Comparison of Classical and Inverse Calibration Equations in Chemical Analysis.

Area of Science:

• Analytical Chemistry
• Instrumental Analysis

Background:

• Calibration curves are fundamental in chemical analysis, relating instrument response to analyte concentration.
• Classical and inverse calibration equations exist, differing in independent and dependent variables.
• Classical equations require complex transformations for new measurements, while inverse equations allow direct computation.

Purpose of the Study:

• To evaluate the predictive performance of classical versus inverse calibration equations.
• To assess the suitability of inverse equations for complex calibration scenarios.
• To explore the potential of inverse equations for enhancing intelligent instruments.

Main Methods:

• Utilized measurement data from two humidity sensor types.
• Incorporated nine additional data sets from existing literature.
• Employed four proposed criteria to evaluate predictive performance.
• Applied regression analysis to establish calibration equations.

Main Results:

• The inverse calibration equation demonstrated effective predictive performance, especially for complex calibrations.
• Direct computation of measurements is feasible with inverse equations.
• Instrument response precision is critical for reliable predictive performance.

Conclusions:

• Inverse calibration equations are a valuable tool for chemical analysis, simplifying measurement calculations.
• The precision of instrument response directly impacts the accuracy of calibration.
• Embedding inverse equations into devices can lead to enhanced intelligent instruments.