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Catalysis

Catalysis

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.

Factors Influencing the Rate of Chemical Reactions

Factors Influencing the Rate of Chemical Reactions

A variety of factors influence the rate of chemical reactions. For a chemical reaction to happen, atoms must collide with enough energy to overcome the repulsion between their electrons. This energy is called activation energy. Factors influencing the rate of reaction either lower the activation energy or increase the likelihood of a successful collision.
Concentration and Pressure:
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Reduction of Alkenes: Asymmetric Catalytic Hydrogenation

Reduction of Alkenes: Asymmetric Catalytic Hydrogenation

Catalytic hydrogenation of alkenes is a transition-metal catalyzed reduction of the double bond using molecular hydrogen to give alkanes. The mode of hydrogen addition follows syn stereochemistry.
The metal catalyst used can be either heterogeneous or homogeneous. When hydrogenation of an alkene generates a chiral center, a pair of enantiomeric products is expected to form. However, an enantiomeric excess of one of the products can be facilitated using an enantioselective reaction or an...

Catalytically Perfect Enzymes

Catalytically Perfect Enzymes

The theory of catalytically perfect enzymes was first proposed by W.J. Albery and J. R. Knowles in 1976. These enzymes catalyze biochemical reactions at high-speed. Their catalytic efficiency values range from 108-109 M-1s-1. These enzymes are also called 'diffusion-controlled' as the only rate-limiting step in the catalysis is that of the substrate diffusion into the active site. Examples include triose phosphate isomerase, fumarase, and superoxide dismutase.

Most enzymes...

Introduction to Mechanisms of Enzyme Catalysis

Introduction to Mechanisms of Enzyme Catalysis

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...

Reduction of Alkenes: Catalytic Hydrogenation

Reduction of Alkenes: Catalytic Hydrogenation

Alkenes undergo reduction by the addition of molecular hydrogen to give alkanes. Because the process generally occurs in the presence of a transition-metal catalyst, the reaction is called catalytic hydrogenation.
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The hydrogenation process takes place on the...

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Related Experiment Video

Updated: Jan 14, 2026

Heterogeneous Removal of Water-Soluble Ruthenium Olefin Metathesis Catalyst from Aqueous Media Via Host-Guest Interaction

Heterogeneous Removal of Water-Soluble Ruthenium Olefin Metathesis Catalyst from Aqueous Media Via Host-Guest Interaction

Published on: August 23, 2018

Reaction-conditioned generative model for catalyst design and optimization with CatDRX.

Apakorn Kengkanna¹, Yuta Kikuchi¹, Takashi Niwa²

¹Department of Computer Science, School of Computing, Institute of Science Tokyo, Kanagawa, Japan.

Communications Chemistry

|October 23, 2025

Summary

This summary is machine-generated.

This study introduces CatDRX, a novel framework for catalyst discovery using a generative model. It efficiently identifies and predicts catalyst performance across diverse reactions, accelerating chemical innovation.

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Area of Science:

Catalysis
Computational Chemistry
Materials Science

Background:

Catalyst design is crucial for optimizing chemical reactions, reducing waste, and improving efficiency.
Current generative models for catalyst discovery are often limited to specific reaction types and predefined molecular fragments.
A broader approach is needed to explore novel catalysts across diverse reaction spaces.

Purpose of the Study:

To present CatDRX, a catalyst discovery framework utilizing a reaction-conditioned variational autoencoder.
To generate novel catalysts and predict their performance for various chemical reactions.
To advance catalyst design and discovery in the chemical and pharmaceutical industries.

Main Methods:

Developed a reaction-conditioned variational autoencoder generative model (CatDRX).
Pre-trained the model on a large reaction database and fine-tuned it for specific downstream reactions.
Integrated property optimization and validation based on reaction mechanisms and chemical knowledge.

Main Results:

Achieved competitive performance in predicting reaction yield and catalytic activity.
Successfully generated potential catalysts tailored to specific reaction conditions.
Demonstrated the framework's effectiveness through various case studies.

Conclusions:

CatDRX offers a versatile approach to catalyst design and discovery.
The framework facilitates the identification of novel catalysts by considering reaction components.
This work advances catalyst development for industrial applications, including pharmaceuticals.