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Sample-Sample Correlation Asynchronous Spectroscopic Method Coupled with Multivariate Curve Resolution-Alternating

Ran Guo1,2,3, Xin Zhang4, An-Qi He3

  • 1College of Chemistry and Environmental Engineering , Shenzhen University , Shenzhen 518060 , P.R. China.

Analytical Chemistry
|December 7, 2019
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Summary
This summary is machine-generated.

A new method called sample-sample correlation (SASS) analyzes complex spectroscopic data by creating secondary asynchronous spectra. This technique successfully resolves overlapping signals and extracts pure component spectra, even for challenging mixtures.

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Area of Science:

  • Spectroscopy
  • Chemometrics
  • Analytical Chemistry

Background:

  • Hyphenated spectroscopic techniques generate complex bilinear data.
  • Traditional methods struggle with severely overlapping temporal profiles and mixed spectral contributions.
  • Existing two-dimensional correlation spectroscopy (2D-COS) and nD asynchronous methods are insufficient for certain complex datasets.

Purpose of the Study:

  • To introduce a novel approach, sample-sample correlation (SASS), for analyzing challenging bilinear spectroscopic data.
  • To demonstrate SASS's capability in constructing secondary asynchronous spectra.
  • To overcome limitations of existing methods in resolving complex mixtures.

Main Methods:

  • Constructing a series of 2D sample-sample correlation spectra from bilinear data.
  • Extracting vertical slices from these 2D spectra to build a secondary 2D asynchronous spectrum.
  • Utilizing systematic absences of cross peaks (SACPs) to guide multivariate curve resolution-alternating least squares (MCR-ALS) for component spectra retrieval.

Main Results:

  • SASS successfully revealed distinct groups of SACPs, indicating component-specific spectral contributions.
  • Pure component spectra, including the challenging HOD spectrum from a H2O/HOD/D2O mixture, were accurately recovered using MCR-ALS guided by SASS.
  • Demonstrated effectiveness on model systems and real-world thermogravimetry-Fourier transform infrared spectroscopy (TG-FT-IR) data of mixtures.

Conclusions:

  • SASS provides indispensable implicit information for solving complex bilinear spectroscopic data analysis problems.
  • The method is applicable to various hyphenated spectroscopic techniques, including TG-FT-IR, and potential applications in environmental monitoring and biomedical diagnosis.
  • SASS offers a robust solution for spectral deconvolution where traditional methods fail.