Halide ion-selective electrode array calibration.

Area of Science:

• Analytical Chemistry
• Electrochemistry
• Chemometrics

Background:

• Ion-selective electrodes (ISEs) are crucial for measuring specific ion concentrations in various matrices.
• Accurate calibration of ISE arrays is essential, particularly in the presence of interfering ions.
• Multivariate calibration techniques offer potential for improved accuracy in complex analytical systems.

Purpose of the Study:

• To evaluate the effectiveness of multivariate calibration methods for ISE array calibration.
• To assess the performance of partial least squares regression (PLSR) and principal component regression (PCR) compared to multivariate linear regression (MLR).
• To determine the optimal calibration strategy for ISE measurements under varying interference conditions.

Main Methods:

• Experimental design was employed to systematically study the calibration process.
• Multivariate calibration methods, including PLSR, PCR, and MLR, were applied to ISE array data.
• Test set prediction was used to evaluate the accuracy and reliability of the calibration models.

Main Results:

• Multivariate linear regression (MLR) provided comparable test set prediction accuracy to PLSR and PCR.
• PLSR and PCR did not demonstrate significant improvements over MLR for the tested ISE array.
• Univariate calibration methods are sufficient for accurate ion determination when minimal or no interference is present.

Conclusions:

• For ISE arrays with minimal interference, univariate calibration is a viable and effective method.
• Complex multivariate methods like PLSR and PCR offer no significant advantage over MLR in this specific application.
• Multivariate calibration, including MLR, does not negatively impact results even when simpler methods suffice.