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

Heterogeneous catalyst design using stochastic optimization algorithms

McLeod1, Gladden

  • 1School of Chemical Engineering, University of Edinburgh, United Kingdom. amcleod@chemeng.ed.ac.uk

Journal of Chemical Information and Computer Sciences
|August 24, 2000
PubMed
Summary

Optimizing heterogeneous catalyst design using stochastic algorithms like genetic algorithms and simulated annealing significantly boosts catalytic activity for diffusion-limited reactions. Simulated annealing proved more efficient for finding optimal catalyst structures.

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

Atlas of Vitreous Biomicroscopy.

The British journal of ophthalmology·2001
Same author

Isotopic analysis of uranium in tree bark by ICP mass spectrometry: a strategy for assessment of airborne contamination

Analytical chemistry·2000
Same author

Probing Ganglia Dissolution and Mobilization in a Water-Saturated Porous Medium using MRI.

Journal of colloid and interface science·2000
Same author

Total Synthesis of (+)-Concanamycin F We thank the EPSRC (GR/K54052), Knoll Pharmaceuticals (CASE Studentship to V.A.D.), the Cambridge Commonwealth Trust (M.D.M.), and Merck for support, and Dr R. Norrie (Knoll Pharmaceuticals) for helpful discussions. We also thank Prof. A. Zeeck (Göttingen) for kindly providing copies of (1)H NMR spectra of concanamycin F (concanolide A).

Angewandte Chemie (International ed. in English)·2000
Same author

Population structure of North American beluga whales (Delphinapterus leucas) based on nuclear DNA microsatellite variation and contrasted with the population structure revealed by mitochondrial DNA variation

Molecular ecology·1999
Same author

Echo-planar imaging of porous media with spatial resolution below 100 &mgr;m

Journal of magnetic resonance (San Diego, Calif. : 1997)·1999

Area of Science:

  • Materials Science
  • Chemical Engineering
  • Computational Chemistry

Background:

  • Heterogeneous catalysis is crucial for many chemical processes.
  • Catalyst design often involves optimizing the arrangement of active sites.
  • Stochastic optimization offers a powerful approach for complex design problems.

Purpose of the Study:

  • To apply stochastic optimization algorithms for designing efficient heterogeneous catalysts.
  • To determine the optimal geometric arrangement of active sites for specific reactions.
  • To compare the efficiency of genetic algorithms and simulated annealing in catalyst design.

Main Methods:

  • Utilized genetic algorithms and simulated annealing to explore catalyst configurations.
  • Modeled diffusion-limited reactions A + B --> 0 and A + B2 --> 0.

Related Experiment Videos

  • Evaluated catalyst activity based on the arrangement of two distinct catalytic sites.

    • Main Results:

    • Identified a checkerboard active site distribution as optimal for both reactions.
    • Achieved approximately 25% higher catalytic activity with the optimal checkerboard design compared to random distributions.
    • Confirmed that both algorithms yield identical optimal solutions.

    Conclusions:

    • Stochastic optimization effectively enhances heterogeneous catalyst design.
    • Simulated annealing is a more efficient algorithm for this optimization task.
    • Optimal site arrangement significantly impacts catalyst performance for diffusion-limited reactions.