Li Zhaofan, Tolba Sara A, Wang Yang, Alesadi Amirhadi, Xia Wenjie
Department of Aerospace Engineering, Iowa State University, Ames, Iowa 50011, USA.
Materials and Nanotechnology Program, North Dakota State University, Fargo, ND 58108, USA.
Chem Commun (Camb). 2024 Oct 10;60(82):11625-11641. doi: 10.1039/d4cc03217a.
Conjugated polymers (CPs) have emerged as pivotal functional materials in the realm of flexible electronics and optoelectronic devices due to their unique blend of mechanical flexibility, solution processability, and tunable optoelectronic properties. This review synthesizes the latest molecular simulation-driven insights obtained from various multiscale modeling techniques, including quantum mechanics (QM), all-atomistic (AA) molecular dynamics (MD), coarse-grained (CG) modeling, and machine learning (ML), to elucidate the optoelectronic, structural, and thermomechanical properties of CPs. By integrating findings from our recent computational work with key experimental studies, we highlight the molecular mechanisms influencing the multifunctional performance of CPs. This comprehensive understanding aims to guide future research directions and applications in the modeling assisted design of high-performance CP-based materials and devices.
共轭聚合物(CPs)因其独特的机械柔韧性、溶液可加工性和可调谐的光电特性,已成为柔性电子和光电器件领域的关键功能材料。本综述综合了从各种多尺度建模技术中获得的最新分子模拟驱动的见解,包括量子力学(QM)、全原子(AA)分子动力学(MD)、粗粒度(CG)建模和机器学习(ML),以阐明CPs的光电、结构和热机械性能。通过将我们最近的计算工作结果与关键实验研究相结合,我们突出了影响CPs多功能性能的分子机制。这种全面的理解旨在指导未来在基于CPs的高性能材料和器件的建模辅助设计方面的研究方向和应用。