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Frontispiece: Improved Infrared Spectra Prediction by DFT from a New Experimental Database
Author(s) -
Katari Madanakrishna,
Nicol Edith,
Steinmetz Vincent,
van der Rest Guillaume,
Carmichael Duncan,
Frison Gilles
Publication year - 2017
Publication title -
chemistry – a european journal
Language(s) - English
Resource type - Reports
SCImago Journal Rank - 1.687
H-Index - 242
eISSN - 1521-3765
pISSN - 0947-6539
DOI - 10.1002/chem.201783564
Subject(s) - benchmark (surveying) , infrared spectroscopy , infrared , mass spectrometry , scaling , spectral line , quantum chemical , infrared multiphoton dissociation , set (abstract data type) , function (biology) , computer science , quantum , algorithm , materials science , chemistry , physics , molecule , mathematics , optics , quantum mechanics , geology , geometry , geodesy , evolutionary biology , biology , programming language
Prediction of gas phase infrared spectra can be improved by correcting DFT results by using a linear function instead of a scaling factor, as has been demonstrated through an approach combining organometallic synthesis, mass spectrometry, IRMPD spectroscopy, and quantum chemical calculations. The experimental studies have provided a new data set which is used to benchmark DFT methods. A means of defining confidence limits for any given computed structure is provided, for more details see the Full Paper by G. Frison et al. on page 8414 ff.