Abstract:An integrated approach combing density functional theory (DFT) and machine learning algorithm (MLA) is proposed here to obtain the molar heat capacities and entropies of diatomic macroscopic gasses with high quality. The DFT approach takes care of the main physical effects, while machine learning takes care of the intricate details it leaves out. After machine learning algorithm correction, a complete set of accurate prediction of vibrational energy spectrum is obtained, which is better than the results of DFT… Show more
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