A layman's guide to cutting your way through the web of DFT functionals, explaining GGAs, mGGAs, hybrids, range-separated hybrids, double hybrids, and dispersion corrections.

A layman's guide to neural network potentials (NNPs), which can run high-accuracy atomistic simulations many orders of magnitude faster than traditional quantum mechanics (QM) simulations.

Here, we report that the vDZP basis set can be used with a wide variety of density functionals to produce efficient and accurate results comparable to those of composite methods without reparameterization.

In this study, we investigate AIMNet2, a machine-learned interatomic potential, as a low-cost surrogate for electronic structure theory in pKa prediction.

How it's used at present, and opportunities for the future.