ArticleJournal of chemical theory and computation2025
Understanding DFT Uncertainties for More Reliable Reactivity Predictions by Advancing the Analysis of Error Sources.
Article in Journal of chemical theory and computation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- The Different Levels of Quantum: A Methodological-Philosophical Portrait of Computational Quantum Chemistry.ACS physical chemistry Au · 2026Review
- Probing Weak Halogen Bonding in Aqueous Solution.Journal of the American Chemical Society · 2026Article
- Systematically Improvable and Locality Accelerated Enzymatic Reactivity Modeling: Toward Chemical Accuracy at Affordable Cost.Journal of chemical theory and computation · 2026Article
- Knowles Partitioning from a Stationary Condition: Single- and Multireference Case.Journal of chemical theory and computation · 2025Article
- Hybrid DFT Quality Thermochemistry and Environment Effects at GGA Cost via Local Quantum Embedding.Journal of chemical theory and computation · 2025Article
- Near-Basis-Set-Limit Double-Hybrid DFT Energies with Exceptionally Low Computational Costs.The journal of physical chemistry letters · 2025Article
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Authors and funding
3 authors.
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Abstract
Decades of advancements and thousands of successful applications have contributed to the reliability of density functional theory (DFT) methods. Especially in main group chemistry, DFT predictions tend to be increasingly more reliable. In this study, we deeply analyze unexpected (ca. 8-13 kcal/mol) DFT disagreements obtained for a few organic reactions using only widely adopted, modern, hybrid, and higher-rung DFT methods. To understand the underlying causes, we move beyond conventional statistics-based benchmarks by combining recent advances in DFT error decomposition with affordable gold-standard references. This approach helps to characterize and disentangle multiple functional and density-based error types and enables us to find functional(s) suitable for broad mechanistic studies in all studied examples. The proposed tools are cost-efficient, readily accessible, and easy to integrate into routine thermochemistry workflows. While the focus is on main group reactions, the approach is also applicable to transition metal, bio-, and surface chemistry to assist more predictive reactivity modeling.
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Registered trials
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