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. [
J. Chem. Phys.
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.