Computational modeling of chemical and photochemical
processes in complex systems faces extraordinary challenges in terms of the
first-principle description of molecular motions and chemical reactions (i.e., ab initio molecular dynamics (MD)). The
current state of the art for ab initio MD is to describe the molecular
interactions using density functional theory (DFT), due to DFT's reasonable
compromise between accuracy and computational cost. However, the chemical
sciences are permeated with systems for which the approximations of DFT
fundamentally break down or for which the computational cost of DFT remains
prohibitive for the MD simulation of necessary length- and timescales. The planned research will use quantum
embedding strategies to move ``beyond DFT" in both key dimensions of
higher accuracy and lower computational cost, thereby bringing broad new
chemical and materials application domains within the reach of ab initio MD simulation. The research will pursue theoretical
innovations that include coupling highly correlated system wavefunction methods
with DFT environments, transferable machine-learning methods for electronic
structure, and non-adiabatic dynamics methods based on the Feynman path-integral
framework. The work will address
frontier chemical challenges ranging from non-adiabatic dynamics through
conical intersections in metalloenzymes, to biological transport of energy and
charge, to coupled electron-nuclear quantum dynamics in surface reactions. The
new simulation capabilities will be implemented in open-source,
high-performance and developer friendly packages. The planned work is fully aligned with the
Computational Chemistry Sciences (CCS) objectives by providing new, advanced
capabilities in major open source chemical-simulation software to be used by
the community to take advantage of gains in massively parallel computing
platforms and systematically alleviate the need to employ semi-empirical
corrections. The work will combine
theoretical, computational, and algorithmic advances to increase (1000-fold or
more) the speed of accurate molecular simulation, including methods and
applications that align with the Department of Energy mission in the chemical
sciences, geosciences, and biosciences. The
planned work is particularly well aligned with targeted focus areas that
include multi-scale (i.e., embedding) methods for describing natural and
artificial photochemistry for solar driven energy conversion and storage, approaches
to account for competing dissipative mechanisms (decoherence or other
non-idealities) in molecular systems, and methods for modeling molecular
complexes composed of interfaces.