Improved Infrared Spectra Prediction by DFT from a New Experimental Database

5 years ago

Improved Infrared Spectra Prediction by DFT from a New Experimental Database

Vincent Steinmetz, Gilles Frison, Madanakrishna Katari, Edith Nicol, Duncan Carmichael, Guillaume van der Rest

This work aims to improve the computation of infrared spectra of gas-phase cations using DFT methods. Experimental infrared multiple photon dissociation (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 hybrids and the range-separated hybrids (RSH) CAM-B3LYP, LC-BLYP, and ωB97X-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, ωB97X-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. Predictive power: 64 experimental vibrational modes, from 10 organometallic complexes, have been measured and used as reference database against which DFT methods have been evaluated. The use of a linear correlation instead of a scaling factor significantly improves the prediction accuracies of all functionals.

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1002/chem.201700340