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Optimization by means of responses surface of an analytical sequence using a sequential injection system
Alberto Pasamontes1, M A Pilar Callao
1Departament de Química Analítica i Química Orgànica, Universitat Rovira i Virgili, Marcel lí Domingo s/n, Campus Sescelades, 43007 Tarragona, Spain.
This study optimizes sequential injection analysis (SIA) conditions using experimental design for better data. The goal is to improve multivariate curve resolution with alternating least squares (MCR-ALS) analysis.
Area of Science:
- Analytical Chemistry
- Chemometrics
Background:
- Sequential Injection Analysis (SIA) is crucial for generating second-order data.
- Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS) requires well-designed analytical sequences for accurate data analysis.
Purpose of the Study:
- To determine optimal working conditions for SIA using experimental design.
- To enhance the quality of second-order data for MCR-ALS analysis.
Main Methods:
- Application of an experimental design methodology.
- Utilizing a desirability function to consolidate multiple response metrics.
- Employing a two-step optimization process: factor screening and response surface modeling.
Main Results:
- Successful determination of optimum SIA working conditions.
- Development of a systematic approach to design informative analytical sequences.
- Integration of desirability functions for efficient multi-response optimization.
Conclusions:
- The proposed experimental design method effectively optimizes SIA parameters for MCR-ALS.
- This approach ensures the generation of high-quality second-order data suitable for advanced chemometric treatment.
- The study provides a robust framework for optimizing analytical methods in complex chemical analyses.
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