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Related Concept Videos

Gas Chromatography: Types of Detectors-II01:19

Gas Chromatography: Types of Detectors-II

In gas chromatography, different detectors are employed to meet specific analytical needs. These detectors are often categorized based on their detection mechanisms and the types of compounds they are best suited to analyze. Thermal Conductivity Detectors (TCD), Flame Ionization Detectors (FID), and Electron Capture Detectors (ECD) represent common categories, each with unique operating principles and applications. However, beyond these, several other detectors are designed for more specialized...
Gas Chromatography: Types of Detectors-I01:21

Gas Chromatography: Types of Detectors-I

There are different types of detectors used in gas chromatography, each with its own specific properties that make it suitable for detecting certain types of analytes. The most commonly used detectors in GC are thermal conductivity detector (TCD), flame ionization detector (FID), and electron capture detector (ECD).
TCD is the earliest and most widely used detector that operates by measuring the changes in the thermal conductivity of the carrier gas. When a sample compound enters the detector,...
Gas Chromatography: Overview of Detectors01:13

Gas Chromatography: Overview of Detectors

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

Gas Chromatography–Mass Spectrometry (GC–MS)

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. The coating...
High-Performance Liquid Chromatography: Types of Detectors01:15

High-Performance Liquid Chromatography: Types of Detectors

The role of the detectors in High-Performance Liquid Chromatography (HPLC) is to analyze the solutes as they exit from the chromatographic column. The detector recognizes the solute's property and generates corresponding electrical signals, which are converted into a readable graph of the detector's response versus elution time called a chromatogram at the computer. There are several types of HPLC detectors, each with its own advantages and limitations, depending on the analyte properties and...
Gas Chromatography: Introduction01:13

Gas Chromatography: Introduction

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 column.

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Related Experiment Video

Updated: May 17, 2026

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing
10:42

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing

Published on: March 22, 2019

Multigas Selective Identification Based on a Single Chemiresistive Gas Sensor via Dynamic Light-Pulse Modulation and

Jinyong Hu1,2, Enduo Hu1,2, Xinyao Liu1,2

  • 1School of Physics and Optoelectronics, Xiangtan University, Xiangtan 411105, PR China.

ACS Sensors
|May 15, 2026
PubMed
Summary
This summary is machine-generated.

A novel dynamic light-pulse modulation strategy enhances single metal oxide semiconductor (MOS) gas sensors. This method improves the selective identification of structurally similar volatile organic compounds (VOCs) using machine learning.

Keywords:
dynamic light modulationgas sensormachine learningselective identificationvolatile organic compounds (VOCs)

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Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy
09:57

Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy

Published on: July 25, 2022

Area of Science:

  • Materials Science
  • Chemical Sensing
  • Nanotechnology

Background:

  • Metal oxide semiconductor (MOS) gas sensors are cost-effective for gas detection but lack selectivity for similar molecules.
  • Current solutions like sensor arrays increase complexity and cost.
  • Distinguishing structurally analogous volatile organic compounds (VOCs) remains a challenge.

Purpose of the Study:

  • To develop a dynamic light-pulse modulation strategy to enhance gas-sensing selectivity using a single MOS sensor.
  • To achieve selective identification of structurally similar VOCs by expanding signal dimensionality.
  • To overcome the cross-sensitivity limitations of conventional MOS gas sensors.

Main Methods:

  • Fabrication of an Ag-modified ZnO nanocomposite gas sensor.
  • Application of dynamic light-pulse modulation to extract multidimensional features from transient resistance signals.
  • Integration of dynamic and steady-state parameters into a feature set.
  • Utilizing a support vector machine classifier for VOC identification.

Main Results:

  • The Ag-modified ZnO sensor showed analogous responses to formic acid, ethanol, and acetic acid.
  • Multidimensional feature extraction via light-pulse modulation enabled differentiation.
  • High identification accuracy (97.8%) was achieved for structurally similar VOCs across a wide concentration range.
  • The strategy successfully overcame cross-sensitivity issues.

Conclusions:

  • Dynamic light-pulse modulation combined with machine learning offers a pathway to enhance single MOS sensor selectivity.
  • This approach enables the development of compact and intelligent gas recognition systems.
  • The proposed strategy addresses limitations in distinguishing structurally similar VOCs.