Using Particle Swarm Optimization and Self-Consistent Field Theory to Discover Globally Stable Morphologies of Block Copolymers
Using Particle Swarm Optimization and Self-Consistent Field Theory to Discover Globally Stable Morphologies of Block Copolymers
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使用粒子群优化和自洽场论发现嵌段共聚物的全局稳定形态
DOI：
10.1021/acs.macromol.2c00042
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发表时间：
2022
期刊：
影响因子：
5.5
通讯作者：
G. Fredrickson
中科院分区：
文献类型：
--
作者：
Carol L. Tsai;G. Fredrickson
本文提出了一种结合粒子群优化（PSO）和自洽场理论（SCFT）的嵌段共聚物全局稳定和低位亚稳中间相的不可知论确定方法。在PSO-SCFT方法中，我们利用SCFT作为局部优化器，通过将PSO在靠近临界波数的单个壳中填充的互空间场播种SCFT模拟。PSO简化了在互空间SCFT种子空间中的搜索，这些种子放松到各种形态。我们提出了两种体系的PSO-SCFT的基准测试结果，这两种体系的理论相图已经建立：典型AB双嵌段和mitoarm星形聚合物AB4，后者支持丰富多样的竞争性球体结构。PSO-SCFT的具体实现表明，以确定双回旋形态在AB二嵌段共聚物熔体。此外，PSO-SCFT成功地恢复了a15在mitoarm熔体中稳定的组成和几种竞争亚稳态候选物的形态。后者是具有zr4al3晶体结构的球体形态，被确定为hP7 Frank-Kasper相，这是以前在嵌段聚合物体系中未见过的形态。因此，PSO-SCFT方法为新型嵌段共聚物体系中低自由能结构的自动识别提供了一个有前途的框架。
We present a method for agnostically determining the globally stable and low-lying metastable mesophases of block copolymers by combining particle swarm optimization (PSO) and self-consistent field theory (SCFT). In the PSO-SCFT method, we exploit SCFT as a local optimizer by seeding SCFT simulations with reciprocal-space fields populated in a single shell by the PSO near a critical wavenumber. The PSO facilitates the search through a space of reciprocal-space SCFT seeds that relax to a variety of morphologies. We present benchmarking results for PSO-SCFT on two systems for which theoretical phase diagrams are well-established: the canonical AB diblock and the miktoarm star polymer AB4, the latter of which supports a rich variety of competing sphere structures. A specific implementation of PSO-SCFT is shown to identify the double gyroid morphology in AB diblock copolymer melts. Furthermore, PSO-SCFT successfully recovers both the A15morphology at a composition where it is expected to be stable in miktoarm melts and several competitive metastable candidates. One of the latter is a sphere morphology with a crystal structure of Zr4Al3that was identified as the hP7 Frank–Kasper phase, a morphology not seen before in block polymer systems. The PSO-SCFT method thus provides a promising framework for the automatic identification of low-free-energy structures in new block copolymer systems.