Research Initiation Award: Initiation of Research in the Computer Simulation of Polymeric Materials

摘要CTS-9410081科罗拉多矿业学院P.I.：约翰·R·道根在聚合物材料的计算机模拟方面是一项创举。共聚物链在无机界面的蒙特卡罗(MC)模拟是合理设计表面活性聚合物的基础。具体使用的MC技术是pakula的协同运动算法；与其他仿真方法相比，它具有显著的优势。模拟提供了详细的结构信息(链构象、吸附量、链段轮廓等)。关于平衡条件下共聚物层的吸附情况。这种结构信息可以根据共聚物链段/底物相互作用的强度、共聚物的特定嵌段序列、溶剂质量和表面非均质性来计算。通过将模拟结果与定义良好的实验数据进行比较，可以确定模型参数。经过验证，MC算法可用于预测目的，从而允许针对特定目的的共聚物层的先验设计。

ABSTRACT CTS-9410081 Colorado School of Mines P.I.: John R. Dorgan An initiative in the computer simulation of polymeric materials is pursued. Monte Carlo (MC) simulation of copolymer chains at inorganic interfaces is developed as a basis for the rational design of surface active polymeric agents. The specific MC technique used is the cooperative-motion algorithm of Pakula; significant advantages over other simulation methods are demonstrated. The simulations provide detailed structural information (chain conformations, absorbed amounts, chain segment profiles, etc.) about the absorbed copolymer layer under equilibrium conditions. This structural information can be calculated based on the strength of the copolymer segment/substrate interaction, the specific block sequencing of the copolymer, solvent quality, and surface heterogeneity. Comparison of simulation results with well defined experimental data allows the determination of model parameters. Upon verification, the MC algorithm may be used for predictive purposes allowing the apriori design of copolymer layers for specific purposes.