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In chemistry, the rate equation (also known as the rate law or empirical differential rate equation) is an empirical differential mathematical expression for the reaction rate of a given reaction in terms of concentrations of chemical species and constant parameters (normally rate coefficients and partial orders of reaction) only.[1] For many reactions, the initial rate is given by a power law such as

where and are the molar concentrations of the species and usually in moles per liter (molarity, ). The exponents and are the partial orders of reaction for and , respectively, and the overall reaction order is the sum of the exponents. These are often positive integers, but they may also be zero, fractional, or negative. The order of reaction is a number which quantifies the degree to which the rate of a chemical reaction depends on concentrations of the reactants.[2] In other words, the order of reaction is the exponent to which the concentration of a particular reactant is raised.[2] The constant is the reaction rate constant or rate coefficient and at very few places velocity constant or specific rate of reaction. Its value may depend on conditions such as temperature, ionic strength, surface area of an adsorbent, or light irradiation. If the reaction goes to completion, the rate equation for the reaction rate applies throughout the course of the reaction.

Elementary (single-step) reactions and reaction steps have reaction orders equal to the stoichiometric coefficients for each reactant. The overall reaction order, i.e. the sum of stoichiometric coefficients of reactants, is always equal to the molecularity of the elementary reaction. However, complex (multi-step) reactions may or may not have reaction orders equal to their stoichiometric coefficients. This implies that the order and the rate equation of a given reaction cannot be reliably deduced from the stoichiometry and must be determined experimentally, since an unknown reaction mechanism could be either elementary or complex. When the experimental rate equation has been determined, it is often of use for deduction of the reaction mechanism.

In highly diluted solutions, such as at concentrations below the micromolar level, molecular collisions are primarily governed by diffusion. Under these conditions, the apparent reaction order deviates from the stoichiometric expectation because reactant molecules require additional time to traverse longer distances before encountering one another. This behavior can be described by Fick's laws of diffusion and is consistent with fractal reaction kinetics, which yield fractional reaction orders.

The rate equation of a reaction with an assumed multi-step mechanism can often be derived theoretically using quasi-steady state assumptions from the underlying elementary reactions, and compared with the experimental rate equation as a test of the assumed mechanism. The equation may involve a fractional order, and may depend on the concentration of an intermediate species.

A reaction can also have an undefined reaction order with respect to a reactant if the rate is not simply proportional to some power of the concentration of that reactant; for example, one cannot talk about reaction order in the rate equation for a bimolecular reaction between adsorbed molecules:

Definition

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Consider a typical chemical reaction in which two reactants A and B combine to form a product C:

This can also be written

The prefactors −1, −2 and 3 (with negative signs for reactants because they are consumed) are known as stoichiometric coefficients. One molecule of A combines with two of B to form 3 of C, so if we use the symbol [X] for the molar concentration of chemical X,[3]

If the reaction takes place in a closed system at constant temperature and volume, without a build-up of reaction intermediates, the reaction rate is defined as

where νi is the stoichiometric coefficient for chemical Xi, with a negative sign for a reactant.[4]

The initial reaction rate has some functional dependence on the concentrations of the reactants,

and this dependence is known as the rate equation or rate law.[5] This law generally cannot be deduced from the chemical equation and must be determined by experiment.[6]

Power laws

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A common form for the rate equation is a power law:[6]

The constant is called the rate constant. The exponents, which can be fractional,[6] are called partial orders of reaction and their sum is the overall order of reaction.[7]

In a dilute solution, an elementary reaction (one having a single step with a single transition state) is empirically found to obey the law of mass action. This predicts that the rate depends only on the concentrations of the reactants, raised to the powers of their stoichiometric coefficients.[8]

The differential rate equation for an elementary reaction using mathematical product notation is:

Where:

  • is the rate of change of reactant concentration with respect to time.
  • k is the rate constant of the reaction.
  • represents the concentrations of the reactants, raised to the powers of their stoichiometric coefficients and multiplied together.

Determination of reaction order

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Method of initial rates

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The natural logarithm of the power-law rate equation is

This can be used to estimate the order of reaction of each reactant. For example, the initial rate can be measured in a series of experiments at different initial concentrations of reactant with all other concentrations kept constant, so that

The slope of a graph of as a function of then corresponds to the order with respect to reactant .[9][10]

However, this method is not always reliable because

  1. measurement of the initial rate requires accurate determination of small changes in concentration in short times (compared to the reaction half-life) and is sensitive to errors, and
  2. the rate equation will not be completely determined if the rate also depends on substances not present at the beginning of the reaction, such as intermediates or products.

Integral method

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The tentative rate equation determined by the method of initial rates is therefore normally verified by comparing the concentrations measured over a longer time (several half-lives) with the integrated form of the rate equation; this assumes that the reaction goes to completion.

For example, the integrated rate law for a first-order reaction is

where is the concentration at time and is the initial concentration at zero time. The first-order rate law is confirmed if is in fact a linear function of time. In this case the rate constant is equal to the slope with sign reversed.[11][12]

Method of flooding

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The partial order with respect to a given reactant can be evaluated by the method of flooding (or of isolation) of Ostwald. In this method, the concentration of one reactant is measured with all other reactants in large excess so that their concentration remains essentially constant. For a reaction a·A + b·B → c·C with rate law the partial order with respect to is determined using a large excess of . In this case

with

and may be determined by the integral method. The order with respect to under the same conditions (with in excess) is determined by a series of similar experiments with a range of initial concentration so that the variation of can be measured.[13]

Zero order

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For zero-order reactions, the reaction rate is independent of the concentration of a reactant, so that changing its concentration has no effect on the rate of the reaction. Thus, the concentration changes linearly with time. The rate law for zero order reaction is

The unit of k is mol dm−3 s−1.[14] This may occur when there is a bottleneck which limits the number of reactant molecules that can react at the same time, for example if the reaction requires contact with an enzyme or a catalytic surface.[15]

Many enzyme-catalyzed reactions are zero order, provided that the reactant concentration is much greater than the enzyme concentration which controls the rate, so that the enzyme is saturated. For example, the biological oxidation of ethanol to acetaldehyde by the enzyme liver alcohol dehydrogenase (LADH) is zero order in ethanol.[16]

Similarly, reactions with heterogeneous catalysis can be zero order if the catalytic surface is saturated. For example, the decomposition of phosphine (PH3) on a hot tungsten surface at high pressure is zero order in phosphine, which decomposes at a constant rate.[15]

In homogeneous catalysis zero order behavior can come about from reversible inhibition. For example, ring-opening metathesis polymerization using third-generation Grubbs catalyst exhibits zero order behavior in catalyst due to the reversible inhibition that occurs between pyridine and the ruthenium center.[17]

First order

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A first order reaction depends on the concentration of only one reactant (a unimolecular reaction). Other reactants can be present, but their concentration has no effect on the rate. The rate law for a first order reaction is

The unit of k is s−1.[14] Although not affecting the above math, the majority of first order reactions proceed via intermolecular collisions. Such collisions, which contribute the energy to the reactant, are necessarily second order. However according to the Lindemann mechanism the reaction consists of two steps: the bimolecular collision which is second order and the reaction of the energized molecule which is unimolecular and first order. The rate of the overall reaction depends on the slowest step, so the overall reaction will be first order when the reaction of the energized reactant is slower than the collision step.

The half-life is independent of the starting concentration and is given by . The mean lifetime is τ = 1/k.[18]

Examples of such reactions are:

  • [19][20]
  • [21]

In organic chemistry, the class of SN1 (nucleophilic substitution unimolecular) reactions consists of first-order reactions. For example, in the reaction of aryldiazonium ions with nucleophiles in aqueous solution, ArN+2 + X → ArX + N2, the rate equation is where Ar indicates an aryl group.[22]

Second order

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A reaction is said to be second order when the overall order is two. The rate of a second-order reaction may be proportional to one concentration squared, or (more commonly) to the product of two concentrations, As an example of the first type, the reaction NO2 + CO → NO + CO2 is second-order in the reactant NO2 and zero order in the reactant CO. The observed rate is given by and is independent of the concentration of CO.[23]

For the rate proportional to a single concentration squared, the time dependence of the concentration is given by

The unit of k is mol−1 dm3 s−1.[14]

The time dependence for a rate proportional to two unequal concentrations is

if the concentrations are equal, they satisfy the previous equation.

The second type includes nucleophilic addition-elimination reactions, such as the alkaline hydrolysis of ethyl acetate:[22]

This reaction is first-order in each reactant and second-order overall:

If the same hydrolysis reaction is catalyzed by imidazole, the rate equation becomes[22]

The rate is first-order in one reactant (ethyl acetate), and also first-order in imidazole, which as a catalyst does not appear in the overall chemical equation.

Another well-known class of second-order reactions are the SN2 (bimolecular nucleophilic substitution) reactions, such as the reaction of n-butyl bromide with sodium iodide in acetone:

This same compound can be made to undergo a bimolecular (E2) elimination reaction, another common type of second-order reaction, if the sodium iodide and acetone are replaced with sodium tert-butoxide as the salt and tert-butanol as the solvent:

Pseudo-first order

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If the concentration of a reactant remains constant (because it is a catalyst, or because it is in great excess with respect to the other reactants), its concentration can be included in the rate constant, leading to a pseudo–first-order (or occasionally pseudo–second-order) rate equation. For a typical second-order reaction with rate equation if the concentration of reactant B is constant then where the pseudo–first-order rate constant The second-order rate equation has been reduced to a pseudo–first-order rate equation, which makes the treatment to obtain an integrated rate equation much easier.

One way to obtain a pseudo-first order reaction is to use a large excess of one reactant (say, [B]≫[A]) so that, as the reaction progresses, only a small fraction of the reactant in excess (B) is consumed, and its concentration can be considered to stay constant. For example, the hydrolysis of esters by dilute mineral acids follows pseudo-first order kinetics, where the concentration of water is constant because it is present in large excess:

The hydrolysis of sucrose (C12H22O11) in acid solution is often cited as a first-order reaction with rate The true rate equation is third-order, however, the concentrations of both the catalyst H+ and the solvent H2O are normally constant, so that the reaction is pseudo–first-order.[24]

Summary for reaction orders 0, 1, 2, and n

[edit]

Elementary reaction steps with order 3 (called ternary reactions) are rare and unlikely to occur. However, overall reactions composed of several elementary steps can, of course, be of any (including non-integer) order.

Parameter Zero order First order Second order nth order (g = 1−n)
Rate Law [25]
Integrated Rate Law [25]

[Except first order]

Units of Rate Constant (k)
Linear Plot to determine k [A] vs. t vs. t vs. t vs. t

[Except first order]

Half-life [25]

[Limit is necessary for first order]

Here stands for concentration in molarity (mol · L−1), for time, and for the reaction rate constant. The half-life of a first-order reaction is often expressed as t1/2 = 0.693/k (as ln(2)≈0.693).

Fractional order

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In fractional order reactions, the order is a non-integer, which often indicates a chemical chain reaction or other complex reaction mechanism. For example, the pyrolysis of acetaldehyde (CH3CHO) into methane and carbon monoxide proceeds with an order of 1.5 with respect to acetaldehyde: [26] The decomposition of phosgene (COCl2) to carbon monoxide and chlorine has order 1 with respect to phosgene itself and order 0.5 with respect to chlorine: [27]

The order of a chain reaction can be rationalized using the steady state approximation for the concentration of reactive intermediates such as free radicals. For the pyrolysis of acetaldehyde, the Rice-Herzfeld mechanism is

Initiation
Propagation
Termination

where • denotes a free radical.[26][28] To simplify the theory, the reactions of the *CHO to form a second *CH3 are ignored.

In the steady state, the rates of formation and destruction of methyl radicals are equal, so that

so that the concentration of methyl radical satisfies

The reaction rate equals the rate of the propagation steps which form the main reaction products CH4 and CO:

in agreement with the experimental order of 3/2.[26][28]

In highly diluted solutions, such as at concentrations below the micromolar level, molecular collisions are primarily governed by diffusion. Under these conditions, the apparent reaction order deviates from the stoichiometric expectation because reactant molecules require additional time to traverse longer distances before encountering one another. This behavior can be described by Fick's laws of diffusion and is consistent with fractal reaction kinetics, which yield fractional reaction orders.

Complex laws

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Mixed order

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More complex rate laws have been described as being mixed order if they approximate to the laws for more than one order at different concentrations of the chemical species involved. For example, a rate law of the form represents concurrent first order and second order reactions (or more often concurrent pseudo-first order and second order) reactions, and can be described as mixed first and second order.[29] For sufficiently large values of [A] such a reaction will approximate second order kinetics, but for smaller [A] the kinetics will approximate first order (or pseudo-first order). As the reaction progresses, the reaction can change from second order to first order as reactant is consumed.

Another type of mixed-order rate law has a denominator of two or more terms, often because the identity of the rate-determining step depends on the values of the concentrations. An example is the oxidation of an alcohol to a ketone by hexacyanoferrate (III) ion [Fe(CN)63−] with ruthenate (VI) ion (RuO42−) as catalyst.[30] For this reaction, the rate of disappearance of hexacyanoferrate (III) is

This is zero-order with respect to hexacyanoferrate (III) at the onset of the reaction (when its concentration is high and the ruthenium catalyst is quickly regenerated), but changes to first-order when its concentration decreases and the regeneration of catalyst becomes rate-determining.

Notable mechanisms with mixed-order rate laws with two-term denominators include:

  • Michaelis–Menten kinetics for enzyme-catalysis: first-order in substrate (second-order overall) at low substrate concentrations, zero order in substrate (first-order overall) at higher substrate concentrations; and
  • the Lindemann mechanism for unimolecular reactions: second-order at low pressures, first-order at high pressures.

Negative order

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A reaction rate can have a negative partial order with respect to a substance. For example, the conversion of ozone (O3) to oxygen follows the rate equation in an excess of oxygen. This corresponds to second order in ozone and order (−1) with respect to oxygen.[31]

When a partial order is negative, the overall order is usually considered as undefined. In the above example, for instance, the reaction is not described as first order even though the sum of the partial orders is , because the rate equation is more complex than that of a simple first-order reaction.

Opposed reactions

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A pair of forward and reverse reactions may occur simultaneously with comparable speeds. For example, A and B react into products P and Q and vice versa (a, b, p, and q are the stoichiometric coefficients):

The reaction rate expression for the above reactions (assuming each one is elementary) can be written as:

where: k1 is the rate coefficient for the reaction that consumes A and B; k−1 is the rate coefficient for the backwards reaction, which consumes P and Q and produces A and B.

The constants k1 and k−1 are related to the equilibrium coefficient for the reaction (K) by the following relationship (set v=0 in balance):

Concentration of A (A0 = 0.25 mol/L) and B versus time reaching equilibrium k1 = 2 min−1 and k−1 = 1 min−1

Simple example

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In a simple equilibrium between two species:

where the reaction starts with an initial concentration of reactant A, , and an initial concentration of 0 for product P at time t=0.

Then the equilibrium constant K is expressed as:

where and are the concentrations of A and P at equilibrium, respectively.

The concentration of A at time t, , is related to the concentration of P at time t, , by the equilibrium reaction equation:

The term is not present because, in this simple example, the initial concentration of P is 0.

This applies even when time t is at infinity; i.e., equilibrium has been reached:

then it follows, by the definition of K, that

and, therefore,

These equations allow us to uncouple the system of differential equations, and allow us to solve for the concentration of A alone.

The reaction equation was given previously as:

For this is simply

The derivative is negative because this is the rate of the reaction going from A to P, and therefore the concentration of A is decreasing. To simplify notation, let x be , the concentration of A at time t. Let be the concentration of A at equilibrium. Then:

Since:

the reaction rate becomes:

which results in:

.

A plot of the negative natural logarithm of the concentration of A in time minus the concentration at equilibrium versus time t gives a straight line with slope k1 + k−1. By measurement of [A]e and [P]e the values of K and the two reaction rate constants will be known.[32]

Generalization of simple example

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If the concentration at the time t = 0 is different from above, the simplifications above are invalid, and a system of differential equations must be solved. However, this system can also be solved exactly to yield the following generalized expressions:

When the equilibrium constant is close to unity and the reaction rates very fast for instance in conformational analysis of molecules, other methods are required for the determination of rate constants for instance by complete lineshape analysis in NMR spectroscopy.

Consecutive reactions

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If the rate constants for the following reaction are and ; , then the rate equation is:

For reactant A:
For reactant B:
For product C:

With the individual concentrations scaled by the total population of reactants to become probabilities, linear systems of differential equations such as these can be formulated as a master equation. The differential equations can be solved analytically and the integrated rate equations are

The steady state approximation leads to very similar results in an easier way.

Parallel or competitive reactions

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Time course of two first order, competitive reactions with differing rate constants.

When a substance reacts simultaneously to give two different products, a parallel or competitive reaction is said to take place.

Two first order reactions

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and , with constants and and rate equations ; and

The integrated rate equations are then ; and .

One important relationship in this case is

One first order and one second order reaction

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This can be the case when studying a bimolecular reaction and a simultaneous hydrolysis (which can be treated as pseudo order one) takes place: the hydrolysis complicates the study of the reaction kinetics, because some reactant is being "spent" in a parallel reaction. For example, A reacts with R to give our product C, but meanwhile the hydrolysis reaction takes away an amount of A to give B, a byproduct: and . The rate equations are: and , where is the pseudo first order constant.[33]

The integrated rate equation for the main product [C] is , which is equivalent to . Concentration of B is related to that of C through

The integrated equations were analytically obtained but during the process it was assumed that . Therefore, previous equation for [C] can only be used for low concentrations of [C] compared to [A]0

Stoichiometric reaction networks

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The most general description of a chemical reaction network considers a number of distinct chemical species reacting via reactions.[34] [35] The chemical equation of the -th reaction can then be written in the generic form

which is often written in the equivalent form

Here

  • is the reaction index running from 1 to ,
  • denotes the -th chemical species,
  • is the rate constant of the -th reaction and
  • and are the stoichiometric coefficients of reactants and products, respectively.

The rate of such a reaction can be inferred by the law of mass action

which denotes the flux of molecules per unit time and unit volume. Here is the vector of concentrations. This definition includes the elementary reactions:

zero order reactions
for which for all ,
first order reactions
for which for a single ,
second order reactions
for which for exactly two ; that is, a bimolecular reaction, or for a single ; that is, a dimerization reaction.

Each of these is discussed in detail below. One can define the stoichiometric matrix

denoting the net extent of molecules of in reaction . The reaction rate equations can then be written in the general form

This is the product of the stoichiometric matrix and the vector of reaction rate functions. Particular simple solutions exist in equilibrium, , for systems composed of merely reversible reactions. In this case, the rate of the forward and backward reactions are equal, a principle called detailed balance. Detailed balance is a property of the stoichiometric matrix alone and does not depend on the particular form of the rate functions . All other cases where detailed balance is violated are commonly studied by flux balance analysis, which has been developed to understand metabolic pathways.[36][37]

General dynamics of unimolecular conversion

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For a general unimolecular reaction involving interconversion of different species, whose concentrations at time are denoted by through , an analytic form for the time-evolution of the species can be found. Let the rate constant of conversion from species to species be denoted as , and construct a rate-constant matrix whose entries are the .

Also, let be the vector of concentrations as a function of time.

Let be the vector of ones.

Let be the identity matrix.

Let be the function that takes a vector and constructs a diagonal matrix whose on-diagonal entries are those of the vector.

Let be the inverse Laplace transform from to .

Then the time-evolved state is given by

thus providing the relation between the initial conditions of the system and its state at time .

See also

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References

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[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
In chemical kinetics, the rate equation, also known as the rate law, is an empirical mathematical relationship that expresses the rate of a chemical reaction as a function of the concentrations of reactants, and sometimes products or catalysts. For a general reaction aA+bBaA + bB \rightarrow products, it takes the form rate=k[A]m[B]n\text{rate} = k [A]^m [B]^n, where kk is the rate constant, [A][A] and [B][B] are the concentrations of the reactants, and mm and nn are the partial reaction orders determined experimentally. The overall reaction order is the sum m+nm + n, which classifies the reaction as zero-order, first-order, second-order, or higher. The foundational concept behind the rate equation emerged from the law of mass action, proposed by Norwegian chemists Cato Maximilian Guldberg and Peter Waage in 1864, which posits that the rate of a chemical reaction is directly proportional to the product of the concentrations of the reacting substances, each raised to a power equal to its stoichiometric coefficient for elementary steps. However, for complex, multi-step reactions, the exponents in the rate equation do not necessarily correspond to stoichiometric coefficients and must be established through experimental methods, such as the initial rates technique, where reaction rates are measured at varying initial concentrations while keeping other variables constant. This empirical nature distinguishes rate equations from balanced chemical equations, providing critical insights into the underlying reaction mechanism and the sequence of elementary steps. The rate constant kk in the rate equation is temperature-dependent and follows the , k=AeEa/RTk = A e^{-E_a / RT}, where AA is the representing the frequency of collisions with proper orientation, EaE_a is the (the minimum energy barrier for the reaction), RR is the , and TT is the absolute in . Higher temperatures exponentially increase kk by enabling more reactant molecules to overcome the activation barrier; as a rough approximation, for many reactions at around , the rate roughly doubles for every 10 °C rise. Rate equations are essential for predicting reaction behavior, optimizing industrial processes like and , and understanding phenomena in fields ranging from to biochemistry.

Fundamentals of Rate Equations

Definition and Basic Principles

In , a rate equation, often referred to as a rate law, is a mathematical expression that describes the relationship between the rate of a and the concentrations of its reactants./12:_Kinetics/12.04:_Rate_Laws) The rate of reaction itself is defined as the change in concentration of a reactant or product over time, typically expressed as the negative change in reactant concentration or the positive change in product concentration, adjusted for stoichiometric coefficients to ensure consistency across species. For a general reaction aA+bBaA + bB \rightarrow products, the rate law takes the form rate=k[A]m[B]n\text{rate} = k [A]^m [B]^n, where [A][A] and [B][B] are the concentrations of the reactants, mm and nn are the reaction orders with respect to each reactant (which may be integers, fractions, or zero), and kk is the rate constant./12:_Kinetics/12.04:_Rate_Laws) This differential form can be written equivalently as d[product]dt=k[A]m[B]n\frac{d[\text{product}]}{dt} = k [A]^m [B]^n for product formation or d[A]dt=1ak[A]m[B]n-\frac{d[A]}{dt} = \frac{1}{a} k [A]^m [B]^n for reactant consumption, emphasizing that the rate quantifies the speed at which the reaction proceeds. The rate constant kk is a fundamental parameter in the rate equation, representing the intrinsic speed of the reaction under specified conditions and incorporating factors such as , solvent, and catalysts./12:_Kinetics/12.04:_Rate_Laws) It exhibits a strong dependence on , as described by the k=AeEa/RTk = A e^{-E_a / RT}, where AA is the related to , EaE_a is the barrier, RR is the , and TT is the absolute ; higher temperatures exponentially increase kk by providing more molecules with sufficient energy to react. While the rate of reaction measures the observable change in concentrations (e.g., in moles per liter per second), the rate law is the specific equation that mathematically models this rate as a function of concentrations, distinguishing it as an empirical tool rather than a direct measure. Rate equations are derived under key assumptions that differentiate elementary reactions from overall reactions. For an elementary reaction—a single-step process—the rate law can be directly inferred from the stoichiometry of the balanced equation, as the molecularity (number of colliding molecules) determines the order; for instance, a bimolecular elementary step yields a second-order rate law. In contrast, overall reactions, which often involve multiple elementary steps, do not permit direct rate law prediction from the net equation; instead, the observed rate law reflects the slowest (rate-determining) step or a combination of steps, requiring experimental determination to identify the effective orders. This distinction underscores that rate equations for complex mechanisms are phenomenological models, not mechanistic derivations, ensuring they accurately capture kinetic behavior without assuming a single-step pathway.

Role in Chemical Kinetics

The rate equation, foundational to , originated from the work of Cato Maximilian Guldberg and Peter Waage, who in 1864 formulated the , proposing that the rate of a is proportional to the product of the concentrations of the reactants raised to powers equal to their stoichiometric coefficients. This insight shifted the study of chemistry from static equilibria to dynamic processes, establishing rate equations as differential expressions describing how reaction rates depend on species concentrations, thereby enabling quantitative predictions of reaction progress. Rate equations are integrated over time to derive concentration-time profiles, which mathematically express how reactant or product concentrations evolve during a reaction, providing a direct link between kinetic parameters and observable changes. For instance, these integrated forms allow chemists to model the temporal behavior of systems, such as in batch reactions where initial concentrations and rate constants predict the full trajectory of species depletion or formation. In applications, this capability supports reactor design by informing the sizing and operational parameters of continuous systems like reactors, where rate equations determine the volume required for a target conversion based on flow rates and kinetics. Similarly, half-lives—the time for reactant concentration to halve—are derived from these profiles, aiding in forecasting reaction durations and stability assessments without exhaustive simulations. Steady-state approximations further leverage rate equations by assuming negligible concentration changes for intermediates, simplifying the analysis of complex multi-step mechanisms to approximate overall rates. The dependence of rate equations is captured through the rate constant kk, governed by the k=AeEa/RTk = A e^{-E_a / RT}, where EaE_a is the , AA is the , RR is the , and TT is ; higher EaE_a exponentially slows reactions by limiting the fraction of collisions with sufficient energy. Catalysts accelerate reactions by lowering EaE_a or enhancing AA, thus increasing kk without being consumed, as seen in enzymatic processes where stabilization reduces the energy barrier. This relationship underscores the role of rate equations in optimizing catalytic systems for industrial efficiency.

Power Law Rate Equations

General Form and Reaction Order

The power law rate equation provides a mathematical description of the reaction rate for many chemical processes, particularly elementary reactions and those approximating such behavior. For a general reaction involving reactants A, B, and others, the rate is expressed as rate=k[\ceA]m[\ceB]n\text{rate} = k [\ce{A}]^m [\ce{B}]^n \cdots where kk is the rate constant, [\ceA][\ce{A}] and [\ceB][\ce{B}] are the concentrations of the reactants, and mm and nn are the partial reaction orders with respect to A and B, respectively. The overall reaction order is defined as the sum of these exponents, m+n+m + n + \cdots, which indicates the total dependence of the rate on reactant concentrations. This form assumes that the rate is proportional to the concentrations raised to constant powers, a simplification valid for many systems under constant conditions. Reaction order differs fundamentally from , the theoretical number of reactant molecules involved in an elementary step as per . While is an integer (unimolecular, bimolecular, etc.) deduced from the , reaction order is an experimental parameter that may be fractional or zero and does not necessarily match the . For elementary reactions, the reaction order equals the , but complex mechanisms can yield orders that deviate, highlighting the empirical nature of rate laws. The units of the rate constant kk are determined by the overall reaction order nn to ensure dimensional consistency, since the rate has units of concentration per time (typically \ceMs1\ce{M s^{-1}}). For an nnth-order reaction, kk has units of \ceM1ns1\ce{M^{1-n} s^{-1}}, such as \ces1\ce{s^{-1}} for first-order or \ceM1s1\ce{M^{-1} s^{-1}} for second-order processes. This dependency arises directly from the power law structure, where balancing the equation requires kk to compensate for the concentration terms. A simple example is the decomposition reaction \ceA>products\ce{A -> products}, where the rate law simplifies to rate=k[\ceA]m\text{rate} = k [\ce{A}]^m and the overall order is simply mm. The value of mm varies by reaction type—for instance, m=1m = 1 for many unimolecular decompositions or m=2m = 2 for certain bimolecular processes—illustrating how the general form adapts to specific kinetics without altering its foundational structure.

Zero-Order Reactions

In zero-order reactions, the rate of reaction is independent of the concentrations of the reactants, resulting in a constant reaction rate throughout the process. The rate law for such reactions is expressed as rate = k, where k is the rate constant, indicating no dependence on reactant concentration. This form arises as a special case of the power law rate equation when the reaction order is zero, often observed under conditions where the reaction is limited by factors other than reactant availability. To derive the integrated rate law, start with the differential form -d[A]/dt = k. Integrating both sides with respect to time from t = 0 (where [A] = [A]_0) to t (where [A] = [A]) yields [A] = [A]0 - kt. This linear relationship shows that the concentration of the reactant decreases at a steady rate over time. The half-life for a zero-order reaction, the time required for the concentration to halve, is given by t{1/2} = [A]_0 / (2k), which depends on the initial concentration and inversely on the rate constant. Zero-order kinetics commonly occurs in scenarios involving saturation, such as enzyme-catalyzed reactions under the Michaelis-Menten model. When substrate concentration greatly exceeds the Michaelis constant (K_m), the enzyme active sites become fully occupied, making the rate equal to the maximum velocity V_max and independent of further substrate addition, thus zero-order in substrate. Similarly, in heterogeneous catalysis, zero-order behavior is seen in surface reactions where all catalytic sites are saturated with reactants, limiting the rate to the availability of those sites rather than gas-phase concentrations. Graphically, zero-order reactions are identified by plotting concentration [A] versus time t, which produces a straight line with a slope of -k, confirming the constant rate and allowing determination of the rate constant from experimental data.

First-Order Reactions

A first-order reaction is characterized by a rate law in which the reaction rate is directly proportional to the concentration of a single reactant, expressed as
rate=d[\ceA]dt=k[\ceA]\text{rate} = -\frac{d[\ce{A}]}{dt} = k[\ce{A}]
where kk is the rate constant and [\ceA][\ce{A}] is the concentration of reactant A. This form arises for elementary unimolecular processes or under conditions where the rate-determining step involves one species.
To derive the integrated rate law, separate variables and integrate:
[\ceA]0[\ceA]d[\ceA][\ceA]=k0tdt\int_{[\ce{A}]_0}^{[\ce{A}]} \frac{d[\ce{A}]}{[\ce{A}]} = -k \int_0^t dt
yielding
ln[\ceA]=ln[\ceA]0kt\ln[\ce{A}] = \ln[\ce{A}]_0 - kt
or equivalently,
[\ceA]=[\ceA]0ekt.[\ce{A}] = [\ce{A}]_0 e^{-kt}.
This exponential decay describes how the concentration decreases over time. A key property is the constant half-life, t1/2=ln2kt_{1/2} = \frac{\ln 2}{k}, which remains independent of the initial concentration [\ceA]0[\ce{A}]_0, unlike higher-order reactions.
Common examples include , where the rate of disintegration is proportional to the number of undecayed nuclei, following the integrated form precisely. Another is the unimolecular decomposition of gas-phase molecules, such as the thermal of to propene, where the reaction proceeds via an energized intermediate. In multi-reactant systems, behavior can emerge under pseudo- conditions when one reactant is in large excess, though full details are covered elsewhere. Graphically, kinetics is confirmed by plotting ln[\ceA]\ln[\ce{A}] versus time, which yields a straight line with k-k, allowing determination of the rate constant from experimental data. This linear relationship distinguishes it from other orders and facilitates analysis of concentration-time profiles.

Second-Order Reactions

Second-order reactions are those in which the overall reaction rate depends on the concentration of one or more reactants raised to the power of two, corresponding to an overall order of two in the rate equation. These reactions typically involve bimolecular elementary steps, where two reactant molecules collide and react. There are two primary forms: reactions involving two molecules of the same reactant (e.g., 2A → products), with the rate law rate = k [A]^2, or reactions between two different reactants (e.g., A + B → products), with rate = k [A][B]. The integrated rate law for a second-order reaction of the form 2A → products is derived by integrating the differential rate equation, yielding: 1[A]=1[A]0+kt\frac{1}{[A]} = \frac{1}{[A]_0} + kt where [A] is the concentration at time t, [A]_0 is the initial concentration, k is the rate constant, and t is time. This equation shows that a plot of 1/[A] versus t produces a straight line with slope equal to k, providing a graphical method to confirm second-order kinetics and determine the rate constant. For the case of A + B → products with equal initial concentrations ([A]_0 = [B]_0), the integrated form is analogous: 1/[A] = 1/[A]_0 + kt, allowing similar linear plotting of reciprocal concentrations against time. The for a second-order reaction, t_{1/2}, is the time required for the concentration of the reactant to decrease to half its initial value and is given by t_{1/2} = 1 / (k [A]_0). Unlike reactions, the half-life depends inversely on the initial concentration, meaning higher starting concentrations result in shorter half-lives. Representative examples of second-order reactions include the dimerization of (2 C_4H_6 → C_8H_{12}), which follows rate = k [C_4H_6]^2 and is often studied to illustrate hyperbolic concentration decay over time, and certain SN2 reactions, such as the reaction of methyl iodide with hydroxide ion (CH_3I + OH^- → CH_3OH + I^-), which proceeds with rate = k [CH_3I][OH^-].

Fractional and Higher-Order Reactions

Fractional-order reactions occur when the reaction order is a non-integer value, such as 1/2 or 3/2, and these typically result from complex reaction mechanisms that are not elementary steps. These mechanisms often involve multiple sequential or parallel pathways, including where reactive intermediates propagate the process, leading to rate laws that do not yield exponents upon experimental determination. For instance, a 3/2-order dependence has been observed in certain reactions, where the rate is proportional to the of one reactant's concentration combined with a linear term for another, reflecting the influence of surface effects or radical intermediates. Higher-order reactions, defined by an overall order n > 2, are uncommon in due to the low probability of simultaneous multi-molecular collisions required for such elementary steps. Termolecular or higher collisions demand precise alignment and energy transfer among three or more molecules, which is statistically rare compared to unimolecular or bimolecular events. The general integrated rate for an nth-order reaction (n ≠ 1) is derived by separating variables in the -d[A]/dt = k [A]^n, yielding: [A]1n[A0]1n1n=kt\frac{[A]^{1-n} - [A_0]^{1-n}}{1-n} = k t or equivalently, 1[A]n1=1[A0]n1+(n1)kt.\frac{1}{[A]^{n-1}} = \frac{1}{[A_0]^{n-1}} + (n-1) k t. This form allows concentration [A] to be solved as a function of time t, with the rate constant k carrying units of (concentration)^{1-n} time^{-1}. For fractional orders like n = 3/2, the equation simplifies accordingly, though numerical methods may be needed for integration in practice. Negative orders, which imply rate inhibition by increasing reactant concentration, arise in even more intricate mechanisms and are not covered in detail here. To compare fractional and higher-order reactions with the more common integer cases, the following table summarizes key features of integrated rate laws, half-lives, and diagnostic plots for orders 0, 1, 2, and general n (n ≠ 1). Half-life t_{1/2} represents the time for [A] to reach [A_0]/2, and linear plots confirm the order by yielding a straight line with slope related to k. For zero-, first-, and second-order reactions, these expressions are exact; for general n, they extend the pattern but require caution near n = 1, where the form approaches the first-order logarithmic equation via L'Hôpital's rule. Plots for fractional or higher n use the linearized form, often requiring computational fitting for non-integer values.
Order (n)Integrated Rate LawHalf-Life (t_{1/2})Linear Plot (y vs. t)
0[A] = [A_0] - k t[A_0] / (2 k)[A] (slope = -k)
1\ln [A] = \ln [A_0] - k t\ln 2 / k (independent of [A_0])\ln [A] (slope = -k)
21/[A] = 1/[A_0] + k t1 / (k [A_0])1/[A] (slope = k)
n (>2 or fractional, n ≠ 1)1/[A]^{n-1} = 1/[A_0]^{n-1} + (n-1) k t(2^{n-1} - 1) / ((n-1) k [A_0]^{n-1})1/[A]^{n-1} (slope = (n-1) k)
These comparisons highlight how higher or fractional orders lead to more rapidly changing half-lives with initial concentration [A_0] compared to lower orders, emphasizing their sensitivity to conditions in complex systems./12%3A_Kinetics/12.05%3A_Integrated_Rate_Laws)

Pseudo-Order Approximations

In chemical kinetics, pseudo-order approximations simplify the study of multi-reactant rate laws by using a large excess of one or more reactants, rendering their concentrations effectively constant throughout the reaction. This approach reduces the apparent reaction order with respect to the limiting reactant, facilitating easier experimental analysis and integration of the rate equation. These approximations are particularly useful for reactions where direct measurement of multiple changing concentrations is challenging. A common example is the pseudo-first-order approximation applied to second-order reactions of the form → products, with rate = k [A][B]. When reactant B is present in large excess such that [B]_0 ≫ [A]_0 (typically by a factor of 10 or more), the concentration of B remains nearly constant at [B] ≈ [B]_0 during the reaction. The rate law then simplifies to rate = k' [A], where k' = k [B]_0 is the pseudo- rate constant. This transformed equation behaves like a true rate law in A, allowing the use of first-order integrated forms for data analysis, such as ln([A]/[A]_0) = -k' t. The validity of this approximation holds only while the excess condition is maintained, ensuring minimal depletion of B relative to its initial amount. Pseudo-zero-order approximations arise in scenarios where all reactants except one are maintained in large excess, or when mechanistic saturation makes the rate independent of the limiting reactant's concentration. For instance, in reactions following a power-law rate but under conditions where the limiting reactant does not influence the rate due to excess of others, the observed kinetics appear zero-order, with rate = k' (constant). This is common in catalytic or enzymatic systems where the catalyst or sites are fully saturated by excess substrate, leading to a constant rate until depletion occurs. The approximation requires the excess concentrations to vastly exceed stoichiometric needs, often [excess]_0 ≫ 100 × [limiting]_0, to keep the rate invariant over a significant portion of the reaction progress. These approximations find widespread applications in hydrolysis reactions, such as the acid-catalyzed hydrolysis of esters like ethyl acetate (CH_3COOC_2H_5 + H_2O → CH_3COOH + C_2H_5OH), where water is in vast excess (pseudo-first-order in ester). The reaction is monitored spectroscopically, often via UV-visible absorbance changes in the products or unreacted species, allowing real-time tracking of concentration versus time under simplified kinetics. Similarly, in analytical chemistry, the reaction of Fe^{3+} with SCN^- to form the red [Fe(SCN)]^{2+} complex uses excess Fe^{3+} for pseudo-first-order conditions, enabling thiocyanate quantification through colorimetric spectroscopy. Limitations include the approximation's breakdown if the excess reactant depletes significantly (violating [excess] ≫ stoichiometry), potentially leading to non-linear kinetics and erroneous rate constants; thus, experiments must verify constancy of the excess species.

Experimental Determination of Rate Laws

Method of Initial Rates

The method of initial rates is an experimental technique in employed to determine the orders of a reaction with respect to its reactants by measuring the instantaneous rate at the very beginning of the reaction (t ≈ 0) across multiple trials with systematically varied initial concentrations. This approach relies on the power law form of the rate equation, where the initial rate is proportional to the initial concentrations raised to their respective orders. In the procedure, a series of experiments is performed in which the initial concentration of one reactant is varied while keeping the initial concentrations of all other reactants constant, and the initial rate is determined for each set of conditions, often by monitoring the change in concentration of a species (e.g., via ) over a short initial time interval. The reaction order m with respect to the varied reactant A is then calculated using the relation m=log(rate2rate1)log([A]2[A]1),m = \frac{\log\left(\frac{\text{rate}_2}{\text{rate}_1}\right)}{\log\left(\frac{[\mathrm{A}]_2}{[\mathrm{A}]_1}\right)}, where rate1 and rate2 are the measured initial rates corresponding to initial concentrations [A]1 and [A]2, respectively. This process is repeated for each reactant to obtain the full rate law. The advantages of this method include its simplicity, as it circumvents the need to integrate the differential rate equation—a task that becomes mathematically challenging for non-first-order or complex kinetics—and its applicability to systems where analytical integration is impractical or unknown. It provides a direct way to isolate the dependence on each reactant's concentration without complications from time-dependent changes. A key assumption underlying the method is that during the initial measurement period, the concentrations of reactants remain essentially constant, and the buildup of products is negligible, ensuring no reverse reaction or product inhibition interferes with the forward rate. This holds best for irreversible reactions or early stages far from equilibrium. As an illustrative example, consider the hypothetical reaction 2A + B → products, where initial rates are measured for varied [A]0 and [B]0. The following table summarizes typical experimental data:
Experiment[A]0 (M)[B]0 (M)Initial Rate (M/s)
10.100.102.0 × 10−3
20.200.108.0 × 10−3
30.100.204.0 × 10−3
Comparing experiments 1 and 2 (constant [B]0), the order with respect to A is m=log(8.0×1032.0×103)log(0.200.10)=log4log2=2.m = \frac{\log\left(\frac{8.0 \times 10^{-3}}{2.0 \times 10^{-3}}\right)}{\log\left(\frac{0.20}{0.10}\right)} = \frac{\log 4}{\log 2} = 2. Comparing experiments 1 and 3 (constant [A]0), the order with respect to B is n=log(4.0×1032.0×103)log(0.200.10)=log2log2=1.n = \frac{\log\left(\frac{4.0 \times 10^{-3}}{2.0 \times 10^{-3}}\right)}{\log\left(\frac{0.20}{0.10}\right)} = \frac{\log 2}{\log 2} = 1. Thus, the rate law is rate = k [A]2 [B]. Such tabulations and calculations allow straightforward determination of orders in practice.

Integral Method

The integral method involves fitting experimental concentration-time data to the integrated form of a proposed rate law to determine the reaction order and rate constant. This approach assumes a power-law rate equation of the form rate = k [A]^n and integrates it over time, then tests for the best linear fit across the dataset to identify the order n. For integer orders, characteristic plots are constructed: for zero-order reactions, a plot of [A] versus time t is linear with slope equal to -k; for first-order, a plot of \ln [A] versus t is linear with slope -k; and for second-order, a plot of 1/[A] versus t is linear with slope k. The rate constant k is calculated directly from the slope of the linear plot, providing a quantitative measure once the order is confirmed. For reactions suspected to have non-integer or unknown orders, the integral method employs trial-and-error testing of various n values or to minimize the error between experimental and predicted concentrations from the integrated rate law. software, such as that available in tools like Excel or specialized kinetics packages, optimizes both n and k by fitting the full integrated equation to the data, offering a robust way to handle fractional orders without assuming linearity in transformed plots. This technique is particularly useful when the order deviates from simple integers, as seen in some catalytic or complex gas-phase reactions. A key advantage of the method is its utilization of the entire experimental , from initial concentrations through the reaction progress, which enhances statistical reliability compared to methods relying on limited points. Additionally, deviations from linearity in the plots can reveal changes in reaction order over time, such as those due to shifting mechanisms or approaching equilibrium, allowing researchers to identify non-ideal behaviors early. As an illustrative example, consider concentration-time data from the of a reactant A. If plotting \ln [A] versus t yields a straight line, the reaction is confirmed as , with derived from the ; however, if the plot curves concave upward, testing 1/[A] versus t may produce linearity, indicating second-order kinetics and distinguishing the mechanism effectively using the full time course. This process confirms the order and provides without needing multiple initial concentration runs.

Isolation Method

The isolation method, also known as the flooding method, is an experimental approach for determining the reaction order with respect to a specific reactant in multi-reactant systems by minimizing variations in the concentrations of other . In this technique, all reactants except the one under study are introduced in large excess, typically 10 to 1000 times their stoichiometric amounts, ensuring that their concentrations remain nearly constant during the reaction. This simplification transforms the overall rate law into a pseudo-order form dependent only on the isolated reactant's concentration, allowing the use of standard integrated rate laws to identify the order. The process is then repeated sequentially for each reactant to construct the complete rate law. Consider a hypothetical reaction A + B + C → products with the rate law r=k[A]m[B]n[C]p.r = k [\mathrm{A}]^m [\mathrm{B}]^n [\mathrm{C}]^p. To determine the order mm with respect to A, B and C are added in large excess, rendering [B][\mathrm{B}] and [C][\mathrm{C}] effectively constant. The rate law then reduces to r=k[A]m,r = k' [\mathrm{A}]^m, where k=k[B]n[C]pk' = k [\mathrm{B}]^n [\mathrm{C}]^p is the pseudo-rate constant. Monitoring the concentration of A over time and fitting the data to integrated rate equations for different orders (e.g., first-order: ln[A]=kt+ln[A]0\ln[\mathrm{A}] = -k't + \ln[\mathrm{A}]_0) reveals mm. This isolation is performed analogously for B and C by varying their roles. (Frost and Pearson, 1961) The method's primary advantages include its ability to reduce complex kinetics to simpler, well-characterized forms, facilitating straightforward data analysis via graphical or numerical integration, and its applicability to where substrates can be flooded relative to catalysts. It is particularly effective for reactions where direct variation of all concentrations simultaneously is impractical. However, the isolation method has limitations, such as the necessity for high concentrations of excess reactants, which may exceed limits, alter reaction mechanisms, or promote unintended side reactions. Additionally, if the excess is insufficient, the assumption of constant concentrations may fail, leading to inaccurate order determinations.

Complex Rate Laws

Reversible Reactions

In reversible reactions, the net rate is determined by the difference between the forward and reverse reaction rates. For a general reversible process, the net rate rnetr_{\text{net}} is expressed as rnet=kf[reactants]fkr[products]rr_{\text{net}} = k_f [\text{reactants}]_f - k_r [\text{products}]_r, where kfk_f is the forward rate constant, krk_r is the reverse rate constant, and the subscripts denote the concentrations involved in each direction. This form accounts for the opposing processes that characterize equilibrium systems in . The system approaches equilibrium when the net rate becomes zero, such that d[product]dt=0\frac{d[\text{product}]}{dt} = 0. At this point, the forward rate equals the reverse rate, leading to the equilibrium constant Keq=kfkr=[products]eq[reactants]eqK_{\text{eq}} = \frac{k_f}{k_r} = \frac{[\text{products}]_{\text{eq}}}{[\text{reactants}]_{\text{eq}}}. This relationship, derived from the , highlights how kinetic parameters directly relate to . A simple example is the reversible first-order reaction \ceAB\ce{A ⇌ B}, where the rate equation is d[\ceA]dt=k1[\ceA]k1[\ceB]-\frac{d[\ce{A}]}{dt} = k_1 [\ce{A}] - k_{-1} [\ce{B}], with k1k_1 and k1k_{-1} as the forward and reverse rate constants, respectively. Assuming initial conditions [\ceA]0=a[\ce{A}]_0 = a and [\ceB]0=0[\ce{B}]_0 = 0, and using the relation [\ceB]=a[\ceA][\ce{B}] = a - [\ce{A}], the integrated rate law is [\ceA]=[\ceA]eq+([\ceA]0[\ceA]eq)e(k1+k1)t[\ce{A}] = [\ce{A}]_{\text{eq}} + ([\ce{A}]_0 - [\ce{A}]_{\text{eq}}) e^{-(k_1 + k_{-1}) t}, where [\ceA]eq=a1+Keq[\ce{A}]_{\text{eq}} = \frac{a}{1 + K_{\text{eq}}} and Keq=k1k1K_{\text{eq}} = \frac{k_1}{k_{-1}}. This exponential form describes the approach to equilibrium, with the effective rate constant k1+k1k_1 + k_{-1} governing the relaxation time τ=1k1+k1\tau = \frac{1}{k_1 + k_{-1}}. For multi-step reversible reactions involving intermediates, the steady-state approximation is often applied to simplify the rate equations. This assumes that the concentration of each intermediate remains nearly constant, such that its rate of formation equals its rate of consumption: d[intermediate]dt0\frac{d[\text{intermediate}]}{dt} \approx 0. For instance, in a mechanism with a fast reversible step followed by a slow irreversible step, solving the steady-state equation for the intermediate yields a net rate law incorporating both forward and reverse contributions from the reversible step. This approach extends the simple reversible form to complex networks while maintaining focus on the balance of opposing rates.

Consecutive Reactions

Consecutive reactions, or sequential reactions, describe a series of irreversible steps in which the product of an initial reaction becomes the reactant for a subsequent one, exemplified by the scheme A → B → C where B is an intermediate. These systems are common in multi-step processes, and their kinetics are analyzed assuming each elementary step follows rate laws. The differential rate equations for the concentrations are: d[A]dt=k1[A]\frac{d[\mathrm{A}]}{dt} = -k_1 [\mathrm{A}] d[B]dt=k1[A]k2[B]\frac{d[\mathrm{B}]}{dt} = k_1 [\mathrm{A}] - k_2 [\mathrm{B}] d[C]dt=k2[B]\frac{d[\mathrm{C}]}{dt} = k_2 [\mathrm{B}] where k1k_1 and k2k_2 are the rate constants for the respective steps. Integrating these equations with initial conditions [A]0=[A](0)[\mathrm{A}]_0 = [\mathrm{A}](0), [B]0=[C]0=0[\mathrm{B}]_0 = [\mathrm{C}]_0 = 0 yields the time-dependent concentrations: [A](t)=[A]0ek1t[\mathrm{A}](t) = [\mathrm{A}]_0 e^{-k_1 t} [B](t)=[A]0k1k2k1(ek1tek2t)[\mathrm{B}](t) = [\mathrm{A}]_0 \frac{k_1}{k_2 - k_1} \left( e^{-k_1 t} - e^{-k_2 t} \right) These expressions hold for k1k2k_1 \neq k_2. When k1k2k_1 \approx k_2, the intermediate [B] exhibits a pronounced buildup before decaying, with the maximum concentration occurring at tmax=ln(k2/k1)k2k1t_\mathrm{max} = \frac{\ln(k_2 / k_1)}{k_2 - k_1}. Such models apply to chain reactions, as seen in polymerization where sequential propagation steps mimic consecutive kinetics. Concentration-time profiles for consecutive reactions graphically illustrate the dynamics: [A] decays exponentially from its initial value, [B] rises to a peak reflecting the interplay of formation and consumption rates, and [C] sigmoidally approaches [A]_0, highlighting the transient accumulation of the intermediate.

Parallel Reactions

In parallel reactions, a single reactant undergoes competing pathways to form different products simultaneously, leading to a total rate of consumption that is the sum of the individual pathway rates. For two competing irreversible reactions, the total rate is given by rtotal=r1+r2r_{\text{total}} = r_1 + r_2, where r1r_1 and r2r_2 are the rates of the individual paths. The selectivity toward a particular product, defined as the fraction of reactant converted via that pathway, is S1=r1rtotalS_1 = \frac{r_1}{r_{\text{total}}}. This framework is fundamental for predicting product distributions in systems where multiple reaction channels are accessible from the same starting material. A common case involves two parallel first-order reactions, such as the decomposition of reactant A into products B and C: A → B with rate constant k1k_1 and A → C with rate constant k2k_2. The rate equations are d[A]dt=(k1+k2)[A]\frac{d[A]}{dt} = -(k_1 + k_2)[A], d[B]dt=k1[A]\frac{d[B]}{dt} = k_1 [A], and d[C]dt=k2[A]\frac{d[C]}{dt} = k_2 [A], where the total rate constant is ktotal=k1+k2k_{\text{total}} = k_1 + k_2. Integrating these yields the concentration of B as [B]=[A]0k1ktotal(1ektotalt)[B] = [A]_0 \frac{k_1}{k_{\text{total}}} (1 - e^{-k_{\text{total}} t}), with a similar expression for C by substituting k2k_2. The selectivity SB=k1ktotalS_B = \frac{k_1}{k_{\text{total}}} remains constant over time, independent of concentration, allowing straightforward prediction of product yields. When parallel pathways have different orders, such as one (r1=k1[A]r_1 = k_1 [A]) and one second-order (r2=k2[A]2r_2 = k_2 [A]^2), the total rate becomes rtotal=k1[A]+k2[A]2r_{\text{total}} = k_1 [A] + k_2 [A]^2, and selectivity S1=k1[A]k1[A]+k2[A]2=k1k1+k2[A]S_1 = \frac{k_1 [A]}{k_1 [A] + k_2 [A]^2} = \frac{k_1}{k_1 + k_2 [A]} varies with the concentration of A. At high concentrations, the second-order path dominates, favoring the corresponding product, while at low concentrations, the path prevails. This concentration dependence complicates integration, often requiring numerical methods, but highlights how reaction conditions can tune branching ratios. In , parallel reactions are critical for controlling product distribution, as competing pathways can lead to desired versus undesired products; kinetic optimization, such as adjusting concentrations or catalysts, enhances selectivity toward target molecules, as exemplified in processes like selective oxidations or cross-coupling reactions.

Advanced Applications

Stoichiometric Networks

Stoichiometric networks describe complex systems of interconnected chemical reactions where multiple species participate in a web of transformations, often involving cycles or branches that exceed simple linear or parallel pathways. The evolution of species concentrations in such networks is compactly represented using a matrix formulation. Let c\mathbf{c} denote the vector of species concentrations, N\mathbf{N} the stoichiometric matrix whose entries NijN_{ij} are the stoichiometric coefficients (positive for products, negative for reactants) for species ii in reaction jj, and v\mathbf{v} the vector of reaction rates. The are then given by dcdt=Nv,\frac{d\mathbf{c}}{dt} = \mathbf{N} \mathbf{v}, where each component of v\mathbf{v} follows a rate law specific to its reaction, such as power-law or mass-action kinetics. This formulation facilitates analysis of mass balance and network structure, enabling the identification of conserved quantities through the kernel of NT\mathbf{N}^T and the computation of fluxes under steady-state conditions. For networks with short-lived intermediates, the steady-state approximation simplifies the model by assuming that the concentrations of these species remain nearly constant over the timescale of interest, i.e., d[\inter]dt=0\frac{d[\inter]}{dt} = 0 for each intermediate. This leads to a reduced algebraic system: the rows of N\mathbf{N} corresponding to intermediates are set to zero, yielding N\interv=0\mathbf{N}_{\inter} \mathbf{v} = 0, which can be solved for the rates v\mathbf{v} in terms of stable species concentrations. The approximation is valid when intermediates react much faster than stable species, minimizing their transient buildup and allowing focus on overall network fluxes. Validity conditions include separation of timescales, with error bounds derived from singular perturbation theory. A prominent application arises in catalytic cycles, such as , where the steady-state approximation yields the Michaelis-Menten rate law. Consider an E binding substrate S to form complex ES, which then produces product P and regenerates E: the rate of product formation is v=Vmax[S]Km+[S]v = \frac{V_{\max} [S]}{K_m + [S]}, with Vmax=k2[E]0V_{\max} = k_2 [E]_0 the maximum rate and Km=k1+k2k1K_m = \frac{k_{-1} + k_2}{k_1} the Michaelis constant. This derives from setting d[ES]/dt=0d[ES]/dt = 0, balancing formation and decay of ES, and captures saturation behavior in biological networks. For intricate networks defying analytical solutions, numerical methods simulate the full ODE system dcdt=Nv(c)\frac{d\mathbf{c}}{dt} = \mathbf{N} \mathbf{v}(\mathbf{c}) to predict time courses and steady states. Deterministic approaches employ integrators like explicit Runge-Kutta schemes for non-stiff systems or implicit methods (e.g., BDF) for stiff kinetics dominated by disparate timescales, ensuring accurate resolution of network behavior without algebraic reduction. These simulations reveal emergent properties, such as oscillations or , in large-scale models.

Unimolecular Reaction Dynamics

Unimolecular reactions involve the decomposition or isomerization of a single reactant molecule, often appearing first-order in kinetics but requiring collisional activation in gas-phase environments. The foundational Lindemann mechanism, proposed in 1922, describes this process through a two-step sequence: activation of the reactant A by collision to form an energized intermediate A*, followed by its decay to products. The mechanism is A + A ⇌ A* + A with forward and reverse rate constants k1k_1 and k1k_{-1}, and A* → products with rate constant k2k_2. Applying the steady-state approximation to [A*] yields the rate law: rate = k1k2[A]2k1[A]+k2\frac{k_1 k_2 [A]^2}{k_{-1} [A] + k_2}. In the high-pressure limit, where collisional deactivation dominates (k1[A]k2k_{-1} [A] \gg k_2), the rate simplifies to a first-order form: rate ≈ k[A]k_\infty [A], with k=k1k2k1k_\infty = \frac{k_1 k_2}{k_{-1}}, reflecting rapid equilibration of A and A* before reaction. Conversely, in the low-pressure regime (k2k1[A]k_2 \gg k_{-1} [A]), the rate becomes second-order: rate ≈ k1[A]2k_1 [A]^2, as every activation leads to reaction without deactivation. The fall-off regime, bridging these limits, is approximated as rate = k[A]1+kkcoll[M]\frac{k_\infty [A]}{1 + \frac{k_\infty}{k_\text{coll} [M]}}, where [M] is the concentration of bath gas molecules facilitating collisions, and kcollk_\text{coll} is the collision rate constant; this captures pressure-dependent behavior observed in experiments. The Rice-Ramsperger-Kassel-Marcus (RRKM) theory extends the Lindemann framework by incorporating to compute microcanonical rate constants k(E)k(E) for energized molecules with excess E above the reaction threshold E0E_0. In RRKM, k(E)=N(EE0)hρ(E)k(E) = \frac{N^\ddagger (E - E_0)}{h \rho(E)}, where N(EE0)N^\ddagger (E - E_0) is the number of vibrational states accessible at the up to EE0E - E_0, ρ(E)\rho(E) is the of the reactant at E, and h is Planck's constant; this emphasizes that the depends critically on the intramolecular distribution and partitioning between reactant and . Developed in 1952, RRKM provides a quantum mechanical basis for predicting unimolecular rates across energy landscapes. Applications of these rate equations are prominent in gas-phase isomerizations, such as the thermal conversion of to propene, where the reaction follows unimolecular kinetics above ~0.01 atm at 490°C, exhibiting fall-off behavior consistent with the . Modern computational extensions, including simulations, solve time-dependent population balance equations for energy-grained species to model pressure, temperature, and bath gas effects on rate constants, enabling accurate predictions for complex systems like reactions. These simulations integrate RRKM rates with collisional energy transfer models, as reviewed in theoretical kinetics methodologies.

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