Laboratoire de Chimie Théorique, Sorbonne Université, F. 75005 Paris, France.
Departamento de Química Física y Analítica, Universidad de Oviedo, 33006 Oviedo, Spain.
Phys Chem Chem Phys. 2022 Sep 21;24(36):21538-21548. doi: 10.1039/d2cp01517j.
We provide a comprehensive overview of the chemical information from electron density: not only how to extract information, but also how to obtain and how to assess the quality of the electron density itself. After introducing several indexes derived from electron density, which allow bonding to be revealed, we focus on the various potential sources of electron density, and also explain the error trends they show so that a judicious choice of methods and limitations are clearly laid on the table. Computational, experimental-computational combinations, and machine learning efforts are covered in this work.
不仅介绍了如何提取信息，还介绍了如何获取和评估电子密度本身的质量。在介绍了几个可以揭示键的电子密度衍生指标之后，我们重点介绍了各种潜在的电子密度来源，并解释了它们所表现出的误差趋势，以便清楚地阐明方法选择和限制。本工作涵盖了计算、实验计算组合和机器学习方面的努力。
