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Comparison of near-infrared and Raman spectroscopy for on-line monitoring of etchant solutions directly through a Teflon tube

Authors
Kim, JaejinHwang, JinyoungChung, Hoeil
Issue Date
Nov-2008
Publisher
Elsevier BV
Keywords
Etchant solution; Near-infrared spectroscopy; Raman spectroscopy; Prediction robustness; Moving window partial least squares; Spectral selectivity
Citation
Analytica Chimica Acta, v.629, no.1-2, pp 119 - 127
Pages
9
Indexed
SCIE
SCOPUS
Journal Title
Analytica Chimica Acta
Volume
629
Number
1-2
Start Page
119
End Page
127
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/171799
DOI
10.1016/j.aca.2008.09.032
ISSN
0003-2670
1873-4324
Abstract
Both near-infrared (NIR) and Raman spectroscopy have been studied for the quantitative measurement of components (H3PO4, HNO3, and CH3COOH) in an etchant solution and the corresponding prediction robustness has been evaluated. Both measurements were accomplished by illuminating radiation directly through a Teflon tube. Raman spectral features of each component were much clearer and more selective than those observed in the NIR spectrum. Especially, NIR spectral variation pertinent to H3PO4 and HNO3 were mostly based on the displacement and perturbation of water bands rather than due solely to NIR absorption. Therefore, the resulting spectral variations were not highly specific. When the validation set contained minor spectral variations resulting from a slight instrumental change, NIR prediction performance for all three components degraded substantially by showing obvious prediction bias. However, the accuracies of Raman predictions were maintained. Since partial least squares (PLS) models for each component were built using NIR spectra of poor specificity with broadly overlapping features, even minor spectral differences introduced by instrumental variations sensitively influenced the prediction performance of the NIR models. Overall, the selectivity (specificity) of a targeting spectroscopic method should be considered critically to secure prediction robustness for monitoring components in an etchant solution.
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