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

Arrhenius Plots02:34

Arrhenius Plots

43.2K
The Arrhenius equation relates the activation energy and the rate constant, k, for chemical reactions. In the Arrhenius equation, k = Ae−Ea/RT, R is the ideal gas constant, which has a value of 8.314 J/mol·K, T is the temperature on the kelvin scale, Ea is the activation energy in J/mole, e is the constant 2.7183, and A is a constant called the frequency factor, which is related to the frequency of collisions and the orientation of the reacting molecules.
The Arrhenius equation can be used...
43.2K
Catalysis02:50

Catalysis

28.7K
The presence of a catalyst affects the rate of a chemical reaction. A catalyst is a substance that can increase the reaction rate without being consumed during the process. A basic comprehension of a catalysts’ role during chemical reactions can be understood from the concept of reaction mechanisms and energy diagrams.
28.7K
Turnover Number and Catalytic Efficiency01:19

Turnover Number and Catalytic Efficiency

16.7K
The turnover number of an enzyme is the maximum number of substrate molecules it can transform per unit time. Turnover numbers for most enzymes range from 1 to 1000 molecules per second. Catalase has the known highest turnover number, capable of converting up to 2.8×106 molecules of hydrogen peroxide into water and oxygen per second. Lysozyme has the lowest known turnover number of half a molecule per second.
Chymotrypsin is a pancreatic enzyme that breaks down proteins during digestion....
16.7K
Introduction to Mechanisms of Enzyme Catalysis01:13

Introduction to Mechanisms of Enzyme Catalysis

9.4K
For many years, scientists thought that enzyme-substrate binding took place in a simple "lock-and-key" fashion. This model stated that the enzyme and substrate fit together perfectly in one instantaneous step. However, current research supports a more refined view scientists call induced fit. The induced-fit model expands upon the lock-and-key model by describing a more dynamic interaction between enzyme and substrate. As the enzyme and substrate come together, their interaction causes...
9.4K
Voltammograms: Overview01:16

Voltammograms: Overview

427
Voltammograms are current plots as a function of applied potential, offering insights into electrochemical systems. The shape of a voltammogram depends on how the current is measured and whether convection (heat transfer by fluid movement) is present or absent.
Shapes of Voltammograms
427
Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

9.0K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
9.0K

You might also read

Related Articles

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

Sort by
Same author

Modular Framework for 3D Molecular Generation in Computational Chemistry Applications.

Journal of the American Chemical Society·2026
Same author

Methodologic Insights on Building and Evaluating Models for Early Warning of Hypotension during Surgery.

Anesthesiology·2026
Same author

Benchmarking physics-inspired machine learning models for transition metal complexes with diverse charge and spin states.

Digital discovery·2026
Same author

Advancing Reproducibility and Open Data in Theoretical and Computational Chemistry.

Journal of chemical theory and computation·2026
Same author

NaviDiv: a web app for monitoring chemical diversity in generative molecular design.

Digital discovery·2026
Same author

Diastereoselective Synthesis of Housanes via the Carbocupration of Cyclopropenes.

Journal of the American Chemical Society·2026
Same journal

Enhanced and selective oxygen reduction by iron porphyrin with a biguanide residue in the second coordination sphere.

Chemical science·2026
Same journal

Excited-state orbital angular momentum enables all-optical molecular spin coherence.

Chemical science·2026
Same journal

Polyvinyl-based hole-transporting materials processed with non-destructive and green solvents for tin-lead perovskite solar cells and all-perovskite tandems.

Chemical science·2026
Same journal

Pd-catalyzed regio- and enantioselective allylation of cyclic allylboronates.

Chemical science·2026
Same journal

Covalent polyoxometalate-polyimide hybridization: multi-scale molecular engineering toward high-performance sodium-ion battery anodes.

Chemical science·2026
Same journal

Catalytic visible light-driven alkane dehydrogenation by a di-uranyl germanotungstate.

Chemical science·2026
See all related articles

Related Experiment Video

Updated: Nov 2, 2025

On the Preparation and Testing of Fuel Cell Catalysts Using the Thin Film Rotating Disk Electrode Method
12:12

On the Preparation and Testing of Fuel Cell Catalysts Using the Thin Film Rotating Disk Electrode Method

Published on: March 16, 2018

22.4K

Data-powered augmented volcano plots for homogeneous catalysis.

Matthew D Wodrich1, Alberto Fabrizio1,2, Benjamin Meyer1,2

  • 1Laboratory for Computational Molecular Design, Institute of Chemical Sciences and Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL) 1015 Lausanne Switzerland clemence.corminboeuf@epfl.ch.

Chemical Science
|June 14, 2021
PubMed
Summary
This summary is machine-generated.

Data-driven catalyst design reveals new thermodynamic insights for hydroformylation. Augmented volcano plots identify optimal catalysts by comparing energy profiles, highlighting distinct trends for iridium versus cobalt/rhodium species.

More Related Videos

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

13.0K
Synthesis and Testing of Supported Pt-Cu Solid Solution Nanoparticle Catalysts for Propane Dehydrogenation
10:19

Synthesis and Testing of Supported Pt-Cu Solid Solution Nanoparticle Catalysts for Propane Dehydrogenation

Published on: July 18, 2017

12.2K

Related Experiment Videos

Last Updated: Nov 2, 2025

On the Preparation and Testing of Fuel Cell Catalysts Using the Thin Film Rotating Disk Electrode Method
12:12

On the Preparation and Testing of Fuel Cell Catalysts Using the Thin Film Rotating Disk Electrode Method

Published on: March 16, 2018

22.4K
Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

13.0K
Synthesis and Testing of Supported Pt-Cu Solid Solution Nanoparticle Catalysts for Propane Dehydrogenation
10:19

Synthesis and Testing of Supported Pt-Cu Solid Solution Nanoparticle Catalysts for Propane Dehydrogenation

Published on: July 18, 2017

12.2K

Area of Science:

  • Catalysis
  • Computational Chemistry
  • Materials Science

Background:

  • Data-driven approaches are revolutionizing catalyst design.
  • Understanding reaction thermodynamics is crucial for optimizing catalytic processes.
  • Hydroformylation is a key industrial reaction.

Purpose of the Study:

  • To explore thermodynamic trends in hydroformylation using a data-driven workflow.
  • To introduce augmented volcano plots for visualizing catalyst performance.
  • To identify catalysts with energy profiles closely matching an ideal reference.

Main Methods:

  • Data generation and statistical analysis.
  • Dimensionality reduction algorithms.
  • Development and application of augmented volcano plots.

Main Results:

  • Augmented volcano plots effectively visualize catalyst cycle energy profiles.
  • Identified distinct thermodynamic scaling relationships for iridium vs. cobalt/rhodium catalysts.
  • Confirmed findings with reconstituted molecular volcano plots showing two distinct volcano shapes.

Conclusions:

  • Augmented volcano plots offer a superior method for catalyst screening.
  • Metal type significantly influences hydroformylation thermodynamics.
  • Iridium catalysts show greater thermodynamic favorability for this reaction.