Inferring Molecular Descriptors and Chemical Reactivity Rules from Diatomic Molecular Data

Abstract

Chemical concepts such as electronegativity and chemical hardness, initially defined before the advent of computational quantum chemistry, remain central to interpreting and guiding experimental chemistry. While modern computational methods yield vast numerical data, translating these outputs into chemically intuitive concepts remains essential. This thesis evaluates fundamental reactivity rules derived from conceptual density functional theory—specifically, the Maximum Hardness Principle (MHP), Minimum Electrophilicity Principle (MEP), and the |∆μ| Big is Good (DMB) rule—using a computationally generated dataset of approximately half a million diatomic acid–base double-exchange reactions.

Benchmarking revealed that MHP and MEP reliably predict reaction outcomes, particularly under conditions aligning with the hard/soft acid–base classification and moderate bond stretching. In contrast, the DMB principle exhibited considerable sensitivity to atomic reference-state choices, bond distances, and the nature of participating elements, clearly limiting its broad practical applicability. This limitation prompted a reconsideration of the widely accepted relationship between electronegativity and electronic chemical potential, μ = −χ, motivating the development of a novel electronegativity scale.

Addressing these challenges, a new electronegativity scale was developed via a graph-theoretic approach, representing intramolecular charge transfers as a directed, weighted graph. Using a minimum feedback-arc set (MFAS) ranking method combined with manifold-learning techniques, this scale provides a numerically stable, chemically intuitive electronegativity ranking. The resulting scale closely aligns with established values for main-group elements and demonstrates robustness when extended to heavier atoms. Importantly, this methodology is readily extendable beyond atomic species, enabling future studies to accurately quantify the electronegativities of functional groups and ions, broadening its utility in mechanistic studies and rational chemical design.