Conical
intersection (CI) seams are configuration spaces of a molecular
system where two or more (spin) adiabatic electronic states are degenerate
in energy. They play essential roles in photochemistry because nonradiative
decays often occur near the minima of the seam, i.e., the minimum
energy CIs (MECIs). Thus, it is important to explore the CI seams
and discover the MECIs. Although various approaches exist for CI seam
exploration, most of them are local in nature, requiring reasonable
initial guesses of geometries and nuclear gradients during the search.
Global search algorithms, on the other hand, are powerful because
they can fully sample the configurational space and locate important
MECIs missed by local algorithms. However, global algorithms are often
computationally expensive for large systems due to their poor scalability
with respect to the number of degrees of freedom. To overcome this
challenge, we develop the parallel on-the-fly
Crystal
algorithm to globally explore the CI seam space, taking advantage
of its superior scaling behavior. Specifically,
Crystal
is coupled with on-the-fly evaluations of the excited and
ground state energies using multireference electronic structure methods.
Meanwhile, the algorithm is parallelized to further boost its computational
efficiency. The effectiveness of this new algorithm is tested for
three types of molecular photoswitches of significant importance in
material and biomedical sciences: photostatin (PST), stilbene, and
butadiene. A rudimentary implementation of the algorithm is applied
to PST and stilbene, resulting in the discovery of all previously
identified MECIs and several new ones. A refined version of the algorithm,
combined with a systematic clustering technique, is applied to butadiene,
resulting in the identification of an unprecedented number of energetically
accessible MECIs. The results demonstrate that the parallel on-the-fly
Crystal
algorithm is a powerful tool for
automated global CI seam exploration.