Standard chemistry, with standard materials under standard conditions, can be described by standard density functionals for the exchange-correlation energy that combine a few exact constraints with fitting to molecular data. But such fitting is essentially interpolative, and has limited extrapolative or predictive power to describe new materials or even familiar materials under extreme conditions. More predictive are the functionals that satisfy many more exact constraints and are not fitted to any bonded system. For example, the 2015 SCAN (strongly constrained and appropriately normed) meta-generalized gradient approximation was designed to satisfy all 17 known exact constraints that a computationally-efficient semi-local functional can satisfy, and was further fitted to atoms as well as the uniform electron gas, appropriate norms for which it can be highly accurate or exact. Grimme found SCAN to be more accurate than any other tested functional, including hybrid functionals, for a set of artificial molecules that are not present in any fitting set. SCAN has also been remarkably successful in its predictions of the critical pressures for structural phase transitions, ground-state crystal structures and their formation energies, the distortions and electric polarizations of ferroelectrics, the structure of liquid water, and the strongly-correlated cuprate high-temperature superconducting materials. At greater computational cost, SCAN can be combined with a self-interaction correction that is scaled down in many-electron regions, and the resulting functional might properly describe many other strongly-correlated materials.

Materials of the universe require predictive, first-principles-based density functionals

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.