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Quantification of Lewis Acidity and Lewis Basicity: A Density-Based Reactivity Theory Study
Lian Zhuo1, Yaqin Zheng1, Lei Zeng1
1College of Chemistry and Chemical Engineering, Hunan Normal University, Changsha, Hunan, China.
Predicting Lewis acidity and basicity is now more accurate using density-based reactivity theory and machine learning. This approach quantifies these chemical properties effectively, enhancing understanding across disciplines.
Area of Science:
- Quantum Chemistry
- Chemical Reactivity Theory
Background:
- Lewis acidity and basicity are fundamental concepts in chemistry and biology.
- Accurate prediction and calculation of these properties remain a significant challenge.
Purpose of the Study:
- To develop a quantitative method for predicting Lewis acidity and basicity.
- To explore descriptors from density-based reactivity theory for this purpose.
Main Methods:
- Analysis of Lewis acids and bases using global and local descriptors from conceptual density functional theory (DFT).
- Application of an information-theoretic approach within DFT.
- Identification of electronic properties like frontier molecular orbitals and atomic charges as descriptors.
- Construction of machine-learning models for prediction.
Main Results:
- Lewis acidity and basicity were effectively quantified using DFT-derived descriptors.
- Electronic properties such as frontier molecular orbitals and atomic charges proved to be robust predictors.
- Machine-learning models achieved high accuracy in predicting Lewis acidity and basicity.
- A strong correlation was found between Lewis acidity/basicity and electrophilicity/nucleophilicity.
Conclusions:
- Density-based frameworks provide a powerful foundation for quantitatively characterizing Lewis acidity and basicity.
- The developed methods offer high fidelity in predicting these crucial chemical concepts.
- This work bridges conceptual frameworks and offers a novel approach to understanding the hard and soft acids and bases principle.
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