Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA.
Soft Matter. 2016 Dec 21;13(1):239-249. doi: 10.1039/c6sm00770h.
Polymer nanocomposites are an important class of materials due to the nanoparticles' ability to impart functionality not commonly found in a polymer matrix, such as electrical conductivity or tunable optical properties. While the equilibrium properties of polymer nanocomposites can be treated using numerous theoretical and simulation approaches, in experiments the effects of processing and kinetic traps are significant and thus critical for understanding the structure and the functionality of polymer nanocomposites. However, simulation methods that can efficiently predict kinetically trapped and metastable structures of polymer nanocomposites are currently not common. This is particularly important in inhomogeneous polymers such as block copolymers, where techniques such as solvent vapor annealing are commonly employed to improve the long-range order. In this work, we introduce a dynamic mean field theory that is capable of predicting the result of processing the structure of polymer nanocomposites, and we demonstrate that our method accurately predicts the equilibrium properties of a model system more efficiently than a particle-based model. We subsequently use our method to predict the structure of block copolymer thin films with grafted nanoparticles after solvent annealing, where we find that the final distribution of the grafted nanoparticles can be controlled by varying the solvent evaporation rate. The extent to which the solvent evaporation rate can affect the final nanoparticle distribution in the film depends on the grafting density and the length of the grafted chains. Furthermore, the effects of the solvent evaporation rate can be anticipated from the equilibrium nanoparticle distribution in the swollen and dry states.
聚合物纳米复合材料是一类重要的材料，因为纳米粒子具有赋予聚合物基体通常不具备的功能的能力，例如导电性或可调光学性质。虽然聚合物纳米复合材料的平衡性质可以通过多种理论和模拟方法来处理，但在实验中，加工和动力学陷阱的影响是显著的，因此对于理解聚合物纳米复合材料的结构和功能至关重要。然而，目前还没有能够有效地预测聚合物纳米复合材料中动力学陷阱和亚稳结构的模拟方法。这在非均相聚合物（如嵌段共聚物）中尤为重要，在这些聚合物中，溶剂蒸气退火等技术通常被用来提高长程有序性。在这项工作中，我们引入了一种动态平均场理论，该理论能够预测处理聚合物纳米复合材料结构的结果，我们证明了我们的方法比基于粒子的模型更有效地预测了模型体系的平衡性质。随后，我们使用我们的方法来预测接枝纳米粒子的嵌段共聚物薄膜在溶剂退火后的结构，我们发现通过改变溶剂蒸发速率可以控制接枝纳米粒子的最终分布。溶剂蒸发速率对薄膜中最终纳米粒子分布的影响程度取决于接枝密度和接枝链的长度。此外，从溶胀和干燥状态下的平衡纳米粒子分布可以预测溶剂蒸发速率的影响。
