PALIRS combines active learning with MACE neural network potentials and a dipole moment model to predict infrared spectra of small organic molecules at a fraction of the DFT cost.
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Leveraging active learning-enhanced machine-learned interatomic potential for efficient infrared spectra prediction
PALIRS combines active learning with MACE neural network potentials and a dipole moment model to predict infrared spectra of small organic molecules at a fraction of the DFT cost.