A joint data and model driven method for study diatomic vibrational spectra including dissociation behavior

Achieving vibrational energies of diatomic systems with high quality by machine learning improved DFT method

When using ab initio methods to obtain high-quality quantum behavior of molecules, it often involves a lot of trial-and-error work in algorithm design and parameter selection, which requires enormous time and computational resource costs. In the study of vibrational energies of diatomic molecules, we found that starting from a low-precision DFT model and then correcting the errors using the high-dimensional function modeling capabilities of machine learning, one can considerably reduce the computational burden and improve the prediction accuracy. Data-driven machine learning is able to capture subtle physical information that is missing from DFT approaches. The results of ¹²C¹⁶O, ²⁴MgO and Na³⁵Cl show that, compared with CCSD(T)/cc-pV5Z calculation, this work improves the prediction accuracy by more than one order of magnitude, and reduces the computation cost by more than one order of magnitude.

A method for predicting the molar heat capacities of HBr and HCl gases based on the full set of molecular rovibrational energies

A new method is presented for one to obtain the molar heat capacities of diatomic macroscopic gas with a full set of microscopic molecular rovibrational energies. Based on an accurate experimental vibrational energies subset of a diatomic electronic ground state, the full vibrational energies can be obtained by using the variational algebraic method (VAM), the potential energy curves (PECs) will be constructed by the Rydberg-Klein-Rees (RKR) method, the full set of rovibrational energies will be calculated by the LEVEL program, and then the partition functions and the molar heat capacities of macroscopic gas can be calculated with the help of the quantum statistical ensemble theory. Applying the method to the ground state HBr and HCl gases, it is found that the relative errors of the partition functions calculated in the temperature range of 300 ∼ 6000 K are in excellent agreement with those obtained from TIPS database, and the calculated molar heat capacities are closer to the experimental values than those calculated by other methods without considering the energy levels of highly excited quantum states. The present method provides an effective new way for one to obtain the full set of molecular rovibrational energies and the molar heat capacities of macroscopic gas through the microscopic spectral information of a diatomic system.

A data- and model-driven strategy for the evaluation of the experimental transition lines: Theoretical prediction for the ground state of 12C16O

An analytical formula that relates the molecular constants of the Herzberg expression and experimental transition lines is developed herein with a difference algebraic approach (DAA) model. Based on the data-driven strategy, the DAA model is able to deal with the tiny uncertainties that exhibit behind the experimental transition lines, which is applied to the P branch emission spectra of some first overtone bands of the ground electronic state of ¹²C¹⁶O. The relationship can be used to generate transition lines with sufficient accuracy, as evident from the high J of agreement with the HITRAN database, Velichko data, Goorvitch data and quantum-mechanical data. In addition, line intensities, absorption oscillator strengths and Einstein A coefficients of these lines, which are introduced to enhance the dataset and are in good agreement with those of other authors, are also reported to validate our results. These various comparative results show that the proposed data-driven strategy based on the DAA model is expecting to be a good algorithm that relies on relatively limited data for training.

Study on potential energy curves and ro-vibrational energies of DT, HT and T2 molecules

Accurately monitoring and effectively controlling the tritium compounds based on their ro-vibrational energy structure are important issues in various nuclear systems. Because of their radioactivity, it is difficult to obtain the corresponding energies directly through experiments. In this paper, the potential energy curves and the corresponding ro-vibrational full spectrum of DT, HT and T₂ systems are derived by ab initio methods. However, it is difficult to verify the reliability of the calculated results due to the lack of direct experimental support. Therefore, a data-driven reliability analysis method is proposed, which can confirm the reliability by extracting information from the relevant calculations and multiple experimental data (the vibrational level, rotational level, and molar heat capacity) of similar systems (HD, H₂, D₂). The results show that: 1) The potential energy curves obtained by the ab initio method can provide the full ro-vibrational energy spectrum with an accuracy of approximately 10 cm^-1; 2) Macroscopic heat capacity information can be used to distinguish and calibrate the overall reliability of microscopic ro-vibrational energies; 3) For the isotopic energy level structure of hydrogen, the influence of isotopes is mainly mass effect.