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Published on: April 8, 2020
Comparison of Explicitly Correlated Methods for Computing High-Accuracy Benchmark Energies for Noncovalent
Dominic A Sirianni1, Lori A Burns1, C David Sherrill1
1Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, School of Computational Science and Engineering, Georgia Institute of Technology , Atlanta, Georgia 30332-0400, United States.
Explicitly correlated methods accurately predict noncovalent interaction energies. Standard augmented correlation-consistent basis sets (aXZ) offer better accuracy than F12 basis sets, with F12b providing the best results for larger basis sets.
Area of Science:
- Computational Chemistry
- Quantum Chemistry
- Theoretical Chemistry
Background:
- Noncovalent interactions are crucial in chemistry and biology.
- Accurate calculation of interaction energies is essential for understanding molecular systems.
- Explicitly correlated methods offer a pathway to high accuracy.
Purpose of the Study:
- To evaluate the reliability of explicitly correlated methods for benchmark noncovalent interaction energies.
- To compare the performance of standard augmented correlation-consistent (aXZ) and specialized F12 basis sets.
- To assess convergence behavior and computational efficiency.
Main Methods:
- Computations using aug-cc-pVXZ (aXZ) and cc-pVXZ-F12 (XZ-F12) basis sets.
- Explicitly correlated coupled cluster singles and doubles [CCSD-F12n (n = a, b, c)] with perturbative triples [(T**)].
- Comparison against estimates of the complete basis set (CBS) limit.
Main Results:
- aXZ basis sets yielded smaller errors compared to the CBS limit than XZ-F12 basis sets.
- The F12b ansatz demonstrated the lowest average errors for triple-zeta (aTZ) and larger basis sets.
- CCSD(T**)-F12b/aXZ exhibited the fastest basis set convergence.
Conclusions:
- Explicitly correlated methods with standard aXZ basis sets provide reliable benchmark noncovalent interaction energies.
- CCSD(T**)-F12b/aTZ and focal point schemes offer comparable accuracy and efficiency.
- These methods are computationally more efficient than large-basis conventional CCSD(T).
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