QSPR Modeling for Predicting Sensitivity of Membrane Sensors based on Modified Diphenylphosphoryl Acetamide Ionophores

Potentiometric sensors, known as ion-selective electrodes, are widely used for measuring ion concentrations in aqueous solutions [1] due to their simplicity, portability, cost-effectiveness, and accuracy. Among the different types of ion-selective electrodes, those with plasticized polymeric membranes have gained significant attention due to their adjustable analytical performance such as selectivity and sensitivity by modifying the active substance, ion-exchanger, solvent-plasticizer and, most important, lipophilic ligands, or ionophores.

Discovering novel and effective ionophores for different ions is a complex and time-consuming process involving guesses about ionophore structure, synthetic availability assessment, synthesis, purification, preparation of sensor membranes, and electrochemical characterization. Despite these efforts, the resulting sensors may not meet the desired characteristics for practical analytical applications.

Recent studies have demonstrated the effectiveness of the Quantitative Structure-Property Relationship (QSPR) approach in predicting sensor properties based on ionophore structure [2]. In this approach, molecular descriptors representing structural properties are related to the property of interest through mathematical modeling. This study aims to extend the application of QSPR to predict the sensitivity of novel ionophores towards three heavy metal ions: Cu²⁺, Cd²⁺, and Pb²⁺, in potentiometric sensors. The study focuses on four new diphenylphosphoryl acetamides ionophores, which have shown increased extraction ability towards metal ions. The reasonable correspondence was found between model predictions and experimental sensitivity values.

References:

1. Zdrachek, E., Bakker, E. Potentiometric Sensing. Anal. Chem. 2021, 93(1), 72-102.
2. Vladimirova, N., Polukeev, V., Ashina, J., Babain, V., Legin, A., Kirsanov, D. Prediction of Carbonate Selectivity of PVC-Plasticized Sensor Membranes with Newly Synthesized Ionophores through QSPR Modeling. Chemosensors 2022, 10, 43.