Use of circular dichroism and artificial neural networks for the kinetic-spectrophotometric resolution of enantiomers

Marcelo Blanco, Jordi Coello, Hortensia Iturriaga, Santiago Maspoch, Marta Porcel

Research output: Contribution to journalArticleResearchpeer-review

13 Citations (Scopus)

Abstract

The circular dichroism (CD) technique was used to resolve 1-phenylethylamine enantiomers by their differential rate of reaction under non-pseudo first-order kinetic conditions with the chiral feagent (-)-citronellal. The same reaction was also monitored under pseudo first-order conditions using UV-VIS spectrophotometry and the results provided by the two techniques were compared by using principal component regression (PCR), partial least-squares regression (PLSR) and artificial neural networks (ANNs) for multivariate calibration. The best results were obtained by compressing the data matrix provided by the CD technique with principal component analysis (PCA) and using the scores of the principal components as input for the ANN. The relative standard error (R.S.E.) of prediction thus obtained was about 3% for both enantiomers. © 2001 Elsevier Science B.V.
Original languageEnglish
Pages (from-to)115-123
JournalAnalytica Chimica Acta
Volume431
Issue number1
DOIs
Publication statusPublished - 8 Mar 2001

Keywords

  • 1-Phenylethylamine
  • Artificial neural networks
  • Circular dichroism
  • Enantiomers
  • Kinetic-spectrophotometric methods

Fingerprint Dive into the research topics of 'Use of circular dichroism and artificial neural networks for the kinetic-spectrophotometric resolution of enantiomers'. Together they form a unique fingerprint.

Cite this