Modern computational and theoretical approaches accurately quantify molecular aromaticity
Modern computational methods, including density functional theory and advanced quantum chemical descriptors, successfully and accurately quantify molecular aromaticity across various chemical systems and external conditions.
The claim states that modern computational and theoretical approaches accurately quantify molecular aromaticity. The retrieved literature features numerous recent studies (e.g., Papers 0, 1, 8, 9, 10, and 11) utilizing state-of-the-art density functional theory, quantum chemical calculations, and multidimensional descriptors (such as HOMA, NICS, PDI, and MCI) to systematically quantify and analyze aromaticity in diverse molecular environments and under various conditions. None of the papers refute this capacity; instead, they demonstrate its active application and refinement. Therefore, the balance of evidence strongly supports the claim.
Charapale O, Posada-Pérez S, Poater A, Solà M. Does Aromaticity Drive Metal Cation Binding to Nanographenes? Insights Into Regioselectivity and Cation- $$ \pi $$ Bonding.. 2026. https://doi.org/10.1002/jcc.70337
Paper 0 uses quantum chemical methods, ring-based reactivity descriptors, and topological indicators to accurately predict local aromaticity and cation interactions in nanographenes.
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Eeckhoudt J, Dellwisch A, Plump A, Zeller F, Neudecker T, De Proft F, Alonso M. How to evaluate aromaticity under pressure? Benzene as a benchmark system.. 2026. https://doi.org/10.1039/d5sc07920a
Paper 1 uses state-of-the-art quantum chemical methodologies and complementary structural, electronic, and magnetic descriptors to evaluate aromaticity under pressure.
Dar SH, Zhu J. Substituent-modulated adaptive aromaticity in NHC-pyrrolyl cations: a combined DFT and machine learning study.. 2026. https://doi.org/10.1039/d6cp00728g
Paper 8 employs density functional theory and multiple aromaticity descriptors (HOMA, NICS, MCI, ACID, EDDB) alongside machine learning to quantify substituent-modulated adaptive aromaticity.
Lin X, Wei M, Mo Y. Craig Excited-State Aromaticity in Metallabenzenes: How, When, and Why?. 2026. https://doi.org/10.1021/jacs.5c18055
Paper 9 applies ab initio valence bond theory and diverse aromaticity indices to demonstrate and quantify Craig excited-state aromaticity in metallabenzenes.
Shankar A. Hydration-induced modulation of aromaticity and reactivity in anthocyanidins: a quantum mechanical study.. 2026. https://doi.org/10.1039/d5ra05334j
Paper 10 uses quantitative assessment tools like HOMA and PDI to accurately evaluate how hydration modulates the aromaticity of anthocyanidins across different rings.
Dehkordi PN, Saeidian H, Mirjafary Z, Rouhani M. Schleyer-type hyperconjugative aromaticity in CH isomers of diazoles revealed by DFT and NBO analysis.. 2026. https://doi.org/10.1038/s41598-026-35776-z
Paper 11 employs density functional theory and multicriteria indices (HOMED, BI, NICS) to quantify Schleyer-type hyperconjugative aromaticity in diazole isomers.
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