Partition Density Functionals: Theory and Applications. Final Technical Report

Partition Density Functional Theory is a method to calculate the energy and density of a molecule via self-consistent calculations on isolated fragments. At the start of this project, Partition Density Functional Theory (PDFT) had only been applied to one-dimensional model systems of non-interacting electrons. Its most appealing feature (the reason why PDFT was born in the first place) was that it allowed one to construct an internally-consistent Density Functional Theory (DFT) valid for non-integer electron numbers to be used in the context of Chemical Reactivity Theory. Many formal properties of the quantities entering the theory, such as partition potentials, were unknown when the project started. The connections with other fragment-based electronic structure methods, and especially with embedding theories, were unclear, and the potential of PDFT for fixing problems of approximate exchange-correlation functionals was unanticipated. Supported by grant DE-SC0005031, we made progress in developing, understanding, implementing, and applying PDFT. We discovered its potential for applications in situations where approximate DFT fails, such as when stretching bonds or when calculating the energy of weakly-interacting systems, both cases of importance for energy research applications. We extended PDFT in several directions (spin-densities, current densities, external electric and magnetic fields), and carried out many calculations on diatomic molecules and small clusters to test ideas for approximate non-additive functionals. As a result, we were able to propose physically-motivated fragment-density approximations for both covalent and weak bonds. Because many applications will increasingly benefit from efficient and accurate electronic-structure calculations via density-embedding techniques, the research results enabled by this grant should prove useful for addressing complex problems in a wide variety of fields, from chemistry to molecular biology and materials engineering.