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

Optimizing Chromatographic Separations01:15

Optimizing Chromatographic Separations

732
Optimizing chromatographic separations is crucial for obtaining clean separations in a minimum amount of time. Optimization is required for several factors, including kinetic effects related to band broadening, plate height, capacity factor, and separation factor.
Band broadening refers to spreading solute bands as they travel through the column. This broadening can impact resolution. Plate height (H) represents the length required for one theoretical plate. A lower plate height corresponds to...
732
Ion-Exchange Chromatography01:09

Ion-Exchange Chromatography

1.5K
Ion-exchange chromatography, or IEC, is a technique for separating ions based on their affinity for the stationary phase. The stationary phase is a cross-linked polymer resin with covalently attached ionic functional groups. The functional groups can be either positively charged (cation exchangers) or negatively charged (anion exchangers). A cation exchanger consists of a polymeric anion and active cations, while an anion exchanger is a polymeric cation with active anions. The choice of...
1.5K
Principles Of Column Chromatography01:13

Principles Of Column Chromatography

8.3K
The chromatography technique was first invented in 1901 by Michael S. Tswett, a Russian botanist, to separate plant pigments using organic solvents. Further, in 1941, Archer John Porter Martin and R. L. M. Synge modified the technique by packing silica gel into a column. A mixture of amino acids was then separated on the packed column using chloroform and water mixture as the mobile phase. This was the first report on column chromatography. At present, column chromatography is a widely used...
8.3K
Chromatographic Methods: Classification01:12

Chromatographic Methods: Classification

3.4K
Chromatographic techniques are classified in three ways: the classification is based on the physical state of the stationary and mobile phases, how the mobile phase and the stationary phase contact each other, or through the chemical or physical processes that isolate the components of the sample. Typically, the mobile phase is either a liquid or gas, while the stationary phase is either a solid or a liquid layer applied to a solid surface.
Chromatographic techniques are typically named by...
3.4K
High-Performance Liquid Chromatography: Elution Process01:05

High-Performance Liquid Chromatography: Elution Process

1.2K
In High-Performance Liquid Chromatography (HPLC), the elution process is critical to the separation of analytes and the quality of chromatographic results. Elution describes how compounds move through the column and separate based on their interactions with the mobile and stationary phases. This process determines the resolution, peak shape, and retention times in the chromatogram, which are essential for identifying and quantifying components in complex mixtures. Understanding the elution...
1.2K
Chromatography: Introduction01:10

Chromatography: Introduction

6.4K
Chromatography is a technique used to separate compounds based on differences of partitioning between two phases, the stationary phase and the mobile phase.
The phase in which the compounds linger or on which the compounds adsorb is called the stationary phase, whereas the mobile phase is the solvent that carries the solutes to be analyzed. In traditional column chromatography, the mixture flows through the stationary phase, and the compounds partition between the stationary and mobile phases...
6.4K

You might also read

Related Articles

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

Sort by
Same author

Uncertainty-driven model-based search methods for method development in liquid chromatography.

Journal of chromatography. A·2026
Same author

Evaluating COVID-19 vaccine allocation policies using Bayesian m-top exploration.

Scientific reports·2026
Same author

Automated micropillar array design with Bayesian optimization and computational fluid dynamics.

Journal of chromatography. A·2026
Same author

Computational study of the mass transfer effects in metal-organic framework columns for liquid chromatography.

Journal of chromatography. A·2026
Same author

Revisiting the definition and measurement of total accessible and hold-up volumes in liquid chromatography: Current understanding and advances.

Journal of chromatography. A·2026
Same author

SERS Substrate Fabrication via Rapid Triboelectrification-Driven Self-Assembly of Close-Packed Colloidal Monolayers.

Small methods·2026

Related Experiment Video

Updated: Dec 11, 2025

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

5.3K

Application of evolutionary algorithms to optimise one- and two-dimensional gradient chromatographic separations.

Bram Huygens1, Kyriakos Efthymiadis2, Ann Nowé2

  • 1Vrije Universiteit Brussel, Department of Chemical Engineering, Pleinlaan 2, 1050 Brussels, Belgium.

Journal of Chromatography. A
|August 22, 2020
PubMed
Summary

Evolutionary algorithms, including genetic algorithms (GA) and evolution strategies (ES), significantly improve chromatographic method development searches. ES algorithms excel in complex searches, outperforming GA and CMA-ES for extensive optimization tasks.

Keywords:
Evolutionary algorithmsGradient elutionLiquid chromatographyMethod developmentMulti-dimensional chromatography

More Related Videos

Curtain Flow Column: Optimization of Efficiency and Sensitivity
06:44

Curtain Flow Column: Optimization of Efficiency and Sensitivity

Published on: June 12, 2016

6.8K
Automated Hydrophobic Interaction Chromatography Column Selection for Use in Protein Purification
10:21

Automated Hydrophobic Interaction Chromatography Column Selection for Use in Protein Purification

Published on: September 21, 2011

44.7K

Related Experiment Videos

Last Updated: Dec 11, 2025

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

5.3K
Curtain Flow Column: Optimization of Efficiency and Sensitivity
06:44

Curtain Flow Column: Optimization of Efficiency and Sensitivity

Published on: June 12, 2016

6.8K
Automated Hydrophobic Interaction Chromatography Column Selection for Use in Protein Purification
10:21

Automated Hydrophobic Interaction Chromatography Column Selection for Use in Protein Purification

Published on: September 21, 2011

44.7K

Area of Science:

  • Analytical Chemistry
  • Computational Chemistry
  • Biochemistry

Background:

  • Chromatographic method development is crucial for separating complex mixtures.
  • Manual or grid search methods can be time-consuming and inefficient.
  • Evolutionary algorithms offer potential for optimizing complex search spaces.

Purpose of the Study:

  • To evaluate the performance of genetic algorithms (GA), evolution strategies (ES), and covariance matrix adaptation evolution strategy (CMA-ES) for chromatographic method development.
  • To compare the efficiency of these algorithms against a standard grid search.
  • To analyze the scalability and convergence properties of each algorithm.

Main Methods:

  • Implementation and parameter optimization of GA, ES, and CMA-ES.
  • Benchmarking against a plain grid search in 1D and 2D chromatography.
  • Analysis of search runs required for achieving target separation quality.
  • Mathematical modeling of algorithm performance using hyperbolic laws.

Main Results:

  • All tested evolutionary algorithms significantly outperformed grid search in terms of required runs.
  • ES algorithms demonstrated superior performance for searches requiring over 100 runs.
  • CMA-ES showed excellent performance for short searches (<50 runs) but risked local optima.
  • Algorithm performance advantage increased with problem difficulty.

Conclusions:

  • Evolutionary algorithms provide a powerful enhancement for chromatographic method development searches.
  • The choice of algorithm (ES, GA, CMA-ES) depends on the expected search space size and complexity.
  • Performance differences between algorithms and grid search are quantifiable and scale with problem difficulty.