Rui Yuting, Chen Yuxinxin, Ivanova Elena, Kumar Vignesh Balaji, Śmiga Szymon, Grabowski Ireneusz, Dral Pavlo O
State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, Xiamen University, Xiamen, Fujian, 361005, China.
Chair of Statistics, School of Business and Economics, Humboldt University of Berlin, Unter den Linden 6, 10099, Berlin, Germany.
Adv Sci (Weinh). 2024 Dec;11(47):e2408239. doi: 10.1002/advs.202408239. Epub 2024 Oct 25.
The development of better density functional theory (DFT) methods is one of the most active research areas, given the importance of DFT for ubiquitous molecular and materials simulations. However, this research primarily focuses on improving a specific exchange-correlation Kohn-Sham density functional. Here, a robust procedure is proposed for constructing transferable ensembles of density functionals that perform superior to any constituent individual density functional. It is shown that such ensembles built only with the density functionals predating the GMTKN55 benchmark of 2017 can reach a record-low weighted error of 1.62 kcal mol on this benchmark compared to 3.08 kcal mol of the best constituent density functional. The DENS24 density functional ensembles are also introduced as practical DFT methods with consistently accurate performance for various simulations at affordable cost. DENS24 ensembles are open-source and can be used for simulations online. Additionally, it is shown that the ensembles can be integrated into the SCF procedure by creating mixed DENS24 functionals, which have the same accuracy but are faster than ensembles of independent functionals.
鉴于密度泛函理论（DFT）在无处不在的分子和材料模拟中的重要性，开发更好的DFT方法是最活跃的研究领域之一。然而，这项研究主要集中在改进特定的交换关联科恩-沙姆密度泛函。在此，提出了一种稳健的程序，用于构建性能优于任何组成单个密度泛函的可转移密度泛函集合。结果表明，仅用2017年GMTKN55基准之前的密度泛函构建的此类集合，在此基准上可达到创纪录的低加权误差1.62千卡/摩尔，而最佳组成密度泛函的误差为3.08千卡/摩尔。还引入了DENS24密度泛函集合，作为实用的DFT方法，以可承受的成本在各种模拟中具有一致准确的性能。DENS24集合是开源的，可用于在线模拟。此外，结果表明，通过创建混合DENS24泛函，集合可以集成到自洽场程序中，混合DENS24泛函具有相同的精度，但比独立泛函的集合更快。
