  In this paper, we study the nuclear gradients of heat bath configuration
interaction self-consistent field (HCISCF) wave functions and use them to
optimize molecular geometries for various molecules. We show that the HCISCF
nuclear gradients are fairly insensitive to the size of the "selected"
variational space, which allows us to reduce the computational cost without
introducing significant error. The ability of HCISCF to treat larger active
spaces combined with the flexibility for users to control the computational
cost makes the method very attractive for studying strongly correlated systems
which require a larger active space than possible with complete active space
self-consistent field (CASSCF). Finally, we study the realistic catalyst,
Fe(PDI), and highlight some of the challenges this system poses for density
functional theory (DFT). We demonstrate how HCISCF can clarify the energetic
stability of geometries obtained from DFT when the results are strongly
dependent on the functional. We also use the HCISCF gradients to optimize
geometries for this species and study the adiabatic singlet-triplet gap. During
geometry optimization, we find that multiple near-degenerate local minima exist
on the triplet potential energy surface.
