Kalman filtering of data from first- and second-order kinetics

Area of Science:

• Analytical Chemistry
• Chemical Kinetics
• Computational Chemistry

Background:

• Simultaneous determination of chemical species often involves complex kinetics.
• Accurate quantification requires robust data processing methods.
• First- and second-order kinetics present unique analytical challenges.

Purpose of the Study:

• To evaluate the Kalman filter algorithm for processing kinetic data in simultaneous species determination.
• To assess the algorithm's performance in quantifying chemical components.
• To investigate the impact of various parameters on the algorithm's accuracy and precision.

Main Methods:

• Application of the Kalman filter algorithm to simulated kinetic data.
• Analysis of reactions involving pseudo first-order and second-order kinetics.
• Resolution of cysteine-ascorbic acid and glutathione-ascorbic acid mixtures using the copper(II)-neocuproine system.

Main Results:

• The Kalman filter algorithm demonstrated effective performance in quantifying chemical components.
• The algorithm successfully resolved mixtures with differing kinetic orders.
• Parameter influence on quantification accuracy and precision was estimated.

Conclusions:

• The Kalman filter is a suitable tool for processing kinetic data in simultaneous determinations.
• The algorithm offers reliable quantification and resolution of complex chemical mixtures.
• The study discusses key features like concentration ratios, accuracy, and precision.