Improved Infrared Spectra Prediction by DFT from a New Experimental Database

Abstract : This work aims to improve the computation of infrared spectra of gas-phase cations using DFT methods. Experimental IRMPD spectra for ten Zn and Ru organometallic complexes have been used to provide reference data for 64 vibrational modes in the 900-2000 cm-1 range. The accuracy of the IR vibrational frequencies predicted for these bands has been assessed over five DFT functionals and three basis sets. The functionals include the popular B3LYP and M06-2X hydrids and the range-separated hybrids (RSH) CAM-B3LYP, LC-BLYP and B97X-D. B3LYP gives the best mean absolute error (MAE) and root-mean-square error (RMSE) values of 7.1 and 9.6 cm-1 , whilst the best RSH functional, B97X-D, gives 12.8 and 16.6 cm-1 respectively. Using linear correlations instead of scaling factors improves the prediction accuracy significantly for all functionals. Experimental and computed spectra for a single complex can show significant differences even when the molecular structure is calculated correctly, and a means of defining confidence limits for any given computed structure is also provided.
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Madanakrishna Katari, Edith Nicol, Vincent Steinmetz, Guillaume Van der rest, Duncan Carmichael, et al.. Improved Infrared Spectra Prediction by DFT from a New Experimental Database. Chemistry - A European Journal, Wiley-VCH Verlag, 2017, 23 (35), pp.8414 - 8423. ⟨10.1002/chem.201700340⟩. ⟨hal-01673625⟩

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