Literature DB >> 11411997

A combined application of reaction prediction and infrared spectra simulation for the identification of degradation products of s-triazine herbicides.

T Kostka1, P Selzer, J Gasteiger.   

Abstract

Substance identification in analytical chemistry is usually performed by comparing an experimental spectrum with a reference spectrum. Especially in environmental chemistry, reference spectra from databases are only available for a limited number of compounds. The combination of the reaction prediction system EROS and of infrared spectra simulation is a powerful tool for computer-assisted substance identification. First, possible degradation products of a chemical are predicted and then the infrared spectra of all these compounds are simulated. Comparison of the simulated infrared spectra with experimental spectra allows one to identify the structure of compounds. The method is demonstrated with the example of s-triazine herbicides.

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Year:  2001        PMID: 11411997     DOI: 10.1002/1521-3765(20010518)7:10<2254::aid-chem2254>3.0.co;2-#

Source DB:  PubMed          Journal:  Chemistry        ISSN: 0947-6539            Impact factor:   5.236


  1 in total

1.  Deep Learning Spectroscopy: Neural Networks for Molecular Excitation Spectra.

Authors:  Kunal Ghosh; Annika Stuke; Milica Todorović; Peter Bjørn Jørgensen; Mikkel N Schmidt; Aki Vehtari; Patrick Rinke
Journal:  Adv Sci (Weinh)       Date:  2019-01-29       Impact factor: 16.806

  1 in total

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