Reith Dirk, Pütz Mathias, Müller-Plathe Florian
Max-Planck-Institut für Polymerforschung, D-55128 Mainz, Germany.
J Comput Chem. 2003 Oct;24(13):1624-36. doi: 10.1002/jcc.10307.
We demonstrate how an iterative method for potential inversion from distribution functions developed for simple liquid systems can be generalized to polymer systems. It uses the differences in the potentials of mean force between the distribution functions generated from a guessed potential and the true distribution functions to improve the effective potential successively. The optimization algorithm is very powerful: convergence is reached for every trial function in few iterations. As an extensive test case we coarse-grained an atomistic all-atom model of polyisoprene (PI) using a 13:1 reduction of the degrees of freedom. This procedure was performed for PI solutions as well as for a PI melt. Comparisons of the obtained force fields are drawn. They prove that it is not possible to use a single force field for different concentration regimes.
我们展示了一种为简单液体系统开发的从分布函数进行势反演的迭代方法如何能够推广到聚合物系统。它利用从猜测的势生成的分布函数与真实分布函数之间平均力势的差异来相继改进有效势。该优化算法非常强大:在几次迭代中每个试验函数都能收敛。作为一个广泛的测试案例,我们使用自由度为13:1的约简对聚异戊二烯(PI)的全原子模型进行了粗粒化处理。此过程针对PI溶液以及PI熔体进行。对得到的力场进行了比较。结果证明,对于不同的浓度范围不可能使用单一的力场。