论文标题
S66x8非共价互动重新审视：复合局部耦合群集方法的新基准和性能
S66x8 Noncovalent Interactions Revisited: New Benchmark and Performance of Composite Localized Coupled-Cluster Methods
论文作者
论文摘要
S66X8非共价相互作用基准已在“纯银”水平上进行了重新评估，使用明确相关的MP2-F12在完整基集限制附近，CCSD（F12*）/aug-cc-cc-pvtz-f12和a（t）（t）（t）（t）从常规ccsd（t）ccsd（t）ccsd（t）/sano-sano-v} z+ ccsd（t）。修订后的参考值与原始的Hobza基准及其对Brauer等人的修订不一致，但仅从Kesharwani等人的Aust的“青铜”水平数据中使用0.04 kcal/mol。 J. Chem。 71，238-248（2018）。然后，我们使用它们来评估有或没有反平衡校正的局部轨道耦合群集方法的性能，例如在Molpro中实现的PNO-LCCSD（T），DLPNO-CCSD（T1）在ORCA中实现，以及在MRCC中实现的MRCC，如他们所在的STERTIVE forneveive normal normal''和and''＆cright''＆cright''我们还考虑了结合不同基集和截止的复合方法。此外，为了隔离域截断误差的基础集合，对于AUG-CC-PVTZ基集，我们将PNO，DLPNO和LNO接近的汇聚与规范CCSD（t）进行了比较。 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一个复合方案，例如紧密{t，q} +1.11 [vvtight（t） - tight（t）]。相比之下，PNO-LCCSD（t）在反平衡方面最有效，而dlpno-ccsd（T1）的性能是可比的。在更经济的方法中，对于DRPA75-D3BJ，ωB97M-V，ωB97M（2），RevDSD-PBBEP86-D4和DFT（SAPT），具有最高的精度，带有TDEXX或ATDEXX kernel。
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 value disagrees by 0.1 kcal/mol RMS with the original Hobza benchmark and its revision by Brauer et al, but by only 0.04 kcal/mol variety from the "bronze" level data in Kesharwani et al., Aust. J. Chem. 71, 238-248 (2018). 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 (T1) 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(T1). 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.
