多分枝聚合物刷的标度理论和模拟

Universal scaling regimes exist for dendrimer brushes, but these regimes are narrow and separated by broad crossover regimes, and there exists an increased number of scaling variables, making predictions more difficult, in particular with varying solvent qualities. It is therefore of great importance to carry out computer simulations in order to test, verify and qualify some of the existing scaling predictions for dendrimer polymer brushes. The research objectives are a systematic analysis of the properties of dendrimer brushes, their MD simulation, and the scaling behavior of typical brush features such as layer thickness, chain tension, mechanical elastic properties and switching dynamics, as a function of dendrimer functionality, generation, grafting density and solvent quality. Additionally, we are planning to use and extend previously developed mean-field and SCF models in order to interpret and understand the features of the polymer brushes. The final goal is to deliver guidelines for laboratory work and technical applications, about how to optimize the brush properties and, possibly, funtionalize the brushes in order to obtain highly environment responsive surface layers. Further on, we want to learn how to optimize the simulation procedure on graphic architectures using the Nvidia CUDA programming environment. In what follows we detail the most important research objectives.

普遍的标度理论在多分支聚合物刷中是存在的，但是这些理论是建立在分离的交叉的区域，且标度标量增加，从而很难准确的预测结果。因此有必要用计算机模拟去证实和预测存在多分支聚合物刷的标度特性。本项目的目的是用分子动力学模拟对多分支聚合物刷的吸附密度和溶剂性质进行系统分析，如：对聚合物层的厚度，链的张力，弹性力性质和切换动力学等与多分支刷的功能、吸附面密度和溶剂性质的依赖关系进行研究。另外，我们计划扩展早期的平均场和自洽场模型来更好地解释聚合物刷的特性。最终目的是为实验和工业上的应用提供指导，例如如何优化聚合物刷特性，如有可能进行功能化从而得到对环境能感知的聚合物层。我们还要学习通过运用Nvidia CUDA 编程环境在图像架构下优化计算过程。正文中我们将详细阐述最重要的研究目的。

对于高分子聚合物刷，尤其是多分枝高分子的研究，主要出于以下几个原因。首先，多分枝高分子聚合物刷在垂直于基底的方向，与普通的线性聚合物刷相比，呈现出了更加复杂的结构，而对于这些结构的研究和理解将有效的指导我们设计具有转换功能的材料表面涂层。其次，目前在实验室环境中，已经可以制造出具有特定性质的高分子聚合物刷（如控制分子质量，设计特殊功能团等），而我们相关的理论计算研究将帮助我们更加准确的理解这些系统的物理性质，同时也可以促进现有的模拟计算方法。