Li Hanwei, Brémond Eric, Sancho-García Juan Carlos, Adamo Carlo
Chimie ParisTech, PSL Research University, CNRS, Institute of Chemistry for Health and Life Sciences F-75005 Paris France
Université de Paris, ITODYS, CNRS F-75006 Paris France.
RSC Adv. 2021 Jul 29;11(42):26073-26082. doi: 10.1039/d1ra04108h. eCollection 2021 Jul 27.
A collection of five challenging datasets, including noncovalent interactions, reaction barriers and electronic rearrangements of medium-sized hydrocarbons, has been selected to verify the robustness of double-hybrid functionals used in conjunction with the small DH-SVPD basis set, especially developed for noncovalent interactions. The analysis is completed by other, more standard functionals, for a total of 17 models, including also empirical corrections for dispersion. The obtained results show that the chemical accuracy threshold, that is an error lower than 1.0 kcal mol, can be obtained by pairing the nonempirical PBE-QIDH functional with the DH-SVPD basis set, as well as by other semi-empirical functionals, such as DSD-PBEP86, using larger basis sets and empirical corrections. More in general, a significant improvement can be obtained using the DH-SVPD basis set with DHs, without resorting to any empirical corrections. This choice leads to a fast computational protocol that, avoiding any empirical potential, remains on a fully quantum ground.
已选择了一组包含五个具有挑战性的数据集,包括中等大小烃类的非共价相互作用、反应势垒和电子重排,以验证与专门为非共价相互作用开发的小基组DH-SVPD结合使用的双杂化泛函的稳健性。分析由其他更标准的泛函完成,总共17个模型,还包括色散的经验校正。所得结果表明,通过将非经验性的PBE-QIDH泛函与DH-SVPD基组配对,以及通过其他半经验泛函,如使用更大基组和经验校正的DSD-PBEP86,可以达到低于1.0 kcal mol的化学精度阈值。一般来说,使用带有双杂化泛函的DH-SVPD基组,无需任何经验校正,就能得到显著改善。这种选择产生了一种快速计算方案,该方案避免了任何经验势,完全基于量子理论。