Application of soft and hard modeling methods to resolve the three competitive complex formation of 13 lanthanide-Arsenazo III complexes

Kakhki Javad, Abedi, Abedi Mohammad

Description

The applicability of soft and hard modeling methods was used to determine the formation constants of complexes between 3,6-bis[(2-arsonophenyl)azo]-4,5-dihydroxy-2,7-naphtalenedisulphonic acid disodium salt (Arsenazo III) and 13 lanthanides. The results showed that all the 13 lanthanides (M) studied form a similar type of complexes and spectral profiles with Arsenazo III (L) with three formation constants corresponding to M/L ratios of 1:1, 1:2, and 2:2.

Sujets

• Chemometrics
• Lanthanide

Informations

• Publié par: biomed
• Publié le: 01 janvier 2012
• Nombre de lectures: 14
• Langue: English
• Poids de l'ouvrage: 1 Mo

Extrait

Kakhki and AbediInt J Ind Chem2012,3:9 http://www.industchem.com/content/3/1/9

R E S E A R C HOpen Access Application of soft and hard modeling methods to resolve the three competitive complex formation of 13 lanthanideArsenazo III complexes * Javad Fadaee Kakhkiand Mohammad Reza Abedi

Abstract The applicability of soft and hard modeling methods was used to determine the formation constants of complexes between 3,6bis[(2arsonophenyl)azo]4,5dihydroxy2,7naphtalenedisulphonic acid disodium salt (Arsenazo III) and 13 lanthanides. The results showed that all the 13 lanthanides (M) studied form a similar type of complexes and spectral profiles with Arsenazo III (L) with three formation constants corresponding to M/L ratios of 1:1, 1:2, and 2:2. Keywords:Arsenazo III, Chemometrics, Hard modeling, Lanthanides, Soft modeling

Background Spectrophotometric titrations are important methods for the investigation of solution equilibria. The titration consists of a collection of spectra of a solution measured as a func tion of the reagent added which influences the equilibrium under the investigation [1,2]. The proper chemometric algorithms can be used in evaluating the equilibrium information such as the stability constant through analysis of the spectroscopic data. Several soft and hard modeling algorithms have been developed to analyze bilinear data obtained from chemical systems. Soft modeling methods range from very general approaches, such as evolving factor analysis (EFA) [3], which is particularly used to estimate the number of spe cies involved in equilibrium studies and the kinetic process by repeated factor analysis of rationally selected subsets of spectra. Factor analysis investigates the rank of the subset of spectra by determining its number of significant eigen values [4]. Multivariate curve resolutionalternating least squares (MCRALS) [5] is an iterative soft modeling resolution method that has been successfully applied to solve many mixed dynamic processes monitored spectrometrically, such as chromatographic runs [6,7], biomacromolecular reactions [8,9], voltammetric data, and environmental data [1012]. In fact, MCR is a selfmodeling chemometric

* Correspondence: [e-mail] Department of Applied Chemistry, Quchan Branch, Islamic Azad University, Quchan, Iran

discipline that comprises several techniques in establishing an initial model on the data and extracting maximum amount of information from the data. These results are useful to validate hard modeling results and investigate the complex chemical systems [13]. Hard modeling approaches of fitting multivariate re sponse data are based on mathematical relationships, which describe the measurements quantitatively [1416]. In chemical equilibria, the analysis is based on the equilib rium model which quantitatively describes the reaction and all concentrations in the solution under investigation. Within the hard modeling methods, analysis of spectral data has shown an optimal performance on many occa sions [1618]. Hard modeling or modelbased method was used to analyze a given measurement based on a predetermined model. The model can be a simple mathematical function or a complex chemical system that is fitted to a data set. So, it needs to determine the right model to be fitted, such as the exact chemical reaction mechanism in kinetics or the correct equilibrium model in a titration experiment. Unfortunately, it is a very difficult one. There are no gen eral applicable tools available to guide towards finding the model that correctly describes the chemical process under investigation because the model fitting is much easier than model finding. There is a good collection of methods avail able in performing modelfree or soft modeling analyses. Typically, these methods (softmodel) deliver the shapes of the concentration profiles of all reacting components as

© 2012 Fadaee Kakhki and Reza Abedi; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.