Reaction Analysis and Process Optimization with Online Infrared Data Based on Kinetic Modeling and Partial Least...

Area of Science:

• Chemical kinetics
• Spectroscopy
• Chemometrics

Background:

• In-situ FT-IR spectroscopy enables online reaction monitoring.
• Analyzing real-time IR data for reactant/intermediate identification is challenging.

Purpose of the Study:

• To develop a robust algorithm for quantitative analysis of reaction processes using FT-IR data.
• To overcome limitations in identifying and quantifying uncertain species in real-time.

Main Methods:

• Developed an algorithm integrating reaction kinetic modeling with partial least squares (PLS).
• Applied the method to Paal-Knorr and glyoxylic acid synthesis reactions for validation.

Main Results:

• Simultaneously calculated concentration profiles and kinetic parameters from spectral data.
• Achieved <2.5% lack of fit for Paal-Knorr reactions and <6% absolute error for glyoxylic acid synthesis.
• Demonstrated successful simulation and optimization of reaction conditions for maximizing product yields.

Conclusions:

• The proposed algorithm provides comprehensive and quantitative analysis of chemical reactions.
• This FT-IR based method simplifies data analysis and reduces the need for extensive sampling.
• The approach is effective for real-time process monitoring and optimization.