Consider updating your workflow(s) in Spartan'24

Energies and Equilibrium Geometries: As a long time Spartan user, I have followed the change in default computational models used for structure (Equilibrium Geometry) over the years. From HF/3-21G to HF/6-31G* to B3LYP/6-31G* to the current wB97X-D/6-31G*, as computers have improved in speed and memory resources, the once challenging has become in many cases, trivial. . .
There are some properties (like structure) where the current default computational models are within experimental error (in other words, one can't really do much better than "on par" with experimental data). Other items, like energy (for example), appear to benefit significantly from newer generation functionals and larger basis sets.
In general, beginning with Spartan'24, my typical baseline computational workflow for new molecules is changing. After some six months or more working with our machine learning models (and after revisions and improvements all around), I am more inclined to embrace the neural network models (where available)…






