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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
Published on: April 8, 2020
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An efficient method by combining different basis sets and SAPT levels.
Zhihao Deng1, Chang Liu1, Zhongwei Li2
1Beijing StoneWise Technology Co Ltd., Beijing, China.
Journal of Computational Chemistry
|May 4, 2024
Summary
We developed efficient computational methods for large molecular complexes, improving non-covalent interaction (NCI) predictions. These methods offer accuracy comparable to gold standards with significantly reduced computational cost.
Area of Science:
- Computational Chemistry
- Quantum Chemistry
- Molecular Interactions
Background:
- Accurate calculation of non-covalent interactions (NCI) for large molecular systems (>50 atoms) using symmetry-adapted perturbation theory (SAPT) is computationally expensive with large basis sets.
- Smaller basis sets often lead to inaccurate predictions of dispersion forces and total interaction energies in NCI calculations.
Purpose of the Study:
- To develop computationally efficient yet accurate methods for calculating NCIs in large molecular complexes.
- To improve the prediction of dispersion energies and overall interaction energies compared to standard SAPT approaches.
Main Methods:
- Proposed two composite methods combining SAPT2 calculations with different basis sets (aug-cc-pVDZ and aug-cc-pVTZ) as baselines.
- Incorporated dispersion term corrections at the SAPT2+ level using bond functions and smaller basis sets with MP2 corrections.
Main Results:
- Evaluated methods on benchmark NCI datasets (S22, S66).
- Demonstrated significant improvements in accuracy compared to the original SAPT Silver standard.
- Achieved accuracy comparable to the SAPT Gold standard in certain cases.
Conclusions:
- The proposed composite methods offer a substantial improvement in the accuracy of NCI calculations for large systems.
- These methods provide a computationally feasible alternative to traditional approaches, maintaining high accuracy with reduced cost.
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