Infrared spectra simulation of substituted benzene derivatives on the basis of a 3D structure representation

The identification of chemical compounds from their infrared spectra faces new challenges from novel experimental techniques such as combinatorial chemistry. To rapidly provide estimates for the infrared spectra of candidate structures, an empirical approach to the modeling of the relationships between the 3D structure of a molecule and its infrared spectrum has been developed. This method is based on a novel 3D structure representation and a powerful modeling technique, a counterpropagation neural network, A dataset of 871 mono-, di-, and trisubstitued benzene derivatives is analyzed with this approach.