Loading...

Development and Application of Independent Component Analysis Method for Evaluation of Complex Chromatographic Data

Zarghani, Maryam | 2017

625 Viewed
  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 50532 (03)
  4. University: Sharif University of Technology
  5. Department: Chemistry
  6. Advisor(s): Parastar Shahri, Hadi
  7. Abstract:
  8. In recent years, chromatographic technique as one of the most important analytical techniques have been developed for the analysis of complex samples. Hyphenated chromatographic techniques such as liquid or gas chromatography combine separation and spectroscopic detection technique to exploit the advantages of both and they have attracted attention of chemists to analyze complex mixtures. However, inadequate separation challenges still exist especially in the analysis of complex samples. Therefore, two-dimensional chromatographic systems such as comprehensive two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) have been proposed for the analysis of complex samples due to their higher resolution and higher peak capacity. However, one of the main challenges in GC×GC is related to the difficulty of the analysis and interpretation of the huge amount of data. Additionally, complete separation of all detectable components still cannot be achieved. Therefore, the objective of the present work was development of joint approximate diagonalization of eigenmatrices (JADE) as a member of independent component analysis (ICA) family, for the analysis of HPLC-DAD, GC-MS and GC×GC-MS data. In this regard, simulated HPLC-DAD, GC-MS and GC×GC-MS data sets with different number of components, different degree of overlap and noise levels were evaluated. Also, column-wise augmentation was used for these data arrangement before JADE analysis. The performance of JADE was evaluated in terms of statistical parameters of lack of fit (LOF), mutual information (MI) and Amari index as well as analytical figures of merit (AFOMs) obtained from calibration curves. In addition, the area of feasible solutions (AFS) was calculated by two different approaches of MCR-BANDs and polygon inflation algorithm (FAC-PACK). Furthermore, JADE performance was compared with multivariate curve resolution-alternation least squares (MCR-ALS) and other ICA algorithms of mean-field ICA (MFICA) and mutual information least dependent component analysis (MILCA). In all cases, JADE could successfully resolve the elution and spectral profiles in GC-MS and GC×GC-MS data with acceptable statistical and calibration parameters and their solutions were in the AFS. To check the applicability of JADE in real cases, JADE was used for resolution and quantification of phenanthrene and anthracene in heavy fuel oil (HFO) analyzed by GC×GC-MS. Surprisingly, pure elution and spectral profiles of target compounds were properly resolved in the presence of baseline and interferences using JADE. Once more, the performance of JADE was compared with MCR-ALS. On this matter, the MI values were 1.01 and 1.13 for resolved profiles by JADE and MCR-ALS, respectively. In addition, LOD values (µg/mL) were respectively 1.36 and 1.24 for phenanthrene and 1.26 and 1.09 for anthracene using MCR-ALS and JADE which showed results of JADE can be compared with MCR-ALS
  9. Keywords:
  10. Independent Component Analysis (ICA) ; Comprehensive Two Dimensional Gas Chromatography ; Rotational Ambiguity ; Multivariate Curve Resolution-Alternative Least Square (MCR-ALS) ; Joint Approximate Diagonalization of Eigenmatrics ; Hyphenated Chromatography

 Digital Object List

 Bookmark

No TOC