Application the computational method KINMODEL(AGDC) to the simultaneous determination of kinetic and analytical parameters

In a preliminary work we developed a computational method of kinetic treatment (KINMODEL(AGDC)) and studied the possibilities of its application for the determination of kinetic and non-kinetic parameters. In this new work, we studied the kinetic and/or analytical applicability of the KINMODEL(AGDC)...

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Bibliographic Details
Published in:Applied mathematics and computation 2013-02, Vol.219 (12), p.7089-7101
Main Authors: Canedo Alonso, M.M., González-Hernández, J.L., Encinar del Dedo, S.
Format: Article
Language:English
Subjects:
C (programming language)
Computation
Computational chemical kinetics
Computational program
Constants
Kinetic modeling
Mathematical analysis
Mathematical models
Optimization
Reaction kinetics
Reaction mechanisms
Resolution of mixtures
Unconstrained optimization
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Summary:In a preliminary work we developed a computational method of kinetic treatment (KINMODEL(AGDC)) and studied the possibilities of its application for the determination of kinetic and non-kinetic parameters. In this new work, we studied the kinetic and/or analytical applicability of the KINMODEL(AGDC) program in a broad series of reactions of different complexities: (a) Simple reactions (reversible and irreversible), (b) Consecutive (reversible and irreversible), (c) Concurrent, (d) Competitive, (e) Cyclic. KINMODEL(AGDC) is a computational method that uses the AGDC mathematical optimization algorithm to determine different types of parameters. It is valid for the treatment of any reaction mechanism and allows the determination of different parameters from absorbance data. In all the reactions system included in the a, b, c, d and e groups, the KINMODEL(AGDC) methodology was applied for the determination of the initial concentrations of the species involved in the reaction mechanism, individually or jointly, with the kinetic constants of the elementary reactions comprising the mechanism. We analyze the influence of an extensive series of factors affecting the optimization process: the nature and number of the parameters to be optimized, the initial estimations of the parameters, the reaction mechanism and the relative values of the different rate constants of the mechanism considered. Since parameters of different natures and orders of magnitude are determined, we analyze the possibility of the existence of ambiguity in the solutions since it is common to find several (two or more) groups of parameters that fit the experimental kinetic data.
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2013.01.029