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Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

8.7K
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,...
8.7K
Measuring Reaction Rates03:09

Measuring Reaction Rates

26.3K
Polarimetry finds application in chemical kinetics to measure the concentration and reaction kinetics of optically active substances during a chemical reaction. Optically active substances have the capability of rotating the plane of polarization of linearly polarized light passing through them—a feature called optical rotation. Optical activity is attributed to the molecular structure of substances. Normal monochromatic light is unpolarized and possesses oscillations of the electrical...
26.3K
Reaction Rate02:53

Reaction Rate

56.4K
The rate of reaction is the change in the amount of a reactant or product per unit time. Reaction rates are therefore determined by measuring the time dependence of some property that can be related to reactant or product amounts. Rates of reactions that consume or produce gaseous substances, for example, are conveniently determined by measuring changes in volume or pressure.
The mathematical representation of the change in the concentration of reactants and products, over time, is the rate...
56.4K
Concentration and Rate Law03:03

Concentration and Rate Law

33.5K
The rate of a reaction is affected by the concentrations of reactants. Rate laws (differential rate laws) or rate equations are mathematical expressions describing the relationship between the rate of a chemical reaction and the concentration of its reactants.
For example, in a generic reaction aA + bB ⟶ products, where a and b are stoichiometric coefficients, the rate law can be written as:
33.5K
Rate Law and Reaction Order02:33

Rate Law and Reaction Order

10.2K
The rate of a reaction is affected by the concentrations of reactants. Rate laws (differential rate laws) or rate equations are mathematical expressions describing the relationship between the rate of a chemical reaction and the concentration of its reactants.
For example, in a generic reaction aA + bB ⟶ products, where a and b are stoichiometric coefficients, the rate law can be written as:
rate = k[A]m[B]n
[A] and [B] represent the molar concentrations of reactants, and k is the rate...
10.2K
Determining Order of Reaction02:53

Determining Order of Reaction

58.2K
Rate laws describe the relationship between the rate of a chemical reaction and the concentration of its reactants. In a rate law, the rate constant k and the reaction orders are determined experimentally by observing how the rate of reaction changes as the concentrations of the reactants are changed. A common experimental approach to the determination of rate laws is the method of initial rates. This method involves measuring reaction rates for multiple experimental trials carried out using...
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Related Experiment Video

Updated: Oct 9, 2025

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes
09:42

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes

Published on: January 16, 2016

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Progress towards machine learning reaction rate constants.

Evan Komp1, Nida Janulaitis1, Stéphanie Valleau1

  • 1Department of Chemical Engineering, University of Washington, Seattle, Washington 98195, USA. valleau@uw.edu.

Physical Chemistry Chemical Physics : PCCP
|December 22, 2021
PubMed
Summary
This summary is machine-generated.

Machine learning (ML) accelerates chemical reaction rate constant calculations by predicting values from input features, overcoming the "curse of dimensionality" in traditional methods. This perspective explores ML applications for predicting energies, force fields, and reaction pathways.

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Area of Science:

  • Computational Chemistry
  • Chemical Physics
  • Materials Science

Background:

  • Calculating reaction rate constants is computationally expensive due to potential energy surface exploration.
  • The "curse of dimensionality" limits the feasibility of these calculations for larger systems.

Purpose of the Study:

  • To introduce supervised machine learning (ML) for predicting chemical reaction rate constants.
  • To review existing kinetic datasets, feature representations, and ML algorithm designs for this purpose.

Main Methods:

  • Utilizing ML to predict activation, reaction, solvation, and dissociation energies.
  • Employing ML for reactive force field parameter prediction and minimum energy path searches.
  • Discussing ML models for direct reaction rate constant prediction.

Main Results:

  • ML significantly reduces the computational cost associated with reaction rate calculations.
  • ML models can accurately predict various energy components crucial for kinetics.
  • ML aids in optimizing force fields and accelerating reaction pathway discovery.

Conclusions:

  • Machine learning offers a powerful approach to overcome computational barriers in chemical kinetics.
  • Further research is needed to explore and refine ML applications for chemical reaction rate constants.