemes is multiscale modeling, which groups every AA segment into one super-atom or coarse-grained (CG) bead. [12,13] In this scheme, it is critical to obtain the "potential energy" (referred to free energy or potential of mean force in most cases) that can accurately describe chain structure and interbead interactions. [14,15] Numerous CG methods have been developed, [16] among which most typical ones include iterative Boltzmann inversion (IBI), [17] force match, [18][19][20] inverse Monte Carlo, [21] conditional reversible work (CRW), [22,23] and MARTINI, [24] etc. Mainly, these methods differ in the target functions that are used to parameterize the nonbonded CG potentials. For example, the IBI method [17] adopts the structural distributions, the CRW method [22] uses the interaction free energy, and the MARTINI method [24] aims to reproduce the partitioning free energies.In general, the CG potentials parameterized until now suffer from representability and transferability. [16,25,26] Namely, even at the same state as the parameterized one with some properties, simulations with these CG potentials cannot reproduce other properties; and CG potentials that are parameterized at some state cannot reliably be used at other states. In order to improve the predictive power of CG simulations, numerous studies have been carried out during the past decade. Here only some of typical ones are mentioned. As one of early works, Qian et al. [27] modified the IBI potentials by a temperature factor to reproduce the thermal expansion coefficients over a broad range of temperature. This method was called one-point extrapolation Multiscale SimulationsThe poly(ethylene oxide) (PEO) is employed as one typical example to demonstrate a new multiscale modeling scheme for simulating high-molecularweight polymeric melts. In this scheme, the structural distributions and the densities at five elevated temperatures at 1 atm, which are obtained from molecular dynamics (MD) simulations of all-atomistic oligomeric melt, are employed as the target functions to parameterize the coarse-grained (CG) potentials. The extensive CG MD simulations rep...

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Microscopic Structure, Conformation, and Dynamics of Ring and Linear Poly(ethylene oxide) Melts from Detailed Atomistic Molecular Dynamics Simulations: Dependence on Chain Length and Direct Comparison with Experimental Data

Cited by 57 publications

References 51 publications

Dynamic Heterogeneity in Ring-Linear Polymer Blends

Dynamic Heterogeneity in Ring-Linear Polymer Blends

Relation between Polymer Conformational Structure and Dynamics in Linear and Ring Polyethylene Blends

Multiscale Modeling Scheme for Simulating Polymeric Melts: Application to Poly(Ethylene Oxide)

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