QTAIM Atomic Charge and Polarization Parameters and
Their Machine-Learning Transference among Boron-Halide Molecules
Posted on 2020-04-16 - 13:06
Atomic charges are
invariant for out-of-plane distortions, making
their molecular vibrations enticing for electronic structure studies.
Of planar molecules, the boron trihalides contain some of the most
polar bonds known to chemistry, although their out-of-plane bending
intensities are very small contrary to expectations from atomic charge
models. Here, the out-of-plane infrared intensities of the BX(2)X(3)X(4) (X(2), X(3), X(4) = H, F, Cl, Br) molecules are investigated using
quantum theory of atoms in molecules atomic charges and atomic dipoles
within the formulism of the charge, charge transfer, dipolar polarization
model at the QCISD/aug-cc-pVTZ quantum level. Dipole moments induced
by equilibrium charge displacement of atoms perpendicular to the molecular
plane are almost completely cancelled by their electronic density
polarizations. The calculated boron trihalide intensities are small
for molecules with such polar bonds ranging from 0.6 to 106.1 km mol–1. Even though the Cl atomic charge of −0.72
e in BCl3 is more negative than the hydrogen values of
−0.67 e in BH3, the hydride out-of-plane intensity
of 82.0 km mol–1 is an order of magnitude larger
than that of the trichloride, 6.3 km mol–1. Owing
to their diverse electronic structures, transference of atomic charges
and dipole parameters among the boron trihalides is extremely challenging
and does not result in accurate intensity values. For this reason,
a machine-learning decision-tree algorithm was used to perform the
transference procedure. Decision trees were optimized using quantum-level
intensity values. Atomic charge and dipole parameters were estimated
for a set of 12 test set molecules. These parameters provided intensity
estimates with a root-mean-square error of 2.1 km mol–1 compared with QCISD/aug-cc-pVTZ reference values.
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Duarte, Leonardo
J.; Bruns, Roy E. (2020). QTAIM Atomic Charge and Polarization Parameters and
Their Machine-Learning Transference among Boron-Halide Molecules. ACS Publications. Collection. https://doi.org/10.1021/acs.jpca.0c01183