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handle: 10261/380976
The thermodynamic properties of 778 azaboles, including the known pyrazaboles, imidazaboles, and triazaboles, have been theoretically calculated at the CBS-QB3 level. Pólya enumeration theorem was used to determine the number of skeletons of azaboles (237 neutral systems), followed by an exploration and generation of the whole space of N–H tautomers. The experimental X-ray geometries, B–C and B–N distances and folding angles, were compared with those of the calculated geometries. Using Free-Wilson (or absence-presence) matrices and multiple regression analysis, the fragments’ contribution to different enthalpies was calculated. Finally, a machine learning model based on Gaussian Process Regression has been created to predict the ΔH°f of the azaboles together with their structural characteristics.
This work was carried out with financial support from the Ministerio de Ciencia, Innovación y Universidades (PID2021-125207NB-C32). Open Access funding is provided thanks to the CRUE-CSIC agreement with Springer Nature.
Peer reviewed
Free-Wilson matrices, Machine learning, Gaussian Process Regression, Azaboles, CBS-QB3, Pólya enumeration theorem
Free-Wilson matrices, Machine learning, Gaussian Process Regression, Azaboles, CBS-QB3, Pólya enumeration theorem
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