Orbital-Corrected Orbital-Free Density Functional Theory

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The dream of theoretical chemistry is highly accurate predictions of condensed-phase phenomena from first principles. Current theoretical methods either cannot consistently treat chemical reactions at a high level of accuracy, or are limited by system size or the time scale of the process. The conventional theoretical treatment of solid-state systems is the standard plane-wave periodic density-functional theory (DFT), but is limited by the scaling of computational cost and the level of accuracy. To achieve better scaling and accuracy, we rely heavily on DFT and improve the existing implementations of DFT. Each of the two ways of solving the DFT problem, i.e., the traditional orbital-based Kohn-Sham (KS) and the orbital-free (OF) schemes, has its own strengths and weaknesses. Recently, we have developed a new implementation of DFT, namely orbital-corrected OF-DFT (OO-DFT), which coalesces the advantages and avoids the drawbacks of OF-DFT and KS-DFT and allows systems within different chemical bonding environments to be studied at a much lower cost than the traditional self-consistent KS-DFT method. For the cubic-diamond Si and the face-centered-cubic Ag systems, OO-DFT accomplishes accuracy comparable to fully self-consistent KS-DFT with at most two non-self-consistent iterations. In this grant period, we will further develop OO-DFT, so that OO-DFT achieves linear scaling by employing currently available linear-scaling KS-DFT algorithms and becomes a powerful tool to treat large systems of thousands of atoms within different chemical bonding environments much more efficiently than other currently available linear-scaling DFT methods. We will implement OO-DFT into ab initio molecular dynamics (AIMD) so that a highly efficient and accurate OO-DFT-based AIMD method will be available for general usage by the entire theoretical/computational chemistry community. In the end, the theoretical techniques will be matured to offer the scientific community a reliable vehicle to provide qualitatively and quantitatively a microscopic understanding of basic mechanisms in complex systems, and to gain insights into aspects of nature that cannot be easily probed by experimental means.