4.6 Article

Accuracy of DLPNO-CCSD(T): Effect of Basis Set and System Size

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JOURNAL OF PHYSICAL CHEMISTRY A
卷 125, 期 7, 页码 1553-1563

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AMER CHEMICAL SOC
DOI: 10.1021/acs.jpca.0c11270

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资金

  1. Australian Research Council [DE160100807]
  2. Australian Government Research Training Program Scholarship
  3. Australian Research Council [DE160100807] Funding Source: Australian Research Council

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The DLPNO-CCSD(T) method offers cost-efficient study of large molecular systems but errors increase with system size, particularly in barrier calculations. Comparisons with canonical CCSD(T) calculations reveal challenges in calculating absolute and relative barriers for reactions, impacting predictions such as stereoselectivity.
The DLPNO-CCSD(T) method is designed to study large molecular systems at significantly reduced cost relative to its canonical counterpart. However, the error in this approach is also size-extensive and relies on cancellation of errors for the calculation of relative energies. This work provides a direct comparison of canonical CCSD(T) and TightPNO DLPNO-CCSD(T) calculations of reaction energies and barriers of a broad range of chemical reactions. The dataset includes acidities, anion binding affinities, enolization, Diels-Alder, nucleophilic substitution, and atom transfer reactions and complements existing theoretical datasets in terms of system size as well as new reaction types (e.g., anion binding affinities and chlorine atom transfer reactions). The performance of DLPNO-CCSD(T) was further examined with respect to systematic variation of basis set and system size and amounts of nonbonded interaction present in the system. The errors in the DLPNO-CCSD(T) were found to be relatively insensitive to the choice of basis set for small systems but increase monotonically with system size. Additionally, calculations of barriers appear to be more challenging than reaction energies with errors exceeding 5 kJ mol(-1) for many Diels-Alder reactions. Further tests on three realistic organic reactions reveal the impact of the DLPNO approximation in calculating absolute and relative barriers that are important for predictions such as stereoselectivity.

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