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. An 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. For all polymorphs, the final pool either contained the experimental structure, or structures with similar lattice parameters, symmetry, and packing motifs.

中文翻译：

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Genarris 2.0：分子晶体的随机结构生成器

Genarris 是一个开源 Python 包，用于生成具有物理约束的随机分子晶体结构，用于种子晶体结构预测算法和训练机器学习模型。在这里，我们展示了代码的新版本，其中包含几项重大改进。已经实施了基于 MPI 的并行化方案，这有助于用户定义工作流的无缝顺序执行。使用在实验结构上训练的机器学习模型开发了一种基于单分子结构估计晶胞体积的新方法。已经实施了一种新算法，用于生成分子占据特殊 Wyckoff 位置的晶体结构。已开发出一种新的分层结构检查程序，以高效准确地检测非物理密切接触。为强氢键实施了新的分子间距离设置。为了演示这些新功能，我们研究了两个具体案例：苯和甘氨酸。对于所有多晶型物，最终池要么包含实验结构，要么包含具有相似晶格参数、对称性和填充图案的结构。