Abstract
An automated real-time method for determination of ISE steady state value and response time is developed, following most recent IUPAC recommendations. Specifically, detection of the ‘steady state’ is related to (1) the time derivative of the emf as it reaches a limiting value (Δ E/Δ t limit, e.g., 0.1–1.0 mV min −1) and (2) the duration of time for which the absolute value of the time derivative remains less than this limiting value (stability window, denoted win st). A suite of representative ISEs, including glass, solid state, and polymer-based electrodes, is examined to determine sensitivity of results to parameterization choice. Measurements taken over a wide range of concentration values and in un-processed samples (i.e., without use of ionic strength adjustment) provide insight into behavior of ISEs in applications where analyte concentrations span a wide range and/or sample pre-processing may not be an option, e.g., use of sensors for in situ environmental sampling. Results show that declared steady state emf is strongly sensitive to variations in Δ E/Δ t limit but relatively unaffected by changes in the stability window when win st ≥30 s. Linearity of calibration curves produced, quantified by root mean squared error (RMSE) against a linear fit, improves as Δ E/Δ t limit decreases, however the percentage of measurements which reach a declared steady state within the prescribed sample window (∼6.5 min) falls with corresponding decreases in the Δ E/Δ t limit parameter. Response time, defined as the time required to reach declared steady emf, is also a strong function of parameterization. Dependence of response times on sample composition and/or ISE membrane composition and type are also discussed; results for ISEs in samples comprised exclusively of interfering ions are included. In general, limiting emf derivatives of {0.25–0.4 mV min −1} and stability windows of {30–40 s} achieve both good analytical accuracy and compliance with potentially short sampling window requirements. Methodology based on use of these parameters can improve sampling speed and accuracy as well as promote inter-comparison of data and ISE characterizations among research teams.
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