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Related Concept Videos

Arrhenius Plots02:34

Arrhenius Plots

48.7K
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...
48.7K
Temperature Dependence on Reaction Rate02:55

Temperature Dependence on Reaction Rate

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The Collision Theory
Atoms, molecules, or ions must collide before they can react with each other. Atoms must be close together to form chemical bonds. This premise is the basis for a theory that explains many observations regarding chemical kinetics, including factors affecting reaction rates.
The collision theory is based on the postulates that (i) the reaction rate is proportional to the rate of reactant collisions, (ii) the reacting species collide in an orientation allowing contact between...
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Effect of Temperature Change on Reaction Rate02:28

Effect of Temperature Change on Reaction Rate

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The Arrhenius equation,
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Le Chatelier's Principle: Changing Temperature02:19

Le Chatelier's Principle: Changing Temperature

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Consistent with the law of mass action, an equilibrium stressed by a change in concentration will shift to re-establish equilibrium without any change in the value of the equilibrium constant, K. When an equilibrium shifts in response to a temperature change, however, it is re-established with a different relative composition that exhibits a different value for the equilibrium constant.
To understand this phenomenon, consider the elementary reaction:
36.6K
Reaction Mechanisms: Rate-limiting Step Approximation01:29

Reaction Mechanisms: Rate-limiting Step Approximation

50
The rate-determining step, or RDS, in a chemical reaction is the slowest step that determines the overall reaction rate. It is identified by using the observed rate law and typically involves approximation methods like the RDS approximation or the steady-state approximation.In the RDS approximation, also known as the rate-limiting-step or equilibrium approximation, the reaction mechanism consists of one or more reversible reactions near equilibrium, followed by a slower RDS, and then one or...
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Clausius-Clapeyron Equation02:35

Clausius-Clapeyron Equation

63.8K
The equilibrium between a liquid and its vapor depends on the temperature of the system; a rise in temperature causes a corresponding rise in the vapor pressure of its liquid. The Clausius-Clapeyron equation gives the quantitative relation between a substance’s vapor pressure (P) and its temperature (T); it predicts the rate at which vapor pressure increases per unit increase in temperature.
63.8K

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Estimating Arrhenius parameters using temperature programmed molecular dynamics.

Venkataramana Imandi1, Abhijit Chatterjee1

  • 1Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai 400076, India.

The Journal of Chemical Physics
|July 25, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a maximum likelihood method using molecular dynamics to efficiently estimate kinetic rates and Arrhenius parameters. The approach accurately calculates transition rates, especially for rare events at low temperatures.

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Area of Science:

  • Computational Chemistry
  • Chemical Kinetics
  • Materials Science

Background:

  • Estimating kinetic rates and Arrhenius parameters is crucial for understanding chemical reactions and material properties.
  • Traditional methods can be computationally expensive, especially for complex systems or rare events.

Purpose of the Study:

  • To develop and validate an efficient method for estimating kinetic rates and Arrhenius parameters.
  • To demonstrate the method's applicability to systems with complex energy landscapes.

Main Methods:

  • Utilizing maximum likelihood analysis on waiting times from temperature-programmed molecular dynamics.
  • Applying the method to prototype systems: solvated alanine dipeptide, metal-solvent interface diffusion, and lithium diffusion in silicon.

Main Results:

  • Efficient estimation of kinetic rates and Arrhenius parameters.
  • Accurate calculation of transition rates even with multiple activated pathways.
  • Successful application to systems with corrugated energy landscapes.

Conclusions:

  • The proposed method provides accurate rate parameter estimates, particularly valuable for predicting rare event rates at low temperatures.
  • Systematic coarse-graining can further enhance accessible timescales.
  • The method is robust, yielding good estimates with 500-1000 waiting times.