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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:粗粒(CG)聚合物模拟可以进入比全原子(AA)分子动力学模拟更长的时间和更大的长度;但是,并非所有CG模型都正确再现了所有长度尺度的聚合物性质。在这里,通过在单个Cg珠粒中组合骨架碳原子,我们通过聚乙烯(PE)和聚四氟乙烯(PTFE)熔融模拟的粗粒原子的位置数据。得到的CG变量具有沿着链骨架的相关性,其取决于粗晶刻度A,并且通常不会被独立的键合长度,键角和扭转角分布再现。通过构造与模拟CG电位的CG变量的分布,我们能够以降低的计算成本评估不同CG模型的结合取向相关。 CG模型和电位仅包括由Boltzmann反演计算的非粘合,键合和键角相互作用正确再现CG可变分布,但不一定再现链刚度,高估持久长度LP和端到端距离& ; R-2&(1/2)随​​着lambda的增加。虽然CG模型包括独立的扭转角度匹配键取向相关性和& R-2&(1/2)更好,仅包括近似模型,包括键合和扭转角之间的相关性与真正的结合取向相关性相匹配。

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