Quantitative predictions for structured polymeric melts

定量模拟方法将被开发并应用于结构聚合物熔体，特别是那些涉及嵌段共聚物的熔体。这是可能的，因为所有的模型和实验都简化为高分子量的标准高斯链模型(GCM)。这种普遍性的深刻含义是，通过将两者映射到GCM上，即使是简单的模型也可以与实验定量匹配。嵌段共聚物与普通聚合物非常相似，不同之处在于它们由不同的化学部分(或嵌段)组成。这些不同的块体因其连通性而趋于分离，导致这些分子的液体(或熔体)自组装成具有纳米大小的结构。将具有不同特性的成分组合成定义良好的纳米结构的能力提供了一种控制材料性能的强大方法。此外，有序纳米结构在新兴的纳米技术领域有着广泛的应用。GCM将聚合物视为通过接触力相互作用的弹性细线，其强度由Flory-Huggins chi参数控制。将其他模型或实验映射到GCM上的关键是知道如何校准chi，这是我们在过去几年中取得的巨大进展。尽管GCM是嵌段共聚物的大多数理论计算的基础，但直接模拟是不现实的，因此需要其他方法。一种策略是使用基于粒子的晶格模型，其中通过将聚合物限制在晶格中来提高模拟的效率。尽管晶格是人为的，但由于普适性，定量预测仍然是可能的。过去，这些模拟仅限于低分子量聚合物，但我们现在开发了一种可以映射到高分子量聚合物的晶格模型。它将被用来开发两嵌段共聚物熔体和二元均聚物共混物的定量预测，以便在实验系统中校准CHI参数。另一种策略是场论模拟(FTS)，将基于粒子的GCM转换为数学上等价的基于场的模型，然后可以进行模拟。这种方法一直受到计算挑战和所谓的紫外线发散的困扰，但我们已经克服了这些障碍，生成了一种能够模拟传统基于粒子的模型过于复杂的系统的高效FTS算法。FTS将用于研究两嵌段共聚物与其母均聚物的三元共混，这些均聚物以产生双连续微乳液而闻名。FTS还将应用于复杂的瓶刷嵌段共聚物，这些聚合物因其快速的动力学和较大的结构域而受到极大的关注。

Quantitative simulation methods will be developed and applied to structured polymeric melts, in particular, those involving block copolymers. This is only possible because all models and experiments reduce to a standard Gaussian-chain model (GCM) at high molecular weights. The profound implication of this universality is that even simple models can be quantitatively matched to experiments by mapping both onto the GCM. Block copolymer are much like ordinary polymers, except that they consist of chemically distinct sections (or blocks). The tendency for the distinct blocks to separate tempered by their connectivity causes a liquid (or melt) of these molecules to self-assemble into structures with nanometer-sized domains. The ability to combine components with different characteristics into well-defined nanostructures provides a powerful way of controlling material properties. Furthermore, the ordered nanostructures have many applications in the emerging field of nanotechnology. The GCM treats polymers as thin elastic threads interacting by contact forces, the strength of which is control by a Flory-Huggins chi parameter. The key to mapping other models or experiments onto the GCM is knowing how to calibrate chi, which is something that we have made great progress on over the past few years. Although the GCM underpins most theoretical calculations on block copolymers, it is impractical to simulate directly and thus one needs other approaches. One strategy is to use particle-based lattice models, where the simulation is made efficient by restricting the polymers to a lattice. Although the lattice is artificial, quantitative predictions are still possible due to universality. In the past, these simulations have been limited to low molecular-weight polymers, but we have now developed a lattice model that can be mapped onto high molecular-weight polymers. It will be used to develop quantitative predictions of diblock copolymer melts and of binary homopolymer blends for the purpose of calibrating the chi parameter in experimental systems. Another strategy is field-theoretic simulations (FTS), where the particle-based GCM is transformed into a mathematically equivalent field-based model, which can then be simulated. This approach has been plagued by computational challenges and a so-called ultraviolet divergence, but we have overcome these obstacles to generate a highly efficient FTS algorithm capable of simulating systems that are too complicated for traditional particle-based models. FTS will be used to investigate ternary blends of diblock copolymers with their parent homopolymers, which are well known for producing bicontinuous microemulsions. FTS will also be applied to complicated bottlebrush block copolymers, which are gaining huge attention due to their fast dynamics and large domains.