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A simple self modelling curve resolution (SMCR) method for two-component systems.

Somaiyeh Khodadadi Karimvand1, Ali Pahlevan1, Jamile Mohammad Jafari1

  • 1Department of Chemistry, Institute for Advanced Studies in Basic Sciences, P.O. Box 45195-1159, Zanjan, Iran.

Analytica Chimica Acta
|March 19, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a new, simple method to calculate the boundaries of feasible solutions for two-component systems using multivariate self-modeling curve resolution (SMCR). This approach addresses rotational ambiguity, a key challenge in SMCR analysis.

Keywords:
Feasible solutionsMicro-structure of dataSelf-modeling curve resolution (SMCR)Spectroscopic measurementsTwo-component systems

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Area of Science:

  • Chemometrics
  • Analytical Chemistry

Background:

  • Multivariate self-modeling curve resolution (SMCR) methods are essential for analyzing chemical data without prior model knowledge.
  • Rotational ambiguity is a significant challenge in SMCR, leading to multiple feasible solutions.

Purpose of the Study:

  • To present a novel and simple SMCR method for determining the boundaries of feasible solutions in two-component systems.
  • To address the issue of rotational ambiguity in SMCR analysis.

Main Methods:

  • A new, straightforward strategy is developed for calculating feasible solutions in two-component systems.
  • The method is applied to analyze four diverse experimental two-component systems.

Main Results:

  • The proposed simple SMCR strategy effectively calculates the boundaries of feasible solutions for two-component systems.
  • The method was validated across various applications, including complex formation, tautomerization kinetics, lipidomics, and gray systems analysis.

Conclusions:

  • The developed simple SMCR method successfully determines the boundaries of feasible solutions for two-component systems.
  • This strategy provides a reliable approach to resolve rotational ambiguity in specific chemical data analyses.