Francisco J. Martin-Martinez

Conceptual Density Functional Theory (DFT) is a powerful framework for rationalising chemical reactivity at both the molecular and atomic levels. To compress local reactivity information, such as atom-condensed Fukui functions, into a single, chemically meaningful global scalar, we introduce the Gini reactivity descriptor (G), which adapts an economic inequality index to quantify how unevenly atom-condensed reactivity is distributed across molecules. Using the Quantum Theory of Atoms in Molecules (QTAIM) to partition spatial descriptors into atom-resolved scalars and applying a Gini-based socio-economic analysis to the distribution of reactivity descriptors, we quantify the reactivity inequality among individual atoms within their molecular context. Validated on controlled molecular series and applied to large molecular datasets, we demonstrate that the Gini reactivity descriptor provides a compact, physically grounded bridge between local electronic structure and global reactivity. In combination with traditional Conceptual DFT descriptors, these quantities define a multivariate reactivity space for molecular design, with direct implications for chemical feature engineering in machine-learning workflows and high-throughput molecular screening.