Theoretical ro-vibrational spectrum of CF(+)

High Accuracy Ab Initio Potential Energy Curves and Dipole Moment Functions for the X1Σ+ and a3Π Spin States of the CF+ Diatomic Molecule

Potential energy curves and dipole moment functions constructed using high-accuracy ab initio methods allow for an in-depth examination of the electronic structure of diatomic molecules. Ab initio computations serve as a valuable complement to experimental data, offering insights into the nature of short-lived molecules such as those encountered within the interstellar medium (ISM). While laboratory experiments provide critical groundwork, the ISM's conditions often permit longer lifetimes for lower stability molecules, enabling unique observations. The CF+ diatomic molecule is one such molecule that has been observed spectroscopically in the ISM. Previous experimental and theoretical work have examined different spectroscopic aspects of the CF+ molecule, but the development of newer, more complete potential energy curves and dipole moment functions allows for even greater insight. We constructed both potential energy curves and dipole moment functions for the ground X1Σ+ and first excited a3Π states of CF+ for both the 12C and 13C isotopologues. The potential energy curves were constructed using coupled cluster with single, double, and perturbative triple excitations (CCSD(T)) at the complete basis set limit with corrections from full triple, quadruple, quintuple, and hextuple excitations within a finite-basis coupled cluster wave function as well as corrections from full configuration interaction and relativistic effects. Rovibrational wave functions were calculated using a vibrational Hamiltonian matrix, which moves beyond the harmonic oscillator approximation. The equilibrium bond length, vibrational constant, and rotational constant were reproduced to within 0.00013 Å, 0.28 cm-1, and 0.00045 cm-1, respectively, of experimental values. Experimental transition energies from rovibrational spectra were reproduced with an error of no larger than 0.63 cm-1. The triplet excited state (a3Π) was found to have a longer equilibrium bond length at 1.21069 Å, a vibrational constant of 1611.29 cm-1, and a rotational constant of 1.56376 cm-1. Rovibrational line lists for the 12C and 13C isotopologues for both the X1Σ+ and the excited a3Π states were generated.

Refining the thermochemical properties of CF, SiF, and their cations by combining photoelectron spectroscopy, quantum chemical calculations, and the Active Thermochemical Tables approach

Fluorinated species have a pivotal role in semiconductor material chemistry and some of them have been detected beyond the Earth's atmosphere. Achieving good energy accuracy on fluorinated species using quantum chemical calculations has long been a challenge. In addition, obtaining direct experimental thermochemical quantities has also proved difficult. Here, we report the threshold photoelectron and photoion yield spectra of SiF and CF radicals generated with a fluorine reactor. The spectra were analysed with the support of ab initio calculations, resulting in new experimental values for the adiabatic ionisation energies of both CF (9.128 ± 0.006 eV) and SiF (7.379 ± 0.009 eV). Using these values, the underlying thermochemical network of Active Thermochemical Tables was updated, providing further refined enthalpies of formation and dissociation energies of CF, SiF, and their cationic counterparts.

Franck-Condon factors using supervised artificial neural networks. I. The CF+ cation

Several studies of the electronic and vibrational structure of CF(+) have been performed since this molecule was first discovered to occur in the interstellar medium, and even before that. However, researchers have paid little attention to calculating its Franck-Condon factors (FCFs), which can aid the identification of this molecule through comparison with the observed intensity spectrum. In this work, an analysis of all of the potential energy curves of CF(+) that were candidates for this kind of calculation was undertaken. The Franck-Condon factors of CF(+) were calculated using a supervised neural network with two layers and a variable learning rate.