Analysis of the current tools for optimization of equilibrium constants from potentiometric data

Cvetkovski, Aleksandar (2024) Analysis of the current tools for optimization of equilibrium constants from potentiometric data. Analytica Chimica Acta 1303 (2024) 342476, 1303.

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Abstract

Defining the distribution of the chemical species in a multicomponent system is a task of great importance with
applications in many fields. To clarify the identity and the abundance of the species that can be formed by the
interaction of the components of a solution, it is fundamental to know the formation constants of those species.
The determination of equilibrium constants is mainly performed through the analysis of experimental data ob-
tained by different instrumental techniques. Among them, potentiometry is the elective technique for this purpose. As such, a survey was run within the NECTAR COST Action – Network for Equilibria and Chemical
Thermodynamics Advanced Research, to identify the most used software for the analysis of potentiometric data
and to highlight their strengths and weaknesses. The features and the calculation processes of each software were
analyzed and rationalized, and a simulated titration dataset of a hypothetic hexaprotic acid was processed by
each software to compare and discuss the optimized protonation constants. Moreover, further data analysis was
also carried out on the original dataset including some systematic errors from different sources, as some cali-
bration parameters, the total analytical concentration of reagents and ionic strength variations during titrations,
to evaluate their impact on the refined parameters. Results showed that differences on the protonation constants
estimated by the tested software are not significant, while some of the considered systematic errors affect results.
Overall, it emerged that software commonly used suffer from many limitations, highlighting the urgency of new
dedicated and modern tools. In this context, some guidelines for data generation and treatment are also given.

Item Type:	Article
Impact Factor Value:	5.7
Subjects:	Medical and Health Sciences > Basic medicine Engineering and Technology > Chemical engineering Natural sciences > Chemical sciences Natural sciences > Computer and information sciences Natural sciences > Matematics Engineering and Technology > Materials engineering
Divisions:	Faculty of Medical Science
Depositing User:	Aleksandar Cvetkovski
Date Deposited:	25 Sep 2024 10:35
Last Modified:	25 Sep 2024 10:35
URI:	https://eprints.ugd.edu.mk/id/eprint/34711

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