基于核密度估计的半晶态系统粗粒化及具有相关三体分子内相互作用
KDE-Based Coarse-graining of Semicrystalline Systems with Correlated Three-body Intramolecular Interaction
AI总结：
本文扩展了迭代Boltzmann反演方法，结合核密度估计与双三次插值构建含三体分子内势能的粗粒化模型，以重现结构分布函数相关性，并证明调节带宽参数可加速聚合物结晶建模。
摘要：
我们对迭代Boltzmann反演方法进行了扩展，以生成具有三体分子内势能的粗粒化模型，该模型能够重现结构分布函数中的相关性。粗粒化结构分布函数使用核密度估计进行计算，以产生解析可微的分布函数，并通过核带宽参数实现可控的平滑。双三次插值用于准确插值由该方法训练的三体势能。为了演示这种新方法，构建了一个聚乙烯的粗粒化模型，其中每个珠子代表一个乙烯单体。与具有独立键长和键角势能的模型相比，所得模型仅增加了10%的计算成本，便重现了径向密度函数以及从目标全原子模拟中采样的键长和键角的联合概率分布。对由新方法开发的模型预测的结晶动力学分析表明，可以调整带宽参数以加速聚合物结晶的建模。具体而言，用更大带宽计算目标RDF会减慢次级结晶，而增加键长和键角分布中θ方向的带宽会降低初级结晶速率。
英文摘要：
We present an extension to the iterative Boltzmann inversion method to generate coarse-grained models with three-body intramolecular potentials that can reproduce correlations in structural distribution functions. The coarse-grained structural distribution functions are computed using kernel density estimates to produce analytically differentiable distribution functions with controllable smoothening via the kernel bandwidth parameters. Bicubic interpolation is used to accurately interpolate the three-body potentials trained by the method. To demonstrate this new approach, a coarse-grained model of polyethylene is constructed in which each bead represents an ethylene monomer. The resulting model reproduces the radial density function as well as the joint probability distribution of bond-length and bond-angles sampled from target atomistic simulations with only a 10% increase in the computational cost compared to models with independent bond-length and bond-angle potentials. Analysis of the predicted crystallization kinetics of the model developed by the new approach reveals that the bandwidth parameters can be tuned to accelerate the modeling of polymer crystallization. Specifically, computing target RDF with larger bandwidth slows down the secondary crystallization, and increasing the bandwidth in $θ$-direction of bond-length and bond-angle distribution reduces the primary crystallization rate.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
