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Mass Spectrometry: Complex Analysis

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Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
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Chromatographic Methods: Classification

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Chromatography is an analytical technique widely used in fields such as chemistry, biology, environmental science, and pharmaceuticals to separate the components of a mixture and identify substances between them. The process of chromatography is based on the interactions between two distinct phases: the stationary phase and the mobile phase. The stationary phase is fixed in place by a supporting material, while the mobile phase moves over it, carrying the solutes. As the mobile phase travels,...

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Updated: Jun 1, 2026

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography

Published on: September 2, 2020

Chemometrics in comprehensive multidimensional separations.

Zhong-Da Zeng¹, Helmut M Hugel, Philip J Marriott

¹Centre for Green Chemistry, School of Chemistry, Monash University, Wellington Rd, Clayton 3800, Australia.

Analytical and Bioanalytical Chemistry

|June 11, 2011

Summary

This summary is machine-generated.

Chemometrics enhances the analysis of complex, high-dimensional data from comprehensive multidimensional separations (CMDS). This review highlights how chemometric methods unlock hidden information and improve the interpretation of chemical processes and experiments.

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Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)

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Published on: May 20, 2013

Area of Science:

Analytical Chemistry
Data Science

Background:

Chemometrics is crucial for extracting knowledge from high-dimensional datasets.
Comprehensive multidimensional separations (CMDS) generate complex data requiring advanced analytical methods.

Purpose of the Study:

To review new developments in chemometrics for maximizing CMDS data potential.
To provide insights into resolving practical problems using chemometric approaches in CMDS.

Main Methods:

Review of recent advancements in chemometric techniques.
Application of chemometrics to experimental parameter optimization and data quality improvement.
Utilizing pattern recognition, multivariate modeling, orthogonality evaluation, and image processing for CMDS data.

Main Results:

Chemometrics successfully applied to identify and quantify chemical components.
Multivariate models established to correlate chromatographic properties and molecular descriptors.
Demonstrated effectiveness in clustering, classification, and data interpretation.

Conclusions:

Chemometrics offers powerful tools for CMDS data analysis and interpretation.
New chemometric developments significantly enhance the resolution of complex chemical problems.
This review provides a valuable overview for researchers utilizing CMDS and chemometrics.