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Persistence Length, End-to-End Distance, and Structure of Coarse-Grained Polymers

机译:持久长度,端到端距离和粗粒聚合物的结构

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Coarse-grained (CG) polymer simulations can access longer times and larger lengths than all-atom (AA) molecular dynamics simulations; however, not all CG models correctly reproduce polymer properties on all length scales. Here we coarse-grain atomistic position data from polyethylene (PE) and polytetrafluoroethylene (PTFE) melt simulations by combining A backbone carbon atoms in a single CG bead. Resulting CG variables have correlations along the chain backbone that depend on the coarse-graining scale A and are generally not reproduced by independent bond-length, bond-angle and torsion-angle distributions. By constructing distributions of CG variables equivalent to those from simulated CG potentials we are able to evaluate the bond orientation correlation for different CG models at reduced computational cost. CG models and potentials that include only nonbonded, bond-length, and bond-angle interactions computed by Boltzmann inversion correctly reproduce the CG variable distributions but do not necessarily reproduce the chain stiffness, overestimating the persistence length L-p and end-to-end distance R-2 (1/2) with increasing lambda. While CG models that include an independent torsion angle match the bond-orientation correlation and R-2 (1/2) better, only approximate models that include correlations between bond and torsion angles match the true bond-orientation correlation.
机译:与全原子(AA)分子动力学模拟相比,粗颗粒(CG)聚合物模拟可以获得更长的时间和更长的长度;然而,并不是所有的CG模型都能在所有长度尺度上正确地再现聚合物的性质。在这里,我们将聚乙烯(PE)和聚四氟乙烯(PTFE)熔体模拟中的粗颗粒原子位置数据结合在一个CG珠中的主链碳原子。由此产生的CG变量沿主链具有相关性,这取决于粗粒化尺度A,并且通常不会通过独立的键长、键角和扭角分布再现。通过构造与模拟CG势等效的CG变量分布,我们能够以较低的计算成本评估不同CG模型的键取向相关性。CG模型和电势仅包括通过Boltzmann反演计算的非键、键长和键角相互作用,它们正确地再现了CG变量分布,但不一定再现了链刚度,高估了持续长度L-p和端到端距离;R-2;(1/2)随着λ的增加。而包含独立扭转角的CG模型与键方向相关性匹配,并且;R-2;(1/2)更好的是,只有包含键和扭转角之间相关性的近似模型才符合真正的键方向相关性。

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