Number of species in complexation equilibria of o-, m- and p- CAPAZOXS with Cd super(2+), Co super(2+), Ni super(2+), Pb super(2+) and Zn super(2+) ions by PCA of UV-vis spectra

• Published in: Talanta (Oxford) Vol. 71; no. 1; pp. 115 - 122
• Main Authors: Meloun, Milan, Syrovy, Tomas
• Format: Journal Article
• Language: English
• Published: 01.01.2007
• ISSN: 0039-9140
• DOI: 10.1016/j.talanta.2006.03.035

A critical comparison of the selected derivative principal component analysis (PCA) methods on the absorbance matrix data concerning the complexation equilibria between o-CAPAZOXS and Cd super(2+), Pb super(2+) and Zn super(2+) or m-CAPAZOXS and Cd super(2+), Co super(2+), Ni super(2+) and Zn super(2+) or p-CAPAZOXS and Cd super(2+) and Zn super(2+) at 25 degree C is provided. As the number of complex species in a complex-forming equilibria mixture is an important step in spectral data treatment, the nine selected index functions for the prediction of the number of light-absorbing species that contribute to a set of spectra is critically tested by the PCA. An improved identification with the second SD(AE) or third derivative TD(AE) and derivative ratio function ROD(AE) for the average error criterion AE is preferred. After the number of various complexes formed the stability constants of species ML, ML sub(2) (and ML sub(3), respectively) type log beta sub(11), log beta sub(12) (and log beta sub(13), respectively) for the system of o-CAPAZOXS (ligand L) with the metals (the standard deviation s(log beta sub(pq)) of the last valid digits is given in brackets) Cd super(2+) (6.39(5) and 11.51(9)), Pb super(2+) (4.24(2) and 9.01(2)) and Zn super(2+) (5.18(7) and 9.06(10)) and for the system of m-CAPAZOXS with Cd super(2+) (6.59(20) and 11.51(32)), Co super(2+) (7.19(6) and 12.19(8)), Ni super(2+) (7.64(7) and 13.39(12)) and Zn super(2+) (4.83(3) and 9.57(3)) and for the system of p-CAPAZOXS with Cd super(2+) (6.44(5), 10.99(10) and 14.57(25)) and Zn super(2+) (6.84(16), 13.05(29) and 18.74(43)) at 25 degree C are estimated using SQUAD(84) nonlinear regression of the mole-ratio spectrophotometric data. The computational strategy is presented with goodness-of-fit tests and various regression diagnostics capable of proving the reliability of the chemical model proposed.