Density embedding and other electronic structure methods for condensed phase chemistry

This thesis discusses electronic structure methods based on Density Functional Theory (DFT) and subsystem DFT (sDFT) that have been developed for modeling electronic processes in molecular condensed phases. Specific processes considered involve valence electron ionization, core-electron excitation, reaction barriers of chemical reactions involving strong electron correlation, and solute-solvent interactions. For virtually all of the processes mentioned, off-the-shelf electronic structure methods would either completely fail in providing a physical picture of the process or would be inapplicable due to the too large minimum model system size (in terms of number of atoms) required to recover a realistic depiction of reality. Therefore, the work presented tackles first and foremost the steep computational scaling of DFT by deploying sDFT. Second, the applicability of sDFT is extended to model difficult systems, such as charged species in condensed phases, or to model ultrafast processes. Third, extensions to the quantum theory of DFT and density-matrix functional theory are also presented to be able to model systems experiencing strong correlation, whether via machine learning models or ab-initio methods. This thesis also features a technology transfer project that leverages the advances carried out in the lab, translating them to the problem of computational drug discovery.