Jove
Visualize
Contact Us
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 Concept Videos

High-Performance Liquid Chromatography: Introduction01:11

High-Performance Liquid Chromatography: Introduction

3.4K
High-performance liquid chromatography(HPLC), formerly referred to as High-pressure liquid chromatography, is a powerful technique used to separate, identify, and quantify components in complex mixtures. The term "high pressure" refers to using high pressure to push the liquid mobile phase through the tightly packed columns.
In HPLC, two phases play a critical role in the separation process:
3.4K
High-Performance Liquid Chromatography: Instrumentation00:57

High-Performance Liquid Chromatography: Instrumentation

2.9K
High-performance liquid chromatography, or HPLC, is an analytical technique that separates liquid samples under high pressures. An HPLC instrument consists of glass bottles for storing solvents called mobile phase reservoirs. HPLC-grade solvents are used to maintain high purity, and the dissolved gases are removed using a degasser, such as a vacuum pumping system or sparging with helium. The solvents are then pumped into the analytical column using a screw-driven syringe or reciprocating pumps.
2.9K
Dimensional Analysis03:40

Dimensional Analysis

60.5K
Dimensional analysis, also known as the factor label method, is a versatile approach for mathematical operations. The main principle behind this approach is: the units of quantities must be subjected to the same mathematical operations as their associated numbers. This method can be applied to computations ranging from simple unit conversions to more complex and multi-step calculations involving several different quantities and their units.
Conversion Factors and Dimensional Analysis
The unit...
60.5K
Dimensional Analysis01:27

Dimensional Analysis

653
Dimensional analysis is a valuable technique in fluid mechanics for simplifying complex problems by reducing them into dimensionless groups. These groups capture the essential relationships between the variables involved, allowing researchers and engineers to analyze fluid flow without dealing with each variable individually. This approach reduces the number of independent variables, allowing for easier analysis and better understanding of physical phenomena.
In fluid mechanics, dimensional...
653
Dimensional Analysis01:23

Dimensional Analysis

2.1K
Dimensional analysis is a powerful tool that is used in physics and engineering to understand and predict the behavior of physical systems. The basic idea behind dimensional analysis is to express physical quantities in terms of fundamental dimensions such as the mass, length, and time. Derived dimensions like the velocity, acceleration, and force are derived from the combinations of these fundamental dimensions.
Dimensional analysis allows us to analyze and compare physical quantities on a...
2.1K
Dimensional Analysis02:19

Dimensional Analysis

23.6K
The concept of dimension is important because every mathematical equation linking physical quantities must be dimensionally consistent, implying that mathematical equations must meet the following two rules. The first rule is that, in an equation, the expressions on each side of the equal sign must have the same dimensions. This is fairly intuitive since we can only add or subtract quantities of the same type (dimension). The second rule states that, in an equation, the arguments of any of the...
23.6K

You might also read

Related Articles

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

Sort by
Same author

pH-responsive imine-chitosan-based intelligent controlled-release packaging films with transformable antimicrobial modes from defense to attack.

Food chemistry: X·2025
Same author

Consumer perception of milk with different fat content: Integrating check-all-that-apply, quantitative descriptive analysis, rate-all-that-apply, and facial emotion analysis.

Journal of dairy science·2025
Same author

Umami-enhancing peptides from Acetes chinensis: Insights into taste mechanism through multiligand docking with T1R1/T1R3.

Food chemistry·2025
Same author

Decoding bitter peptides in soy sauce: From identification to mechanism in bitter taste formation.

Food chemistry·2025
Same author

Exploration of key aroma compounds contributing to sweet aroma differences between base and commercial Fenjiu: an approach integrating Napping-UFP with molecular sensoromics.

Food chemistry: X·2025
Same author

Machine learning-assisted identification of core flavor compounds and prediction of core microorganisms in fermentation grains and pit mud during the fermentation process of strong-flavor Baijiu.

Food chemistry·2025
Same journal

Stereo-sensitive modelling of gas chromatographic retention indices of mono-cycloalkanes in jet fuel range.

Journal of chromatography. A·2026
Same journal

Approaches to using retention indices with coupled column pressure tuning in gas chromatography.

Journal of chromatography. A·2026
Same journal

MOF-supported surface-imprinted polymer for hazard governance of aristolochic acids in herbal matrices: A safety-control strategy supported by multiscale simulations.

Journal of chromatography. A·2026
Same journal

Portable cold-assisted head-space solid-phase microextraction coupled with GC-MS/MS for sensitive determination of trace polychlorinated naphthalenes in water.

Journal of chromatography. A·2026
Same journal

Characterization of phosphorous impurities originating from the synthesis of Sarin.

Journal of chromatography. A·2026
Same journal

Extraction and chromatographic purification of purpurin: A scalable approach using modified dry column vacuum chromatography.

Journal of chromatography. A·2026
See all related articles

Related Experiment Video

Updated: Jan 23, 2026

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography
10:14

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

Published on: September 2, 2020

5.4K

An improved peak clustering algorithm for comprehensive two-dimensional liquid chromatography data analysis.

Jucai Xu1, Lin Zheng1, Guowan Su1

  • 1School of Food Science and Engineering, South China University of Technology, Guangzhou 510640, China; Guangdong Food Green Processing and Nutrition Regulation Technologies Research Center, Guangzhou 510640, China.

Journal of Chromatography. A
|June 12, 2019
PubMed
Summary
This summary is machine-generated.

An improved algorithm enhances two-dimensional (2D) peak detection in complex liquid chromatography (LC×LC) data. This method boosts accuracy for LC×LC quantitative analysis, even with challenging gradient conditions.

Keywords:
Data analysisOverlap criterionPeak detectionRetention time criterionTwo-dimensional liquid chromatography

More Related Videos

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.9K
Immunoglobulin G N-Glycan Analysis by Ultra-Performance Liquid Chromatography
11:01

Immunoglobulin G N-Glycan Analysis by Ultra-Performance Liquid Chromatography

Published on: January 18, 2020

9.0K

Related Experiment Videos

Last Updated: Jan 23, 2026

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography
10:14

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

Published on: September 2, 2020

5.4K
ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.9K
Immunoglobulin G N-Glycan Analysis by Ultra-Performance Liquid Chromatography
11:01

Immunoglobulin G N-Glycan Analysis by Ultra-Performance Liquid Chromatography

Published on: January 18, 2020

9.0K

Area of Science:

  • Analytical Chemistry
  • Chromatography

Background:

  • Complex samples require advanced analytical techniques.
  • Two-dimensional liquid chromatography (LC×LC) offers enhanced separation power.
  • Accurate peak detection is crucial for quantitative LC×LC analysis.

Purpose of the Study:

  • To develop an improved algorithm for 2D peak detection in LC×LC data.
  • To enhance the accuracy and reliability of LC×LC quantitative analysis.
  • To address challenges in peak detection caused by shifting gradients and low sampling rates.

Main Methods:

  • A two-step algorithm combining 1D peak detection with merging criteria (retention time, overlap, unimodality).
  • Implementation of variable thresholds for improved 2D retention time difference examination.
  • Application of a bidirectional overlap criterion for enhanced detection of tailing peaks.

Main Results:

  • The algorithm demonstrated improved performance in detecting peaks in complex LC×LC datasets.
  • Achieved over 60% accuracy, even with low 1D sampling frequency or shifting 2D gradients.
  • Quantitative evaluation via comparison with mass analysis confirmed the algorithm's effectiveness.

Conclusions:

  • The developed algorithm significantly improves 2D peak detection in LC×LC.
  • It offers a robust solution for quantitative LC×LC analysis under various challenging conditions.
  • This advancement aids in better performance assessment of LC×LC systems.