Synergy of Machine Learning and Density Functional Theory Calculations for Predicting Experimental Lewis Base Affinity and Lewis Polybase Binding Atoms
Hieu Huynh,
Khanh Le,
Linh Vu
et al.
Abstract:Investigation of Lewis acid-base interactions has been conducted by ab initio calculations and Machine Learning (ML) models. This study aims to resolve two critical tasks that have not been quantitatively investigated. First, ML models developed from Density Functional Theory (DFT) calculations predict experimental BF3 affinity with Pearson correlation coefficients around 0.9 and mean absolute errors around 10 kJ mol-1. The ML models are trained by DFT-calculated BF3 affinity of more than 3000 adducts, with in… Show more
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