Determination of ion-selective electrode characteristics by non-linear curve fitting

Area of Science:

• Electrochemistry
• Analytical Chemistry
• Chemical Sensing

Background:

• Ion-selective electrodes (ISEs) are crucial for ion concentration measurements.
• Accurate determination of electrode characteristics, such as potentiometric selectivity coefficients, is essential for reliable ISE performance.
• Existing methods for determining these coefficients can be complex or require specialized software.

Purpose of the Study:

• To develop a simple and practical method for determining potentiometric selectivity coefficients of ion-selective electrodes (ISEs).
• To enable the calculation of electrode characteristics including slope, selectivity coefficients, and cell constant using readily available software.
• To demonstrate the method's flexibility with different ISEs and theoretical models.

Main Methods:

• Utilized the fixed interference (FI) method to collect experimental data.
• Applied non-linear least-squares regression to fit the experimental data to appropriate theoretical models.
• Employed the 'Solver' add-on in Microsoft Excel for data processing and model fitting.

Main Results:

• A simple, practical method for determining ISE potentiometric selectivity coefficients was successfully developed.
• Electrode characteristics (slope, selectivity coefficients, cell constant) can be accurately determined using this approach.
• The method demonstrated flexibility by modeling a valinomycin potassium-selective electrode using both the Nikolskii-Eisenman equation and an alternative model for unequal ionic charges.

Conclusions:

• The proposed method offers a simple, practical, and accessible approach for characterizing ion-selective electrodes.
• Non-linear regression analysis with Microsoft Excel's Solver is effective for processing ISE data.
• This method facilitates accurate determination of potentiometric selectivity coefficients, enhancing the reliability of ion-selective electrode measurements.