Santra Golokesh, Semidalas Emmanouil, Mehta Nisha, Karton Amir, Martin Jan M L
Department of Molecular Chemistry and Materials Science, Weizmann Institute of Science, 7610001 Reḥovot, Israel.
School of Molecular Sciences, The University of Western Australia, Perth, WA 6009, Australia.
Phys Chem Chem Phys. 2022 Oct 27;24(41):25555-25570. doi: 10.1039/d2cp03938a.
The S66x8 noncovalent interactions benchmark has been re-evaluated at the "sterling silver" level, using explicitly correlated MP2-F12 near the complete basis set limit, CCSD(F12*)/aug-cc-pVTZ-F12, and a (T) correction from conventional CCSD(T)/sano-V{D,T}Z+ calculations. The revised reference values differ by 0.1 kcal mol RMS from the original Hobza benchmark and its revision by Brauer , but by only 0.04 kcal mol RMS from the "bronze" level data in Kesharwani , , 2018, , 238-248. We then used these to assess the performance of localized-orbital coupled cluster approaches with and without counterpoise corrections, such as PNO-LCCSD(T) as implemented in MOLPRO, DLPNO-CCSD(T) as implemented in ORCA, and LNO-CCSD(T) as implemented in MRCC, for their respective "Normal", "Tight", and "very Tight" settings. We also considered composite approaches combining different basis sets and cutoffs. Furthermore, in order to isolate basis set convergence from domain truncation error, for the aug-cc-pVTZ basis set we compared PNO, DLPNO, and LNO approaches with canonical CCSD(T). We conclude that LNO-CCSD(T) with veryTight criteria performs very well for "raw" (CP-uncorrected), but struggles to reproduce counterpoise-corrected numbers even for veryveryTight criteria: this means that accurate results can be obtained using either extrapolation from basis sets large enough to quench basis set superposition error (BSSE) such as aug-cc-pV{Q,5}Z, or using a composite scheme such as Tight{T,Q} + 1.11[vvTight(T) - Tight(T)]. In contrast, PNO-LCCSD(T) works best with counterpoise, while performance with and without counterpoise is comparable for DLPNO-CCSD(T). Among more economical methods, the highest accuracies are seen for dRPA75-D3BJ, ωB97M-V, ωB97M(2), revDSD-PBEP86-D4, and DFT(SAPT) with a TDEXX or ATDEXX kernel.
已在“标准银”水平上重新评估了S66x8非共价相互作用基准,使用了接近完整基组极限的显式相关MP2-F12、CCSD(F12*)/aug-cc-pVTZ-F12,以及来自传统CCSD(T)/sano-V{D,T}Z+计算的(T)校正。修订后的参考值与原始的霍布扎基准及其由布劳尔进行的修订相差0.1 kcal/mol RMS,但与凯沙瓦尼等人2018年的“青铜”水平数据仅相差0.04 kcal/mol RMS(第238 - 248页)。然后,我们使用这些数据来评估有无平衡校正的定域轨道耦合簇方法的性能,例如MOLPRO中实现的PNO-LCCSD(T)、ORCA中实现的DLPNO-CCSD(T)以及MRCC中实现的LNO-CCSD(T)在其各自“正常”“紧密”和“非常紧密”设置下的性能。我们还考虑了结合不同基组和截止值的复合方法。此外,为了将基组收敛与域截断误差区分开来,对于aug-cc-pVTZ基组,我们将PNO、DLPNO和LNO方法与正则CCSD(T)进行了比较。我们得出结论,具有非常紧密标准的LNO-CCSD(T)对于“原始”(未校正CP)情况表现非常好,但即使对于非常非常紧密的标准,也难以重现平衡校正后的数值:这意味着可以使用从足够大的基组进行外推以消除基组叠加误差(BSSE),例如aug-cc-pV{Q,5}Z,或者使用复合方案,如Tight{T,Q} + 1.11[vvTight(T) - Tight(T)]来获得准确结果。相比之下,PNO-LCCSD(T)在有平衡校正时效果最佳,而DLPNO-CCSD(T)在有和没有平衡校正时的性能相当。在更经济的方法中,dRPA75-D3BJ、ωB97M-V、ωB97M(2)、revDSD-PBEP86-D4以及带有TDEXX或ATDEXX核的DFT(SAPT)具有最高的精度。