Dynamic diffusion model for tracing the real-time potential response of polymeric membrane ion-selective electrodes

Area of Science:

• Electrochemistry
• Analytical Chemistry
• Materials Science

Background:

• Ion-selective electrodes (ISEs) are crucial for real-time chemical sensing.
• Understanding potential drifts in ISEs is vital for accurate measurements, especially at low detection limits.
• Existing models often fail to capture complex transient behaviors like potential drifts.

Purpose of the Study:

• To present a numerical solution for predicting the time-dependent potential response of polymeric-based ISEs.
• To model short- and middle-term potential drifts influenced by concentration gradients.
• To provide a tool for understanding real-time potentiometric sensor behavior.

Main Methods:

• Developed a numerical model based on approximate solutions of the diffusion equation.
• Employed a finite difference in time and finite elements in space numerical scheme.
• Applied the model to a silver ionophore-based membrane system (calix[4]arene derivative).

Main Results:

• The model accurately predicts time-dependent potential drifts observed experimentally.
• Achieved good correlation with experimental data, despite lower-than-expected organic phase diffusion coefficients.
• Demonstrated the model's ability to provide previously inaccessible time-dependent information.

Conclusions:

• The numerical model offers valuable insights into the real-time response of ISEs.
• It can address open questions regarding response time and memory effects in low-detection-limit sensors.
• The model is applicable to various membrane electrodes where ion flux is significant.