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 Experiment Videos

[Column efficiency prediction of two dimensional chromatography by artificial neural network].

J Huang1, S F Zhou, Z S Guo

  • 1College of Chemical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.

Se Pu = Chinese Journal of Chromatography
|January 25, 2003
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

[Learning curve of uniportal video-assisted thoracoscopic surgery lobectomy for the treatment of resectable lung cancer].

Zhonghua wai ke za zhi [Chinese journal of surgery]·2018
Same author

[A prospective comparative study examing the impact of uniportal and three portal video-assisted thoracic surgery on short-term quality of life in lung cancer].

Zhonghua wai ke za zhi [Chinese journal of surgery]·2018
Same author

[A serum lipidomic study of patients with non-alcoholic fatty liver disease].

Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology·2017
Same author

Magnetic mediation effect of a C impurity in a Mn-doped Zn₁₂O₁₂ nanocluster: a case of multiple exchange interactions.

Journal of physics. Condensed matter : an Institute of Physics journal·2015
Same author

A low-copy-number Sorghum DNA sequence that detects hypervariable EcoRV fragments.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·2013
Same author

A RFLP linkage map of Sorghum bicolor (L.) Moench.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·2013
Same journal

[Experimental teaching design of instrument analysis for undergraduate study： detection of bifenthrin pesticide residues in tea by response surface methodology-optimized QuEChERS combined with gas chromatography-mass spectrometry].

Se pu = Chinese journal of chromatography·2026
Same journal

[Case-based teaching with both positive and negative examples in undergraduate analytical chemistry laboratory： determination of six nitrogen-containing pesticides in environmental samples by solid-phase microextraction-high performance liquid chromatography].

Se pu = Chinese journal of chromatography·2026
Same journal

[Revolution teaching practice in sample pretreatment supported by large-scale instrument： a case study of magnetic covalent organic framework enriching organic ultraviolet filters in seawater].

Se pu = Chinese journal of chromatography·2026
Same journal

[Determination of 40 carbonyl compounds in ambient air by high performance liquid chromatography-triple quadrupole mass spectrometry].

Se pu = Chinese journal of chromatography·2026
Same journal

[Determination of 22 organophosphates and their metabolites and 11 phthalate metabolites in human whole blood by ultra performance liquid chromatography-tandem mass spectrometry].

Se pu = Chinese journal of chromatography·2026
Same journal

[Determination of <i>S-</i>enantiomer in linagliptin by supercritical fluid chromatography-ultraviolet detection].

Se pu = Chinese journal of chromatography·2026
See all related articles

Artificial neural network (ANN) modeling effectively predicts column efficiency in chromatography. This method accurately captures complex, non-linear relationships between operating conditions and performance.

Area of Science:

  • Chromatography
  • Artificial Intelligence
  • Chemical Engineering

Background:

  • Traditional modeling methods struggle with complex, non-linear relationships between column efficiency and operating conditions in chromatography.
  • Establishing quantitative models for predicting column performance is challenging due to intricate factor interactions.

Purpose of the Study:

  • To investigate the relationship between column efficiency and operating conditions using artificial neural network (ANN) modeling.
  • To develop a predictive model for column efficiency in a two-dimensional column chromatography system.
  • To demonstrate the suitability of ANN for modeling complex chromatographic systems.

Main Methods:

  • Utilized a three-layer, weight-connected artificial neural network (ANN) model.

Related Experiment Videos

  • Employed the varied-pace back-propagation (BP) learning algorithm.
  • Defined input vectors as pre-column temperature, main column temperature, pressure difference, and vent rate.
  • Defined output vectors as the effective plate number, representing column efficiency.

    • Main Results:

    • The ANN model accurately predicted column efficiency (effective plate number) under various operating conditions.
    • Model predictions showed strong consistency with experimentally found values.
    • The developed model successfully captured the non-linear dynamics of the chromatographic system.

    Conclusions:

    • Artificial neural network (ANN) modeling is a suitable and effective method for studying column efficiency in two-dimensional column chromatography.
    • ANN provides a robust approach to quantitatively model complex, non-linear relationships in chromatographic systems.
    • This study validates the application of ANN for optimizing operating conditions to enhance column performance.