分子自组织：预测竞争有序基序的模式多样性和最低能态
Molecular self-organization: Predicting the pattern diversity and lowest energy state of competing ordering motifs
摘要：
采用溶液浇铸法在石墨表面制备了高度柔性的\Frechet树枝状分子的自组织单层膜。扫描隧道显微镜（STM）揭示了一个前所未有的各种模式与多达七个稳定的层次有序图案作为一个通用的模型系统。通过分子力学模拟确定的基本分子性质被浓缩到各种链构型的粗粒度相互作用位点模型。在随机初始配置的蒙特卡罗方法中，实验模式的多样性可以在局部和全局排序的所有方面再现。基于能量分析的Monte Carlo和分子力学建模的最稳定的模式，预测符合的模式，其中占主导地位的STM图像后几个小时或适度加热。
英文摘要：
Self-organized monolayers of highly flexible \Frechet dendrons were deposited on graphite surfaces by solution casting. Scanning tunneling microscopy (STM) reveals an unprecedented variety of patterns with up to seven stable hierarchical ordering motifs serving as a versatile model system. The essential molecular properties determined by molecular mechanics simulations are condensed to a coarse grained interaction site model of various chain configurations. In a Monte Carlo approach with random starting configurations the experimental pattern diversity can be reproduced in all facets of the local and global ordering. Based on an energy analysis of the Monte Carlo and molecular mechanics modeling the thermodynamically most stable pattern is predicted coinciding with the pattern, which dominates in the STM images after several hours or upon moderate heating.
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