Performance modelling of zeolite-based potentiometric sensors

Developing simple and cost-effective electrochemical sensors for widespread on-site application is of considerable practical importance in agriculture, environmental monitoring and food science. Among multiple sensing platforms, potentiometry is particularly effective in terms of simplicity, low cost and mass-production. This work is focused on a systematic analysis of the structure – performance relationship using chemometric techniques, which can be applied to sensor arrays with varying response patterns. The potentiometric sensitivity of zeolite-modified electrodes, containing thirteen synthetic and three natural zeolites, in aqueous solutions of Na+, K+, NH4+, Ca2+ and Mg2+ has been correlated with a range of zeolite characteristics using PCA and PLS modelling, thus demonstrating how structural and physical properties impact the performance of zeolite-modified potentiometric sensors. In addition to steric factors, e.g. zeolite pore size, the important characteristics governing the sensor performance are the Si/Al ratio and the presence of specific extraframework cations. For instance, K+ and Na+ show a strong effect on the potentiometric sensitivity towards Ca2+. The level of precision achieved by the PLS models indicates that semi-quantitative predictions are feasible. To improve the computational models, larger sets of data with a wider range of zeolite-modified sensors are necessary. The constituent materials of such sensors should have a set of well-defined properties, which can be controlled and tuned for a particular application. It is anticipated that synthetic rather than natural zeolites would satisfy such requirements.