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Reaction Rate02:53

Reaction Rate

51.9K
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...
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The Integrated Rate Law: The Dependence of Concentration on Time02:39

The Integrated Rate Law: The Dependence of Concentration on Time

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While the differential rate law relates the rate and concentrations of reactants, a second form of rate law called the integrated rate law relates concentrations of reactants and time. Integrated rate laws can be used to determine the amount of reactant or product present after a period of time or to estimate the time required for a reaction to proceed to a certain extent. For example, an integrated rate law helps determine the length of time a radioactive material must be stored for its...
35.0K
Measuring Reaction Rates03:09

Measuring Reaction Rates

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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...
25.0K
Concentration and Rate Law03:03

Concentration and Rate Law

30.6K
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:
30.6K
Multi-Step Reactions02:31

Multi-Step Reactions

7.3K
Chemical reactions often occur in a stepwise fashion involving two or more distinct reactions taking place in a sequence. A balanced equation indicates the reacting species and the product species, but it reveals no details about how the reaction occurs at the molecular level. The reaction mechanism (or reaction path) provides details regarding the precise, step-by-step process by which a reaction occurs. Each of the steps in a reaction mechanism is called an elementary reaction. These...
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Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

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Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
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Related Experiment Video

Updated: Jun 22, 2025

Saccharomyces cerevisiae Exponential Growth Kinetics in Batch Culture to Analyze Respiratory and Fermentative Metabolism
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Good Rates From Bad Coordinates: The Exponential Average Time-dependent Rate Approach.

Nicodemo Mazzaferro1, Subarna Sasmal1, Pilar Cossio2,3

  • 1Department of Chemistry, New York University, New York, New York 10003, United States.

Journal of Chemical Theory and Computation
|July 2, 2024
PubMed
Summary

This study introduces a new method, the Exponential Average Time-Dependent Rate (EATR) estimator, to accurately calculate biochemical process rates using molecular dynamics simulations. EATR improves upon existing techniques by more rapidly converging to true rate constants, even with short simulation times.

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Area of Science:

  • Computational chemistry
  • Biophysics
  • Molecular dynamics simulations

Background:

  • Calculating biochemical reaction rates via molecular dynamics is challenging due to long timescales.
  • Existing methods are limited by exponential scaling with free-energy barriers.

Purpose of the Study:

  • To develop an improved rate estimator for molecular dynamics simulations.
  • To introduce the Exponential Average Time-Dependent Rate (EATR) estimator.
  • To assess the quality of collective variables (CVs) used in simulations.

Main Methods:

  • Developed a new formulation for rate estimation in biased molecular dynamics.
  • Introduced the CV biasing efficiency (γ) parameter.
  • Tested the EATR estimator on model potentials, coarse-grained proteins, and atomistic protein folding.

Main Results:

  • EATR converges faster to true rate constants than previous methods, even with short bias deposition times.
  • The CV biasing efficiency (γ) effectively assesses the quality of chosen CVs.
  • The method successfully handles multiple, less-than-optimal bias coordinates and integrates with OPES flooding.

Conclusions:

  • The EATR estimator provides a powerful framework for predicting rate constants from biased molecular dynamics simulations.
  • This approach enhances the accuracy and efficiency of calculating biochemical process rates.
  • The CV biasing efficiency offers a valuable metric for simulation quality assessment.