The objective of this research is to develop
SPARC-X: a computational framework for performing Kohn-Sham Density Functional
Theory (DFT) calculations that scale linearly with the number of atoms in the
system, leveraging petascale/exascale parallel computers to study chemical
phenomena at unprecedented length and time scales. SPARC-X will exploit a
recent breakthrough in electronic structure methodologies: systematically
improvable, strictly local, orthonormal, discontinuous real-space bases that efficiently
and systematically capture the local chemistry of the system. With further
adaptation using new machine-learning techniques and the use of the massively
parallel Spectral Quadrature (SQ) electronic structure method, the algorithmic
complexity and prefactor associated with DFT calculations involving semilocal
as well as hybrid functionals will be dramatically reduced. Using petascale computational
resources, SPARC-X will enable quantum mechanical simulations at length and
time scales previously accessible only by empirical approaches, e.g., 100,000
atoms for a few picoseconds using semilocal functionals or 1,000 atoms for a few
nanoseconds using hybrid functionals. Using future exascale resources, the
sizes and times targeted are two orders of magnitude larger. Such a capability
has applications in a wide variety of chemical sciences, including reactive
interfaces where large length- and/or long time-scales are needed and
traditional force fields fail. This is particularly important in the dynamics of
catalysis, where bond breaking and formation must be understood in detail. This
project will develop, test, and apply the SPARC-X framework to understand the
photocatalytic properties of TiO_{2} systems with and without Au
co-catalysts for nitrogen transformations. This integrated development and application
strategy will ensure that SPARC-X is a robust, efficient, and scalable software
package for quantum simulations on current petascale and future exascale
computing resources.