Казанский (Приволжский) федеральный университет, КФУ
КАЗАНСКИЙ
ФЕДЕРАЛЬНЫЙ УНИВЕРСИТЕТ
 
SIMULTANEOUS VOLTAMMETRIC DETERMINATION OF PHENOLIC ANTIOXIDANTS WITH CHEMOMETRIC APPROACHES
Форма представленияСтатьи в зарубежных журналах и сборниках
Год публикации2014
Языканглийский
  • Будников Герман Константинович, автор
  • Евтюгин Геннадий Артурович, автор
  • Зиятдинова Гузель Камилевна, автор
  • Савельев Анатолий Александрович, автор
  • Библиографическое описание на языке оригинала Ziyatdinova, G.K. Simultaneous voltammetric determination of phenolic antioxidants with chemometric approaches / G.K. Ziyatdinova, A.A. Saveliev, G.A. Evtugyn, H.C. Budnikov // Electrochim. Acta. - 2014. - V. 137. - P. 114-120.
    Аннотация This work is devoted to the new approach for the description of voltammograms with overlapped peaksof individual analytes. The prediction of individual concentration is achieved by decomposition of entire voltammogram using radial basis function approach followed by fitting the curves using linear model and artificial neural net. The analytical case study is the direct determination of three phenolic antioxidants, i.e., tert-butylhydroquinone, 3-tert-butyl-4-hydroxyanisole and propyl gallate. The artificial mixtures contained their binary and ternary solutions in the range of concentration from 0.25 to 1.00 mM. The results of decomposition were first checked on similarity of recorded and reconstructed voltammograms followed by determination of individual concentrations by least square method (linear model fitting) and feed-forward artificial net consisting of two hidden layers with 7 and 3 neurons. The relative standard deviation of 0.03-0.07 can be obtained.
    Ключевые слова Voltammetric detection of antioxidants, radial basis function method, artificial neural networks, sterically hindered phenols
    Название журнала ELECTROCHIMICA ACTA
    Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на эту карточку https://repository.kpfu.ru/?p_id=107830

    Полная запись метаданных