Literature DB >> 10826615

Rapid access to infrared reference spectra of arbitrary organic compounds: scope and limitations of an approach to the simulation of infrared spectra by neural networks

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Abstract

Substance identification by infrared spectroscopy is performed by comparison of the experimental spectrum with a reference spectrum from a printed compilation or a database. If the analyzed compound can not be found in a database the corresponding reference spectrum has to be simulated. In order to achieve this, several reasonable candidates of structures for the compound at hand have to be conceived and for all these, infrared spectra have to be developed. The simulated spectrum that is most similar to the experimental suggests the correct structure. A rapid spectrum prediction method based on neural networks has been developed that supplies reference spectra for any organic compound. The scope and limitations of this method will be discussed on a test set of 16 compounds representing a broad range of organic chemistry.

Year:  2000        PMID: 10826615     DOI: 10.1002/(sici)1521-3765(20000303)6:5<920::aid-chem920>3.0.co;2-w

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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