arXiv subjects

Miruna T. Cretu

Publications and source records attributed to Miruna T. Cretu.

3 recordsLinked to original sources

arXiv2022

Ion-atom-atom three-body recombination in cold hydrogen and deuterium plasmas

We present a detailed study about ion-atom-atom three-body recombination in hydrogen and deuterium plasmas based on classical trajectory calculations in hyperspherical coordinates. Our results, due to the predominant role of the long-range charged-induced dipole interaction, indicate that H$_2^+$ and D$_2^+$ are the main reaction products in the case of hydrogen and deuterium plasmas, respectively. Besides, we find a more steep energy-dependent reaction rate when the collision energy surpasses the dissociation energy of the molecular ion, thus entering a new dynamical regime dominated by short-range interactions.

physics.atom-ph↗

arXiv2021

Dynamics of translational and rotational thermalization of AlF molecules via collisions with cryogenic helium

We investigated helium-mediated translational and rotational thermalization of the aluminum monofluoride (AlF) molecule at cryogenic temperatures via a new $ab \ initio$ potential energy surface (PES) and quantum multichannel scattering theory. Our examination of the elastic and rotationally inelastic channels revealed that helium is an efficient quencher of AlF at temperatures relevant to buffer gas cooling experiments ($\sim1$ mK to $10$ K). We also showed that this conclusion is robust against possible inaccuracies of the PES.

physics.chem-ph↗

arXiv2020

Predicting second virial coefficients of organic and inorganic compounds using Gaussian Process Regression

We show that by using intuitive and accessible molecular features it is possible to predict the temperature-dependent second virial coefficient of organic and inorganic compounds using Gaussian process regression. In particular, we built a low dimensional representation of features based on intrinsic molecular properties, topology and physical properties relevant for the characterization of molecule-molecule interactions. The featurization was used to predict second virial coefficients in the interpolative regime with a relative error $\lesssim 1\% $ and to extrapolate the prediction to temperatures outside of the training range for each compound in the dataset with a relative error of 2.14\%. Additionally, the model's predictive abilities were extended to organic molecules unseen in the training process, yielding a prediction with a relative error of 2.66\%. Therefore, apart from being robust, the present Gaussian process regression model is extensible to a variety of organic and inorganic compounds.

physics.chem-ph↗