Daga Loredana Edith, Civalleri Bartolomeo, Maschio Lorenzo
Dipartimento di Chimica, Università di Torino and NIS (Nanostructured Interfaces and Surfaces) Centre, Via P. Giuria 5, 10125 Torino, Italy.
J Chem Theory Comput. 2020 Apr 14;16(4):2192-2201. doi: 10.1021/acs.jctc.9b01004. Epub 2020 Mar 26.
It is customary in molecular quantum chemistry to adopt basis set libraries in which the basis sets are classified according to either their size (triple-ζ, quadruple-ζ, ...) and the method/property they are optimal for (correlation-consistent, linear-response, ...) but not according to the chemistry of the system to be studied. In fact the vast majority of molecules is quite homogeneous in terms of density (i.e., atomic distances) and types of bond involved (covalent or dispersive). The situation is not the same for solids, in which the same chemical element can be found having metallic, ionic, covalent, or dispersively bound character in different crystalline forms or compounds, with different packings. This situation calls for a different approach to the choice of basis sets, namely a system-specific optimization of the basis set that requires a practical algorithm that could be used on a routine basis. In this work we develop a basis set optimization method based on an algorithm-similar to the direct inversion in the iterative subspace-that we name BDIIS. The total energy of the system is minimized together with the condition number of the overlap matrix as proposed by VandeVondele et al. [VandeVondele et al. 2007, 227, 114105]. The details of the method are here presented, and its performance in optimizing valence orbitals is shown. As demonstrative systems we consider simple prototypical solids such as diamond, graphene sodium chloride, and LiH, and we show how basis set optimizations have certain advantages also toward the use of large (quadruple-ζ) basis sets in solids, both at the DFT and Hartree-Fock level.
在分子量子化学中，习惯采用基组库，其中基组是根据其大小（三重ζ、四重ζ等）以及它们最适合的方法/性质（相关一致、线性响应等）来分类的，而不是根据待研究体系的化学性质。实际上，绝大多数分子在密度（即原子间距）和所涉及的键的类型（共价键或色散键）方面相当均匀。固体的情况则不同，在固体中，同一化学元素在不同的晶体形式或化合物中，以不同的堆积方式，可能具有金属、离子、共价或色散结合的性质。这种情况需要一种不同的基组选择方法，即针对特定体系对基组进行优化，这需要一种可常规使用的实用算法。在这项工作中，我们基于一种类似于迭代子空间直接反演的算法开发了一种基组优化方法，我们将其命名为BDIIS。正如万德冯德等人所提出的[万德冯德等人，2007，227，114105]，体系的总能量与重叠矩阵的条件数一起被最小化。这里给出了该方法的详细信息，并展示了其在优化价轨道方面的性能。作为示例体系，我们考虑了简单的典型固体，如金刚石、石墨烯、氯化钠和氢化锂，并展示了基组优化在固体中使用大（四重ζ）基组时，在密度泛函理论（DFT）和哈特里 - 福克水平上都具有一定优势。
