An experimental procedure based on neural network processing of time-sequence-selected absorbance spectra is described, having the aim of reducing the whole uncertainty of chromium(VI) concentration in water measurements, preventing bias error due to a non-negligible presence of interfering substance, in particular Sn(II). Aspects concerning the instrumentation system, operating steps and data processing procedure are analysed in order to evaluate uncertainty causes and their effects on the whole uncertainty of the methodology, which try to enhance flow injection analysis capabilities, taking into account requirements of method reproducibility and standardization. Chromium solutions in water in the range 0–500 μg l−1, with Sn(II) concentration ranging from 0 to 20 mg l−1, have been analysed by this modified flow injection method. A satisfactory error reduction and a warning when the presence of Sn(II) is detected have been achieved. The effect of pH on the method results is also studied.

Flow Injection Absorbance Spectra Time Processing for the Determination of Cr(VI) in the Presence of Sn(II) as Interfering Substance

D'EMILIA, Giulio;EMANUELA NATALE
2007-01-01

Abstract

An experimental procedure based on neural network processing of time-sequence-selected absorbance spectra is described, having the aim of reducing the whole uncertainty of chromium(VI) concentration in water measurements, preventing bias error due to a non-negligible presence of interfering substance, in particular Sn(II). Aspects concerning the instrumentation system, operating steps and data processing procedure are analysed in order to evaluate uncertainty causes and their effects on the whole uncertainty of the methodology, which try to enhance flow injection analysis capabilities, taking into account requirements of method reproducibility and standardization. Chromium solutions in water in the range 0–500 μg l−1, with Sn(II) concentration ranging from 0 to 20 mg l−1, have been analysed by this modified flow injection method. A satisfactory error reduction and a warning when the presence of Sn(II) is detected have been achieved. The effect of pH on the method results is also studied.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/13218
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