Manz Thomas A
Chemical & Materials Engineering, New Mexico State University Las Cruces New Mexico 88003-3805 USA
RSC Adv. 2020 Dec 15;10(72):44121-44148. doi: 10.1039/d0ra06392d. eCollection 2020 Dec 9.
This article studies two kinds of information extracted from statistical correlations between methods for assigning net atomic charges (NACs) in molecules. First, relative charge transfer magnitudes are quantified by performing instant least squares fitting (ILSF) on the NACs reported by Cho (, 2020, , 688-696) across 26 methods applied to ∼2000 molecules. The Hirshfeld and Voronoi deformation density (VDD) methods had the smallest charge transfer magnitudes, while the quantum theory of atoms in molecules (QTAIM) method had the largest charge transfer magnitude. Methods optimized to reproduce the molecular dipole moment (, ACP, ADCH, CM5) have smaller charge transfer magnitudes than methods optimized to reproduce the molecular electrostatic potential (, CHELPG, HLY, MK, RESP). Several methods had charge transfer magnitudes even larger than the electrostatic potential fitting group. Second, confluence between different charge assignment methods is quantified to identify which charge assignment method produces the best NAC values for predicting linear correlations the results of 20 charge assignment methods having a complete basis set limit across the dataset of ∼2000 molecules. The DDEC6 NACs were the best such predictor of the entire dataset. Seven confluence principles are introduced explaining why confluent quantitative descriptors offer predictive advantages for modeling a broad range of physical properties and target applications. These confluence principles can be applied in various fields of scientific inquiry. A theory is derived showing confluence is better revealed by standardized statistical analysis (, principal components analysis of the correlation matrix and standardized reversible linear regression) than by unstandardized statistical analysis. These confluence principles were used together with other key principles and the scientific method to make assigning atom-in-material properties non-arbitrary. The N@C system provides an unambiguous and non-arbitrary falsifiable test of atomic population analysis methods. The HLY, ISA, MK, and RESP methods failed for this material.
本文研究了从分子中净原子电荷（NAC）分配方法之间的统计相关性中提取的两类信息。首先，通过对Cho（2020年，第688 - 696页）报道的应用于约2000个分子的26种方法所得到的NAC进行即时最小二乘法拟合（ILSF），来量化相对电荷转移量。Hirshfeld方法和Voronoi变形密度（VDD）方法的电荷转移量最小，而分子中的原子量子理论（QTAIM）方法的电荷转移量最大。为重现分子偶极矩而优化的方法（如ACP、ADCH、CM5）的电荷转移量比为重现分子静电势而优化的方法（如CHELPG、HLY、MK、RESP）要小。有几种方法的电荷转移量甚至比静电势拟合组的还要大。其次，对不同电荷分配方法之间的融合程度进行量化，以确定哪种电荷分配方法能产生最佳的NAC值，用于预测约2000个分子数据集上20种具有完整基组极限的电荷分配方法的线性相关结果。DDEC6 NAC是整个数据集的最佳此类预测指标。引入了七条融合原则，解释了为什么融合定量描述符在对广泛的物理性质和目标应用进行建模时具有预测优势。这些融合原则可应用于科学探究的各个领域。推导了一种理论，表明通过标准化统计分析（如相关矩阵的主成分分析和标准化可逆线性回归）比通过非标准化统计分析能更好地揭示融合。这些融合原则与其他关键原则及科学方法一起使用，使得材料中原子性质的分配不再是任意的。N@C系统为原子布居分析方法提供了一个明确且非任意的可证伪测试。HLY、ISA、MK和RESP方法对这种材料不适用。
