Researchers Make Important Progress in Density Functional Theory

Kohn–Sham density functional theory is widely used in chemistry, but no functional can accurately predict the whole range of chemical properties, although recent progress by some doubly hybrid functionals comes close. Density functional theory has been a focused research area of Center member and ECNU Professor Xiao He’s research team. Recently, Professor He’s team made a breakthrough by optimizing a singly hybrid functional called CF22D with higher across-the-board accuracy for chemistry than most of the existing non-doubly hybrid functionals. They used physical descriptors, broad databases and supervised learning for the systematic optimization of a flexible functional form including the simultaneous optimization of a molecular-mechanics damped-dispersion term. The study has been published in a recent issue of Nature Computational Science.

Journal Reference:

Liu, Y., Zhang, C., Liu, Z., Truhlar, D. G., Wang, Y., and He, X. Supervised learning of a chemistry functional with damped dispersion. Nat. Comput. Sci. (2022). https://doi.org/10.1038/s43588-022-00371-5

>> To read the article in Chinese at East China Normal University, click here.