Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Gas Chromatography: Overview of Detectors01:13

Gas Chromatography: Overview of Detectors

1.8K
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...
1.8K
Gas Chromatography: Types of Detectors-II01:19

Gas Chromatography: Types of Detectors-II

1.1K
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...
1.1K
Gas Chromatography: Types of Detectors-I01:21

Gas Chromatography: Types of Detectors-I

1.4K
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,...
1.4K
Gas Chromatography–Mass Spectrometry (GC–MS)01:14

Gas Chromatography–Mass Spectrometry (GC–MS)

6.5K
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....
6.5K
Gas Chromatography: Sample Injection Systems01:08

Gas Chromatography: Sample Injection Systems

1.3K
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...
1.3K
Gas Chromatography: Introduction01:13

Gas Chromatography: Introduction

3.6K
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...
3.6K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A rare giant asymptomatic biatrial myxoma.

Journal of cardiothoracic surgery·2026
Same author

Stable Lithium Metal Batteries in Ester Electrolytes Enabled by High-Entropy Alloy-Modified Graphitized Carbon Paper Anodes.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

Plasma-derived small extracellular vesicle miR-660-5p as a predictor for carotid plaque vulnerability and postoperative major adverse cardiovascular event risk.

Atherosclerosis plus·2026
Same author

NoctuaXR: Enhancing Video See-Through Perception for XR in Low-Light Environments with Real-Time Ambient-Aware Adaptation.

IEEE transactions on visualization and computer graphics·2026
Same author

Associations of Folate and Homocysteine Levels with Futile Recanalization in Acute Ischemic Stroke After Successful Endovascular Thrombectomy.

Neurology and therapy·2025
Same author

Associations of the volume and proportion of vigorous-intensity physical activity with all-cause, cardiovascular, and cancer mortality: a systematic review and meta-analysis.

PeerJ·2025

相关实验视频

Updated: Jan 15, 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

6.6K

可重新配置的多通道气体传感器阵列用于复杂气体混合物识别和鱼类新鲜度分类.

He Wang1,2, Dechao Wang1,2, Hang Zhu1,2

  • 1National Key Laboratory of Automotive Chassis Integration and Bionics, School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130022, China.

Sensors (Basel, Switzerland)
|October 16, 2025
PubMed
概括

研究人员开发了一种可重新配置的传感器阵列,以识别复杂的气体混合物,如鱼类腐烂生物标志物. 该系统利用金属氧化物传感器的交叉灵敏度,通过机器学习实现96%的准确性,用于实际评估食品的新鲜度.

关键词:
鱼的新鲜度 鱼的新鲜度气体传感器是一个气体传感器.混合气体混合气体是一种混合气体.传感器阵列是一系列的传感器阵列.

更多相关视频

Identification of Olfactory Volatiles using Gas Chromatography-Multi-unit Recordings GCMR in the Insect Antennal Lobe
09:49

Identification of Olfactory Volatiles using Gas Chromatography-Multi-unit Recordings GCMR in the Insect Antennal Lobe

Published on: February 24, 2013

14.7K
Microalgae Cultivation and Biomass Quantification in a Bench-Scale Photobioreactor with Corrosive Flue Gases
08:41

Microalgae Cultivation and Biomass Quantification in a Bench-Scale Photobioreactor with Corrosive Flue Gases

Published on: December 19, 2019

10.8K

相关实验视频

Last Updated: Jan 15, 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

6.6K
Identification of Olfactory Volatiles using Gas Chromatography-Multi-unit Recordings GCMR in the Insect Antennal Lobe
09:49

Identification of Olfactory Volatiles using Gas Chromatography-Multi-unit Recordings GCMR in the Insect Antennal Lobe

Published on: February 24, 2013

14.7K
Microalgae Cultivation and Biomass Quantification in a Bench-Scale Photobioreactor with Corrosive Flue Gases
08:41

Microalgae Cultivation and Biomass Quantification in a Bench-Scale Photobioreactor with Corrosive Flue Gases

Published on: December 19, 2019

10.8K

科学领域:

  • 化学传感器 化学传感器
  • 机器学习应用 机器学习应用
  • 食品安全技术 食品安全技术

背景情况:

  • 金属氧化物半导体气体传感器具有低成本和快速响应等优势.
  • 由于交叉敏感性,复杂气体混合物的有限选择性是一个重大挑战.
  • 现有的传感器系统在各种气体环境中难以准确识别.

研究的目的:

  • 开发可重新配置的传感器阵列系统,用于增强气体混合物分析.
  • 调查金属氧化物传感器中交叉灵敏度的使用,以提高选择性.
  • 创建一个实用的平台来识别特定的气体生物标志物,例如那些表明鱼类腐烂的生物标志物.

主要方法:

  • 设计了一个可重新配置的化学复制传感器阵列,支持最多12个传感器,具有高级控制功能.
  • 应用机器学习分类器包括随机森林 (RF),卷积神经网络 (CNN) 和主组件分析 (PCA) 预处理后的支持矢量机器 (SVM).
  • 通过相关性分析和特征重要性评估优化传感器通道,以减少系统复杂性.

主要成果:

  • 随机森林 (RF) 模型最初实现了鱼类破坏生物标志物的94%的分类准确性.
  • 将传感器阵列从12个传感器优化到8个传感器,提高了准确度到96%,同时简化了系统.
  • 这项研究表明,利用传感器交叉灵敏度产生了信息丰富的气味指纹.

结论:

  • 一个可重新配置的传感器阵列系统有效地解决了复杂气体混合物的选择性限制.
  • 蓄意使用交叉灵敏度,结合机器学习,为气体传感提供了一个强大的方法.
  • 该平台为复杂的气体识别和实时食品新鲜度评估提供了实用的解决方案.