Genarris 2.0: A random structure generator for molecular crystals

Genarris is an open source Python package for generating random molecular crystal structures with physical constraints for seeding crystal structure prediction algorithms and training machine learning models. Here we present a new version of the code, containing several major improvements. A MPI-based parallelization scheme has been implemented, which facilitates the seamless sequential execution of user-defined workflows. A new method for estimating the unit cell volume based on the single molecule structure has been developed using a machine-learned model trained on experimental structures. A new algorithm has been implemented for generating crystal structures with molecules occupying special Wyckoff positions. A new hierarchical structure check procedure has been developed to detect unphysical close contacts efficiently and accurately. New intermolecular distance settings have been implemented for strong hydrogen bonds. To demonstrate these new features, we study two specific cases: benzene and glycine. Genarris finds the experimental structures of the two polymorphs of benzene and the three polymorphs of glycine.Genarris是一款开源Python软件包，可生成带有物理约束的随机分子晶体结构，用于为晶体结构预测算法提供初始种子结构，同时支撑机器学习模型的训练。本文介绍了该代码的新版本，其包含多项重大改进。已实现一种基于消息传递接口（Message Passing Interface, MPI）的并行化方案，可支持用户自定义工作流的无缝顺序执行。研发了一种基于单分子结构估算晶胞体积的新方法，该方法采用了基于实验结构训练得到的机器学习模型。已实现一种新算法，可生成分子占据特定魏科夫位置（Wyckoff positions）的晶体结构。开发了一套全新的分层结构检查流程，可高效且准确地检测出非物理合理的紧密接触。新增了针对强氢键的分子间距离设置功能。为展示这些新增功能，本文选取苯与甘氨酸两个体系进行案例研究。Genarris可复现苯的两种晶型以及甘氨酸的三种晶型的实验晶体结构。