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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...
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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,...
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Enzyme kinetics studies the rates of biochemical reactions. Scientists monitor the reaction rates for a particular enzymatic reaction at various substrate concentrations. Additional trials with inhibitors or other molecules that affect the reaction rate may also be performed.
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The Michaelis–Menten equation is a fundamental model for describing capacity-limited kinetics in drug metabolism. It offers insights into the rate of decline of plasma drug concentration Cp over time, with Vmax and KM as pivotal parameters.
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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...
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This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
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Predicting Long-Time-Scale Kinetics under Variable Experimental Conditions with Kinetica.jl.

Joe Gilkes1,2, Mark T Storr3, Reinhard J Maurer1,4

  • 1Department of Chemistry, University of Warwick, Gibbet Hill Road, CV4 7AL Coventry, U.K.

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|June 3, 2024
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Summary

Kinetica.jl automates the creation and kinetic analysis of large chemical reaction networks. This software enables accurate long-time-scale molecular degradation predictions for materials design.

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Area of Science:

  • Computational Chemistry
  • Materials Science
  • Chemical Engineering

Background:

  • Predicting molecular degradation over long timescales is crucial for industrial materials design.
  • Constructing accurate chemical reaction networks with kinetic data is computationally intensive.
  • Existing methods struggle with the scale and complexity of realistic reaction systems.

Purpose of the Study:

  • To introduce Kinetica.jl, a novel software package for automated chemical reaction network generation and kinetic modeling.
  • To enable the efficient simulation of complex chemical systems over extended time scales.
  • To bridge the gap between theoretical reaction networks and experimental observations.

Main Methods:

  • A kinetics-driven algorithm explores chemical reaction space to construct large-scale networks.
  • Machine learning models predict activation energies for elementary reactions.
  • Symbolic-numeric modeling and discrete kinetic approximation enable efficient long-time-scale simulations.
  • Hydrocarbon pyrolysis was simulated using transient temperature profiles.

Main Results:

  • Kinetica.jl can generate and characterize networks with approximately 10^3 chemical species and 10^4-10^5 reactions.
  • The software allows flexible and efficient computation of kinetic profiles under variable temperature conditions.
  • Accurate long-time-scale kinetic profiles were propagated for automated reaction network refinement.
  • Successful demonstration of hydrocarbon pyrolysis simulation over second timescales.

Conclusions:

  • Kinetica.jl provides an automated solution for generating, characterizing, and modeling complex chemical reaction systems.
  • The package facilitates direct connections between computational models and experimental data.
  • This approach significantly advances the capability for predicting molecular degradation and designing new materials.