Quantifying Base-Dependent Lewis Acidity in Substituted Boranes through DFT and Machine Learning
- 1Department of Chemistry and Materials Science, School of Chemical Engineering, Aalto University, 02150 Espoo, Finland
Abstract
The dependence of Lewis acidity on the interacting base is established. Here, density functional theory calculations and machine-learning analysis quantify substituent effects and base dependence within a combinatorial library of 816 trisubstituted boranes constructed from 16 substituents. Interactions with five probe bases (H2O, NH3, C5H5N, PMe3, and Cl–) yield 3927 calculated adduct formation free energies in dichloromethane. Electron-withdrawing substituents generally enhance borane Lewis acidity, whereas electron-donating substituents attenuate it. The magnitude of these effects varies with the base, producing changes and occasional reversals in relative acidity rankings. PMe3 shows the strongest dependence on substituent identity among the investigated bases. Weak linear correlations between isolated-borane global hardness and adduct formation free energy indicate limited predictive power for this single descriptor. Random forest models describe the computed trends, while SHAP analysis identifies the summed Hammett σ p parameter, the borane–base frontier orbital energy gap, and borane electrophilicity as the most influential descriptors in the model. These results provide a quantitative map of substituent effects and the transferability of relative borane acidity rankings across the investigated bases.
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BibTeX
@article{mahdian2026quantifying,
title = {{Quantifying Base-Dependent Lewis Acidity in Substituted Boranes through DFT and Machine Learning}},
author = {Amir Mahdian and Kari Laasonen and Kaveh Farshadfar},
journal = {Inorganic Chemistry},
year = {2026},
month = oct,
doi = {10.1021/acs.inorgchem.6c04676},
url = {https://doi.org/10.1021/acs.inorgchem.6c04676},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Quantifying Base-Dependent Lewis Acidity in Substituted Boranes through DFT and Machine Learning
AU - Amir Mahdian
AU - Kari Laasonen
AU - Kaveh Farshadfar
PY - 2026
DA - 2026/10/19
JO - Inorganic Chemistry
DO - 10.1021/acs.inorgchem.6c04676
UR - https://doi.org/10.1021/acs.inorgchem.6c04676
AB - The dependence of Lewis acidity on the interacting base is established. Here, density functional theory calculations and machine-learning analysis quantify substituent effects and base dependence within a combinatorial library of 816 trisubstituted boranes constructed from 16 substituents. Interactions with five probe bases (H2O, NH3, C5H5N, PMe3, and Cl–) yield 3927 calculated adduct formation free energies in dichloromethane. Electron-withdrawing substituents generally enhance borane Lewis acidity, whereas electron-donating substituents attenuate it. The magnitude of these effects varies with the base, producing changes and occasional reversals in relative acidity rankings. PMe3 shows the strongest dependence on substituent identity among the investigated bases. Weak linear correlations between isolated-borane global hardness and adduct formation free energy indicate limited predictive power for this single descriptor. Random forest models describe the computed trends, while SHAP analysis identifies the summed Hammett σ p parameter, the borane–base frontier orbital energy gap, and borane electrophilicity as the most influential descriptors in the model. These results provide a quantitative map of substituent effects and the transferability of relative borane acidity rankings across the investigated bases.
SN - 0020-1669
SN - 1520-510X
ER -