Structural characterization of carbonyl compounds by IR spectroscopy and chemometrics data analysis

Although there are some distinctive peaks in mid-IR region of the electromagnetic spectrum for carbonyl compounds, it is very difficult to assign a FT-IR spectrum to a specific carbonyl functional group due to the presence of other functional groups, which change the position of the distinctive peaks. Here, we analyzed the FT-IR spectra of a large set of carbonyl compounds by chemometrics methods to differentiate between the different carbonyl functional groups. FT-IR spectra of 370 carbonyl compounds (149 carboxylic acids, 47 aldehydes, 110 esters and 64 ketones) were collected from the Spectral Database for Organic Compounds and then were converted to digital data using a home-made program. The extended canonical variate analysis combined with partial least squares discriminate analysis method (ECVA-PLS-DA) was employed as a supervised classification method. Classification analysis by ECVA-PLS-DA resulted in a suitable classification model such that one can discriminate between the different carbonyl compounds using FT-IR spectra with a small error. The classification errors (reported as percentage of misclassified compounds) were 1.8% and 7.8% for training and test sets, respectively. Considering high structural diversity of the studied compounds and the employment of different methods for acquiring the spectra (i.e., KBr disk, CCl4 solution, liquid film and Nujol moll) there are acceptable errors. Thus, it is concluded that with the help of chemometrics methods, one is able to differentiate the carbonyl compounds using their IR spectra without need to extra spectroscopic information. This can be considered as a significant improvement in structural characterization of organic compounds using only IR spectroscopy.

► Characterization of carbonyl compounds by chemometrics analysis was achieved.
► ECVA could efficiently differentiate the carbonyl compounds based IR spectra.
► In comparison with PLS, ECVA achieved better.
► ECVA could assign carbonyl compounds to their own functional group using IR spectra.