Machine Learning to Predict Homolytic Dissociation Energies of C−H Bonds: Calibration of DFT‐based Models with Experimental Data
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DOI: 10.1002/minf.202200193
Abstract: Random Forest (RF) QSPR models were developed with a data set of homolytic bond dissociation energies (BDE) previously calculated by B3LYP/6‐311++G(d,p)//DFTB for 2263 sp3C−H covalent bonds. The best set of attributes consisted in 114 descriptors… read more here.
Keywords: dissociation energies; dft; mae kcal; experimental data ... See more keywords