Research Interests

 

Chemometrics in Chromatography (ChroMATHography) 

 

Chemometric methods have critical importance for the discovery of the information/knowledge buried or concealed in high-dimensional datasets acquired from hyphenated and multi-dimensional chromatography and for interpretation of separation processes. 

The terms "Mathematical Chromatography" and "ChroMATHography" have been suggested to describe the combination of chromatography and chemometrics.

  •  Regarding the importance of separation science in general and especially chromatography in the analysis of complex samples and the role of chemometrics in the analysis of different types of chromatographic data involving hyphenated (e.g. GC-MS, HPLC-DAD) and multi-dimensional (e.g. GC×GC-FID, GC×GC-TOFMS), we are working on development and application of different chemometrics methods such as multivariate curve resolution (MCR), multivariate optimization (experimental design) and recently unsuppervised pattern recognition for the analysis of chromatographic data.


●- Different applications of second- and third-order multivariate calibration methods such as MCR-ALS, PARAFAC and
     PARAFAC2 are under way in our research group for fast HPLC-DAD analysis, GC-MS and HPLC-DAD chromatographic
     fingerprinting and GC×GC data analysis. 


●- Development of new algorithms for separation data and user-friendly software for non-expert users (e.g. MCRC Software, MVC app and RMet) compose another part of our researches.   

Graphical abstract: Mutual information concept for evaluation of separation quality in hyphenated chromatographic measurements
  • Development of different chemometric methods for food authenticity and adulteration detection including discrimination and class modeling


Summary of Our Researches

1- Fundamentals
- Multivariate Curve Resolution (MCR)
- Multi-way and Multi-set analysis of high dimensional data
- Multivariate Optimization (Response Surface Methodology, RSM)
- Multivariate Clustering (Unsupervised Classification)

2- Applications
- Data Analysis of Hyphenated Chromatographic Measurements (GC-MS, HPLC-DAD)
- Data Analysis of Multi-dimensional Chromatographic Measurements (GC×GC-FID, GC×GC-TOFMS)
- Handling Common Chromatographic Issues (Baseline/Background Contribution, Noise, Non-Gaussian
   Peaks, Retention Time Shifts, Co-elution (overlapped and embedded peaks))
- Chromatographic Fingerprinting of Natural Products (Medicinal Plants)
- Fast Chromatographic Measurements using HPLC
- Plant and human Metabolomics

- Food authenticity and adulteration detection