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Local Quadrupole Ellipticity as Predictor of Anion‐Affinity in Nanographenes.

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Title: Local Quadrupole Ellipticity as Predictor of Anion‐Affinity in Nanographenes.
Authors: Charapale, Omkar1 (AUTHOR), Posada‐Pérez, Sergio2 (AUTHOR), Poater, Albert1 (AUTHOR), Solà, Miquel1 (AUTHOR) miquel.sola@udg.edu
Source: Journal of Computational Chemistry. 5/15/2026, Vol. 47 Issue 13, p1-11. 11p.
Subjects: Quadrupole moments, Electrostatics, Graphene, Molecular recognition
Abstract: Anion binding to nanographenes is governed by noncovalent interactions, particularly anion–π interactions in electron‐deficient aromatic regions and CH‐‐‐anion hydrogen bonding in electron‐rich domains. These interactions are primarily driven by electrostatic effects, with the quadrupole moment of the aromatic system playing a central role in determining the strength and directionality of anion–π binding. The perpendicular component of the quadrupole moment (Qzz) correlates with binding energies for both anion–π and CH‐‐‐anion interactions, though polycyclic systems present challenges due to competing interaction modes. In this study, we investigate the role of the local quadrupole moment in anion binding across 171 Cl−–aromatic complexes, comparing various descriptors including aromaticity indices, Fukui functions, and electron density at ring critical points. We find that electrostatic descriptors, particularly the local quadrupole moment, provide a more consistent and robust explanation for binding energies than conventional descriptors. Specifically, two geometric descriptors derived from the local quadrupole moment—the scale factor (SRmax$$ {S}_R^{max} $$) and the ellipticity (ec′$$ {e}_c^{\prime } $$)—show good correlation with binding strength, with SRmax$$ {S}_R^{max} $$ reflecting π‐acidity and ellipticity quantifying charge distribution anisotropy. These descriptors are validated across fluorinated naphthalenes and nanographenes, demonstrating their general applicability. Regression models based on SRmax$$ {S}_R^{max} $$ and ec′$$ {e}_c^{\prime } $$ effectively predict binding energies, with enhanced accuracy when combined with polarization‐dependent penalty functions, especially for larger nanographene systems. While the predictive model is still somewhat constrained by polarization effects, its simplicity, robustness, and transferability across a wide range of systems offer distinct advantages over more complex, multilayered machine learning models. These results underscore the critical role of quadrupole moment anisotropy in anion–π interactions and offer a practical framework for predicting anion binding affinities and designing π‐acidic receptors. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:Anion binding to nanographenes is governed by noncovalent interactions, particularly anion–π interactions in electron‐deficient aromatic regions and CH‐‐‐anion hydrogen bonding in electron‐rich domains. These interactions are primarily driven by electrostatic effects, with the quadrupole moment of the aromatic system playing a central role in determining the strength and directionality of anion–π binding. The perpendicular component of the quadrupole moment (Qzz) correlates with binding energies for both anion–π and CH‐‐‐anion interactions, though polycyclic systems present challenges due to competing interaction modes. In this study, we investigate the role of the local quadrupole moment in anion binding across 171 Cl−–aromatic complexes, comparing various descriptors including aromaticity indices, Fukui functions, and electron density at ring critical points. We find that electrostatic descriptors, particularly the local quadrupole moment, provide a more consistent and robust explanation for binding energies than conventional descriptors. Specifically, two geometric descriptors derived from the local quadrupole moment—the scale factor (SRmax$$ {S}_R^{max} $$) and the ellipticity (ec′$$ {e}_c^{\prime } $$)—show good correlation with binding strength, with SRmax$$ {S}_R^{max} $$ reflecting π‐acidity and ellipticity quantifying charge distribution anisotropy. These descriptors are validated across fluorinated naphthalenes and nanographenes, demonstrating their general applicability. Regression models based on SRmax$$ {S}_R^{max} $$ and ec′$$ {e}_c^{\prime } $$ effectively predict binding energies, with enhanced accuracy when combined with polarization‐dependent penalty functions, especially for larger nanographene systems. While the predictive model is still somewhat constrained by polarization effects, its simplicity, robustness, and transferability across a wide range of systems offer distinct advantages over more complex, multilayered machine learning models. These results underscore the critical role of quadrupole moment anisotropy in anion–π interactions and offer a practical framework for predicting anion binding affinities and designing π‐acidic receptors. [ABSTRACT FROM AUTHOR]
ISSN:01928651
DOI:10.1002/jcc.70393