INVESTIGADORES
GOICOECHEA Hector Casimiro
artículos
Título:
Experimental study of non-linear second-order analytical data with focus on the second-order advantage
Autor/es:
JULIA CULZONI,; PATRICIA DAMIANI,; GARCIA-REIRIZ; GOICOECHEA, HÉCTOR C; ALEJANDRO OLIVIERI,
Revista:
ANALYST
Editorial:
The Royal Society of Chemistry
Referencias:
Lugar: Londres; Año: 2007 p. 654 - 663
ISSN:
0003-2654
Resumen:
Three different experimental systems have been studied regarding the determination of analytes in
complex samples, using non-linear second-order instrumental data, which are intrinsically able to
provide the second-order advantage. This permits the quantitation of calibrated analytes in the
presence of unexpected sample components, although a suitable algorithm is required. The
recently described combination of artificial neural networks with post-training residual
bilinearization has been applied to the three data sets, with successful results concerning
prediction accuracy and precision, as well as profile recovery for the potential interferents in test
samples. The studies involve: (1) the determination of two pharmaceuticals in the presence of an
unexpected excipient by absorbancepH matrix measurements, (2) the quantitation of iron(II) by
its catalytic effect on the kinetics of the bromate oxidation of a colorant in the presence of a
second interfering organic dye, and (3) the analysis of the antibiotic amoxicillin by fluorescence
excitationemission matrices in the presence of a fluorescent anti-inflammatory. The prediction
results were compared and shown to be significantly better than those yielded by the unfolded
partial least-squares/residual bilinearization model, due to the non-linear nature of the studied data.
its catalytic effect on the kinetics of the bromate oxidation of a colorant in the presence of a
second interfering organic dye, and (3) the analysis of the antibiotic amoxicillin by fluorescence
excitationemission matrices in the presence of a fluorescent anti-inflammatory. The prediction
results were compared and shown to be significantly better than those yielded by the unfolded
partial least-squares/residual bilinearization model, due to the non-linear nature of the studied data.
its catalytic effect on the kinetics of the bromate oxidation of a colorant in the presence of a
second interfering organic dye, and (3) the analysis of the antibiotic amoxicillin by fluorescence
excitationemission matrices in the presence of a fluorescent anti-inflammatory. The prediction
results were compared and shown to be significantly better than those yielded by the unfolded
partial least-squares/residual bilinearization model, due to the non-linear nature of the studied data.
its catalytic effect on the kinetics of the bromate oxidation of a colorant in the presence of a
second interfering organic dye, and (3) the analysis of the antibiotic amoxicillin by fluorescence
excitationemission matrices in the presence of a fluorescent anti-inflammatory. The prediction
results were compared and shown to be significantly better than those yielded by the unfolded
partial least-squares/residual bilinearization model, due to the non-linear nature of the studied data.
II) by
its catalytic effect on the kinetics of the bromate oxidation of a colorant in the presence of a
second interfering organic dye, and (3) the analysis of the antibiotic amoxicillin by fluorescence
excitationemission matrices in the presence of a fluorescent anti-inflammatory. The prediction
results were compared and shown to be significantly better than those yielded by the unfolded
partial least-squares/residual bilinearization model, due to the non-linear nature of the studied data.