RESUMEN
Quantum-chemical subsystem and embedding methods require complex workflows that may involve multiple quantum-chemical program packages. Moreover, such workflows require the exchange of voluminous data that go beyond simple quantities, such as molecular structures and energies. Here, we describe our approach for addressing this interoperability challenge by exchanging electron densities and embedding potentials as grid-based data. We describe the approach that we have implemented to this end in a dedicated code, PyEmbed, currently part of a Python scripting framework. We discuss how it has facilitated the development of quantum-chemical subsystem and embedding methods and highlight several applications that have been enabled by PyEmbed, including wave-function theory (WFT) in density-functional theory (DFT) embedding schemes mixing non-relativistic and relativistic electronic structure methods, real-time time-dependent DFT-in-DFT approaches, the density-based many-body expansion, and workflows including real-space data analysis and visualization. Our approach demonstrates, in particular, the merits of exchanging (complex) grid-based data and, in general, the potential of modular software development in quantum chemistry, which hinges upon libraries that facilitate interoperability.
RESUMEN
For an electronic system, given a mean field method and a distribution of orbital occupation numbers that are close to the natural occupations of the correlated system, we provide formal evidence and computational support to the hypothesis that the entropy (or more precisely -σS, where σ is a parameter and S is the entropy) of such a distribution is a good approximation to the correlation energy. Underpinning the formal evidence are mild assumptions: the correlation energy is strictly a functional of the occupation numbers, and the occupation numbers derive from an invertible distribution. Computational support centers around employing different mean field methods and occupation number distributions (Fermi-Dirac, Gaussian, and linear), for which our claims are verified for a series of pilot calculations involving bond breaking and chemical reactions. This work establishes a formal footing for those methods employing entropy as a measure of electronic correlation energy (e.g., i-DMFT [Wang and Baerends, Phys. Rev. Lett. 128, 013001 (2022)] and TAO-DFT [J.-D. Chai, J. Chem. Phys. 136, 154104 (2012)]) and sets the stage for the widespread use of entropy functionals for approximating the (static) electronic correlation.
RESUMEN
Understanding and predicting the properties of molecular liquids from the corresponding properties of the individual molecules is notoriously difficult because there is cooperative behavior among the molecules in the liquid. This is particularly relevant for water, where even the most fundamental molecular properties, such as the dipole moment, are radically different in the liquid compared to the gas phase. In this work, we focus on the ionization potential (IP) of liquid water by dissecting its individual contributions from the individual molecules making up the liquid. This is achieved by using periodic subsystem DFT, a state-of-the-art electronic structure method based on density embedding. We identify and evaluate four important electronic contributions to the IP of water: (1) mean-field, evaluated at the Hartree-Fock level; (2) electronic correlation, incorporated via DFT and wave function-based methods; (3) interaction with and (4) polarization of the environment, both evaluated ab initio with density embedding. Furthermore, we analyze their impact on the IP relative to the structural fluctuation of liquid water, revealing unexpected, hidden correlations, confirming that the broadening of the photoelectron spectra is mostly caused by intermolecular interactions confined in the first solvation shell.
RESUMEN
The low energy excited states of the conformational isomers of solvated azobenzene are calculated with several DFT methods accounting for the solute-solvent interaction implicitly with the polarizable continuum model or explicitly with subsystem DFT. For the latter, embedding potentials are calculated for 21 sampled snapshots of the solvent molecules. First, we find that accounting for the solvent implicitly or explicitly has little effect on the predicted cis-trans S1 excitation energy gap. Second, we find that azobenzene's S1 cis and trans energies are accurate as long as a screened range-separated hybrid exchange-correlation functional is employed. Finally, we also tested a simplified workflow whereby a single, averaged, embedding potential is used. Unfortunately, we find larger deviations against the experiment for the simplified workflow. This highlights a basic flaw in the approach, where the time scale of solvent averaging is much longer than that of the solute's electronic polarization.