Lao Ka Un
Department of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, USA.
J Chem Phys. 2024 Dec 21;161(23). doi: 10.1063/5.0242359.
In this study, we introduce two datasets for nanoscale noncovalent binding, featuring complexes at the hundred-atom scale, benchmarked using coupled cluster with single, double, and perturbative triple [CCSD(T)] excitations extrapolated to the complete basis set (CBS) limit. The first dataset, L14, comprises 14 complexes with canonical CCSD(T)/CBS benchmarks, extending the applicability of CCSD(T)/CBS binding benchmarks to systems as large as 113 atoms. The second dataset, vL11, consists of 11 even larger complexes, evaluated using the local CCSD(T)/CBS method with stringent thresholds, covering systems up to 174 atoms. We compare binding energies obtained from local CCSD(T) and fixed-node diffusion Monte Carlo (FN-DMC), which have previously shown discrepancies exceeding the chemical accuracy threshold of 1 kcal/mol in large complexes, with the new canonical CCSD(T)/CBS results. While local CCSD(T)/CBS agrees with canonical CCSD(T)/CBS within binding uncertainties, FN-DMC consistently underestimates binding energies in π-π complexes by over 1 kcal/mol. Potential sources of error in canonical CCSD(T)/CBS are discussed, and we argue that the observed discrepancies are unlikely to originate from CCSD(T) itself. Instead, the fixed-node approximation in FN-DMC warrants further investigation to elucidate these binding discrepancies. Using these datasets as reference, we evaluate the performance of various electronic structure methods, semi-empirical approaches, and machine learning potentials for nanoscale complexes. Based on computational accuracy and stability across system sizes, we recommend MP2+aiD(CCD), PBE0+D4, and ωB97X-3c as reliable methods for investigating noncovalent interactions in nanoscale complexes, maintaining their promising performance observed in smaller systems.
在本研究中,我们引入了两个用于纳米级非共价结合的数据集,其特点是包含百原子规模的复合物,并使用耦合簇单双激发及微扰三重激发[CCSD(T)]外推至完备基组(CBS)极限进行基准测试。第一个数据集L14包含14个具有标准CCSD(T)/CBS基准的复合物,将CCSD(T)/CBS结合基准的适用性扩展到了多达113个原子的系统。第二个数据集vL11由11个更大的复合物组成,使用具有严格阈值的局部CCSD(T)/CBS方法进行评估,涵盖了多达174个原子的系统。我们将局部CCSD(T)和固定节点扩散蒙特卡罗(FN-DMC)得到的结合能与新的标准CCSD(T)/CBS结果进行比较,此前在大型复合物中这两种方法显示出超过1 kcal/mol化学精度阈值的差异。虽然局部CCSD(T)/CBS在结合不确定性范围内与标准CCSD(T)/CBS一致,但FN-DMC在π-π复合物中始终低估结合能超过1 kcal/mol。讨论了标准CCSD(T)/CBS中潜在的误差来源,我们认为观察到的差异不太可能源于CCSD(T)本身。相反,FN-DMC中的固定节点近似值得进一步研究以阐明这些结合差异。以这些数据集为参考,我们评估了各种电子结构方法、半经验方法和机器学习势对纳米级复合物的性能。基于跨系统尺寸的计算精度和稳定性,我们推荐MP2+aiD(CCD)、PBE0+D4和ωB97X-3c作为研究纳米级复合物中非共价相互作用的可靠方法,它们在较小系统中保持了有前景的性能。