Linnett is Back: Chemical Bonding through the Lens of Born Maxima.

IF 5.7 1区 化学 Q2 CHEMISTRY, PHYSICAL Journal of Chemical Theory and Computation Pub Date : 2025-02-21 DOI:10.1021/acs.jctc.4c01785
María Menéndez-Herrero, Evelio Francisco, Ángel Martín Pendás
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引用次数: 0

Abstract

The classical Lewis-Langmuir electron pair model remains central to chemical bonding theories despite its inherent contradictions with quantum mechanical principles such as antisymmetry. This paper revisits the long-forgotten Linnett's double quartet (LDQ) model, which integrates spin considerations into chemical bonding. We demonstrate that the distribution of electrons at the maxima of the square of the wave function (Born maxima) highlights the rigidity of the same-spin electron blocks and validates the LDQ framework in atoms and molecules. A generalized LDQ model accounts for all bond types, including covalent, polar covalent, ionic, dative, and electron-deficient, and directly incorporates electron correlation effects, providing a rigorous yet intuitive approach to bonding. This perspective also reveals fundamental flaws in conventional mean-field descriptions that ignore the correlated motion of electrons. By bridging traditional and quantum paradigms, the generalized LDQ model offers a robust tool for understanding chemical bonding, with implications for education, experimental design, and theoretical advancements.

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来源期刊
Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation 化学-物理:原子、分子和化学物理
CiteScore
9.90
自引率
16.40%
发文量
568
审稿时长
1 months
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Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere.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.
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