Jove
Visualize
Contact Us

Related Concept Videos

Gas Chromatography–Mass Spectrometry (GC–MS)01:14

Gas Chromatography–Mass Spectrometry (GC–MS)

4.0K
Gas chromatography–mass spectrometry (GC–MS) is the combination of analytical techniques of gas chromatography and mass spectrometry in a single instrument for analyzing a mixture of compounds. The gas chromatograph separates the compounds in the mixture, and the mass spectrometer analyzes each compound separately to determine the molecular masses and molecular structures.
A gas chromatograph consists of a long, narrow capillary column with a polysiloxane coating on the inner wall....
4.0K
Gas Chromatography: Introduction01:13

Gas Chromatography: Introduction

1.5K
Gas chromatography (GC) is a technique for separating and analyzing volatile compounds in a sample. Its primary purpose is to identify and quantify components in complex mixtures, making it essential in fields such as environmental analysis, pharmaceuticals, and petrochemicals. GC is also called vapor-phase chromatography (VPC) or gas-liquid partition chromatography (GLPC).
In GC,  a sample is vaporized and mixed with an inert carrier gas (the mobile phase), which transports it through a...
1.5K
Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

723
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.
GC–MS is a powerful hyphenated method commonly used in forensics and environmental...
723
Gas Chromatography: Sample Injection Systems01:08

Gas Chromatography: Sample Injection Systems

371
In gas chromatography, the sample is introduced as a vapor plug into the carrier gas stream for high efficiency and resolution. A microsyringe injects the sample solution into a heated sample port, vaporizing it and mixing it with the carrier gas. This process is important to ensure the sample is properly prepared for analysis. Thermally sensitive samples can be injected directly into the column and volatilized by slowly increasing the column temperature.
Two primary injection methods are used...
371
Volatilization01:10

Volatilization

368
Volatilization gravimetry is an analytical technique that measures the mass lost due to the volatilization of the substance. This technique is used to estimate the amount of volatile material in a sample. To perform this method, heat a known amount of the sample to a high temperature in a crucible or other suitable vessel. The volatile substance in the sample evaporates, and the vapor is completely expelled from the crucible either by heating the sample or bubbling a stream of inert gas through...
368
Gas Chromatography: Overview of Detectors01:13

Gas Chromatography: Overview of Detectors

439
Detectors in gas chromatography (GC) help identify and quantify the components of a mixture by translating chemical properties into measurable signals, which are displayed on a chromatogram. Detectors can be categorized into two main types: destructive and non-destructive.
A non-destructive detector allows a sample to be analyzed without altering or consuming it, meaning the sample can be collected after detection for further analysis. Examples include thermal conductivity detectors and...
439

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Separation of Ammonia Isotopologues by Benchtop Drift Tube Ion Mobility Spectrometry and Chemometric Modeling.

Journal of the American Society for Mass Spectrometry·2026
Same author

Towards "greener" strategies in quality control: rapid volatilomics of cocoa based on HS-GC-IMS and machine learning.

Analytical and bioanalytical chemistry·2026
Same author

Fingerprinting of Peach During the Ripening Process Using an Analytical Platform with Spectrometric and Volatilome-Based Chromatographic Techniques.

Journal of agricultural and food chemistry·2025
Same author

Shaping the Future of Coffee: Climate Resilience, Liberica's Rise, and By-Product Innovation-Highlights from the International Coffee Convention 2023 (ICC2023).

Foods (Basel, Switzerland)·2024
Same author

Nontargeted Volatile Metabolite Screening and Microbial Contamination Detection in Fermentation Processes by Headspace GC-IMS.

Analytical chemistry·2024
Same author

Quantitative Mass Spectrometry Imaging Using Multivariate Curve Resolution and Deep Learning: A Case Study.

Journal of the American Society for Mass Spectrometry·2023
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jun 6, 2025

Preparation of Drosophila Larval Samples for Gas Chromatography-Mass Spectrometry GC-MS-based Metabolomics
07:21

Preparation of Drosophila Larval Samples for Gas Chromatography-Mass Spectrometry GC-MS-based Metabolomics

Published on: June 6, 2018

11.1K

How Machine Learning and Gas Chromatography-Ion Mobility Spectrometry Form an Optimal Team for Benchtop Volatilomics.

Hadi Parastar1, Philipp Weller2

  • 1Department of Chemistry, Sharif University of Technology, P.O. Box 11155-9516, Tehran, Iran.

Analytical Chemistry
|November 29, 2024
PubMed
Summary

Gas chromatography-ion mobility spectrometry (GC-IMS) offers a promising point-of-need solution for volatilomics. Machine learning techniques enhance GC-IMS analysis, improving qualitative and quantitative results for researchers using open-source tools.

More Related Videos

Profiling Volatile Compounds in Blackcurrant Fruit using Headspace Solid-Phase Microextraction Coupled to Gas Chromatography-Mass Spectrometry
05:29

Profiling Volatile Compounds in Blackcurrant Fruit using Headspace Solid-Phase Microextraction Coupled to Gas Chromatography-Mass Spectrometry

Published on: June 9, 2021

3.7K
Gas Chromatography-Mass Spectrometry Paired with Total Vaporization Solid-Phase Microextraction as a Forensic Tool
05:31

Gas Chromatography-Mass Spectrometry Paired with Total Vaporization Solid-Phase Microextraction as a Forensic Tool

Published on: May 25, 2021

7.0K

Related Experiment Videos

Last Updated: Jun 6, 2025

Preparation of Drosophila Larval Samples for Gas Chromatography-Mass Spectrometry GC-MS-based Metabolomics
07:21

Preparation of Drosophila Larval Samples for Gas Chromatography-Mass Spectrometry GC-MS-based Metabolomics

Published on: June 6, 2018

11.1K
Profiling Volatile Compounds in Blackcurrant Fruit using Headspace Solid-Phase Microextraction Coupled to Gas Chromatography-Mass Spectrometry
05:29

Profiling Volatile Compounds in Blackcurrant Fruit using Headspace Solid-Phase Microextraction Coupled to Gas Chromatography-Mass Spectrometry

Published on: June 9, 2021

3.7K
Gas Chromatography-Mass Spectrometry Paired with Total Vaporization Solid-Phase Microextraction as a Forensic Tool
05:31

Gas Chromatography-Mass Spectrometry Paired with Total Vaporization Solid-Phase Microextraction as a Forensic Tool

Published on: May 25, 2021

7.0K

Area of Science:

  • Analytical Chemistry
  • Chemometrics
  • Computational Chemistry

Background:

  • Volatilomics research demands rapid, on-site analytical capabilities.
  • Traditional methods for volatilomics can be time-consuming and require specialized laboratory settings.
  • Gas chromatography-ion mobility spectrometry (GC-IMS) is emerging as a powerful technique for volatile compound analysis.

Purpose of the Study:

  • To explore the potential of GC-IMS as a point-of-need analytical tool for volatilomics.
  • To discuss the application and versatility of machine learning (ML) techniques in GC-IMS data analysis.
  • To provide practical workflows and insights for improving qualitative and quantitative GC-IMS results.

Main Methods:

  • Utilizing gas chromatography-ion mobility spectrometry (GC-IMS) for sample analysis.
  • Applying modern machine learning (ML) and chemometric methods for data processing and interpretation.
  • Demonstrating workflows using open-source software packages for accessibility.

Main Results:

  • GC-IMS demonstrates significant potential as a point-of-need volatilomics platform.
  • ML techniques effectively address challenges in GC-IMS analysis, enhancing data reliability.
  • Open-source workflows facilitate reproducible and accessible research in GC-IMS.

Conclusions:

  • GC-IMS, coupled with ML, provides a versatile and powerful approach for modern volatilomics.
  • The integration of open-source tools democratizes advanced analytical capabilities for researchers.
  • Further development in GC-IMS and ML integration will lead to more robust qualitative and quantitative analytical outcomes.