结晶
对映体药物
分子
化学
化学物理
分辨率(逻辑)
能源景观
无定形固体
Crystal(编程语言)
分子动力学
手性拆分
计算化学
结晶学
对映体
有机化学
计算机科学
人工智能
对映选择合成
催化作用
生物化学
程序设计语言
作者
John E. Carpenter,Michael Grünwald
摘要
Predicting the crystallization of chiral molecules from solution is a major challenge in the chemical sciences. In this paper, we use molecular dynamics computer simulations to study the crystallization of a family of coarse-grained models of chiral molecules with a broad range of molecular shapes and interactions. Our simulations reproduce the experimental crystallization behavior of real chiral molecules, including racemic and enantiopure crystals, as well as amorphous solids. Using efficient algorithms for the packing of shapes, we enumerate millions of low-energy crystal structures for each model and analyze the thermodynamic landscape of polymorphs. In agreement with recent conjectures, our analysis shows that the ease of crystallization is largely determined by the number of competing polymorphs with low free energy. We find that this number and, hence, crystallization outcomes depend on molecular interactions in a simple way: Strongly heterogeneous interactions across molecules promote crystallization and favor the spontaneous resolution of racemic mixtures. Our results help rationalize a number of experimental observations and can provide guidance for the design of molecules and experimental conditions for desired crystallization outcomes.
科研通智能强力驱动
Strongly Powered by AbleSci AI