A new strategy for calibrating indicator displacement assay (IDA)-based sensor systems.

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Sensor Technology

Background:

• Indicator Displacement Assays (IDA) are widely used for sensing applications.
• Traditional calibration methods for IDA sensors often rely on instrumental responses and can be affected by matrix effects.
• Accurate calibration is crucial for reliable sensor performance.

Purpose of the Study:

• To introduce a novel calibration strategy for IDA-based sensors.
• To replace instrumental measurement responses with equilibrium concentrations of spectroscopically active species.
• To reduce matrix effects and simplify calibration models.

Main Methods:

• Utilizing the Classical Least Squares (CLS) method to determine equilibrium concentrations of active species.
• Coupling Indirect Hard Modelling (IHM) with CLS to mitigate matrix effects.
• Exploiting fundamental variables (equilibrium concentrations) from spectral data.

Main Results:

• The proposed method reduces the number of input variables required for calibration.
• Coupling IHM and CLS effectively minimizes matrix effects on the calibration model.
• The strategy was successfully validated using both simulated and real sensor array data.

Conclusions:

• The novel strategy offers a more robust and simplified approach to calibrating IDA-based sensors.
• Replacing instrumental responses with fundamental variables improves accuracy and reduces reliance on variable selection.
• This method enhances the reliability of IDA sensors in complex sample matrices.