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Tensammetric Analysis of Nonionic Surfactant Mixtures by Artificial Neural Network
Author(s) -
Safavi A.,
Sedaghatpour F.,
Shahbaazi H. R.
Publication year - 2005
Publication title -
electroanalysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 128
eISSN - 1521-4109
pISSN - 1040-0397
DOI - 10.1002/elan.200403225
Subject(s) - nonionic surfactant , aqueous solution , pulmonary surfactant , adsorption , mercury (programming language) , artificial neural network , electrode , chromatography , chemistry , capacitive deionization , materials science , capacitive sensing , analytical chemistry (journal) , electrochemistry , organic chemistry , computer science , artificial intelligence , biochemistry , programming language , operating system
An artificial neural network (ANN) model has been developed for tensammetric determination of a series of Brijes (Brij 30, Brij 35, Brij 56, Brij 96) as nonionic surfactants. The tensammetric method is based on the measurement of the capacitive current of the mercury electrode after adsorption of surfactants. All Brijes were analyzed in the concentration range of 1.0–100.0 μg mL −1 . The proposed method shows good sensitivity and applicability to the simultaneous determination of mixtures of four Brijes in aqueous solutions.