Using chemical modeling for Designing of Optimal pH Sensor Based on Analytical Sensitivity Enhancement

Abstract The behavior of chemical systems can be predicted based on the chemical model or the law of mass action in combining with Beer’s Law. The information about chemical behavior of different species in an equilibrium condition and pure responses of active species propound the idea of using this information for designing of sensors, systematically. In this contribution, we applied chemical modeling for designing pH sensors using common pH indicators. Because individually considered they display a limited dynamic range, two or more pH indicators are usually required for the pH measurements in a broad pH range. Two different aspects were considered: 1) finding the optimum approach for the combination of pH indicators (i.e. an array or a mixture of indicators in solution), in this regard, analytical sensitivity is used as an optimization criterion and 2) tuning equilibrium constants of indicators to produce new desired pH indicators. The tuning of apparent constants was performed using a surfactant solution. An array of a certain indicator in the aqueous and micellar phase increases its dynamic pH range. Three pH indicators including phenol red, neutral red, and methyl orange were selected and their interactions with the micellar phase of Brij-35 were investigated. Based on the obtained information about the behavior of the indicators in micellar solution, the optimum pH sensor was then designed and pH was predicted with the root mean square error of pH prediction value of 0.1.