Marinella de Giovanetti, Rodrigo A. Cormanich and Stephan P. A. Sauer*,
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引用次数: 0
Abstract
This study evaluates the performance of doubles-corrected random phase approximation (RPA) and higher random phase approximation (HRPA) approaches in predicting nuclear magnetic resonance (NMR) coupling constants involving fluorine. Their performance is benchmarked against experimental data and compared with that of higher-level theoretical methods, specifically second-order polarization propagator (SOPPA) and SOPPA(CCSD). Additionally, we discuss their performance relative to density functional theory (DFT). We find that RPA(D) is severely constrained by (near) triplet instabilities, while HRPA(D) demonstrates markedly improved stability. Statistical analysis reveals stronger patterns for carbon–fluorine couplings across the methods and systems investigated compared with fluorine–hydrogen couplings. While SOPPA-based methodologies prove to be superior in accuracy, HRPA(D) shows promising performance in reducing the computational burden of these calculations, albeit with a tendency to underestimate the coupling strength. These findings highlight the potential of HRPA(D) as a practical alternative to SOPPA methods, even for such difficult properties as NMR spin–spin coupling constants involving fluorine, emphasizing its role in improving predictive accuracy and efficiency across diverse chemical environments.
期刊介绍:
The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.