Avrami equation

Last updated
The transformation of one phase from another by the growth of nuclei forming randomly in the parent phase Avrami equation.svg
The transformation of one phase from another by the growth of nuclei forming randomly in the parent phase

The Avrami equation describes how solids transform from one phase to another at constant temperature. It can specifically describe the kinetics of crystallisation, can be applied generally to other changes of phase in materials, like chemical reaction rates, and can even be meaningful in analyses of ecological systems. [1]

Contents

The equation is also known as the Johnson–MehlAvramiKolmogorov (JMAK) equation. The equation was first derived by Johnson, Mehl, Avrami and Kolmogorov (in Russian) in a series of articles published in the Journal of Chemical Physics between 1939 and 1941. [2] [3] [4] Moreover, Kolmogorov treated statistically the crystallization of a solid in 1937 (in Russian, Kolmogorov, A. N., Izv. Akad. Nauk. SSSR., 1937, 3, 355).

Transformation kinetics

Typical isothermal transformation plot (top). The transformation can be described using the Avrami equation as a plot of
ln
[?]
ln
[?]
1
1
-
Y
{\displaystyle \ln \ln {\tfrac {1}{1-Y}}}
vs
ln
[?]
t
{\displaystyle \ln {t}}
, yielding a straight line. Avrami transformation plot.svg
Typical isothermal transformation plot (top). The transformation can be described using the Avrami equation as a plot of vs , yielding a straight line.

Transformations are often seen to follow a characteristic s-shaped, or sigmoidal, profile where the transformation rates are low at the beginning and the end of the transformation but rapid in between.

The initial slow rate can be attributed to the time required for a significant number of nuclei of the new phase to form and begin growing. During the intermediate period the transformation is rapid as the nuclei grow into particles and consume the old phase while nuclei continue to form in the remaining parent phase.

Once the transformation approaches completion, there remains little untransformed material for further nucleation, and the production of new particles begins to slow. Additionally, the previously formed particles begin to touch one another, forming a boundary where growth stops.

Derivation

The simplest derivation of the Avrami equation makes a number of significant assumptions and simplifications: [5]

If these conditions are met, then a transformation of into will proceed by the nucleation of new particles at a rate per unit volume, which grow at a rate into spherical particles and only stop growing when they impinge upon each other. During a time interval , nucleation and growth can only take place in untransformed material. However, the problem is more easily solved by applying the concept of an extended volume – the volume of the new phase that would form if the entire sample was still untransformed. During the time interval to the number of nuclei N that appear in a sample of volume V will be given by

where is one of two parameters in this simple model: the nucleation rate per unit volume, which is assumed to be constant. Since growth is isotropic, constant and unhindered by previously transformed material, each nucleus will grow into a sphere of radius , and so the extended volume of due to nuclei appearing in the time interval will be

where is the second of the two parameters in this simple model: the growth velocity of a crystal, which is also assumed constant. The integration of this equation between and will yield the total extended volume that appears in the time interval:

Only a fraction of this extended volume is real; some portion of it lies on previously transformed material and is virtual. Since nucleation occurs randomly, the fraction of the extended volume that forms during each time increment that is real will be proportional to the volume fraction of untransformed . Thus

rearranged

and upon integration:

where Y is the volume fraction of ().

Given the previous equations, this can be reduced to the more familiar form of the Avrami (JMAK) equation, which gives the fraction of transformed material after a hold time at a given temperature:

where , and .

This can be rewritten as

which allows the determination of the constants n and from a plot of vs . If the transformation follows the Avrami equation, this yields a straight line with slope n and intercept .

Final crystallite (domain) size

Crystallization is largely over when reaches values close to 1, which will be at a crystallization time defined by , as then the exponential term in the above expression for will be small. Thus crystallization takes a time of order

i.e., crystallization takes a time that decreases as one over the one-quarter power of the nucleation rate per unit volume, , and one over the three-quarters power of the growth velocity . Typical crystallites grow for some fraction of the crystallization time and so have a linear dimension , or

i.e., the one quarter power of the ratio of the growth velocity to the nucleation rate per unit volume. Thus the size of the final crystals only depends on this ratio, within this model, and as we should expect, fast growth rates and slow nucleation rates result in large crystals. The average volume of the crystallites is of order this typical linear size cubed.

This all assumes an exponent of , which is appropriate for the uniform (homogeneous) nucleation in three dimensions. Thin films, for example, may be effectively two-dimensional, in which case if nucleation is again uniform the exponent . In general, for uniform nucleation and growth, , where is the dimensionality of space in which crystallization occurs.

Interpretation of Avrami constants

Originally, n was held to have an integer value between 1 and 4, which reflected the nature of the transformation in question. In the derivation above, for example, the value of 4 can be said to have contributions from three dimensions of growth and one representing a constant nucleation rate. Alternative derivations exist, where n has a different value. [6]

If the nuclei are preformed, and so all present from the beginning, the transformation is only due to the 3-dimensional growth of the nuclei, and n has a value of 3.

An interesting condition occurs when nucleation occurs on specific sites (such as grain boundaries or impurities) that rapidly saturate soon after the transformation begins. Initially, nucleation may be random, and growth unhindered, leading to high values for n (3 or 4). Once the nucleation sites are consumed, the formation of new particles will cease.

Furthermore, if the distribution of nucleation sites is non-random, then the growth may be restricted to 1 or 2 dimensions. Site saturation may lead to n values of 1, 2 or 3 for surface, edge and point sites respectively. [7]

Applications in biophysics

The Avrami equation was applied in cancer biophysics in two aspects. First aspect is connected with tumor growth and cancer cells kinetics, [8] which can be described by the sigmoidal curve. In this context the Avrami function was discussed as an alternative to the widely used Gompertz curve. In the second aspect the Avrami nucleation and growth theory was used together with multi-hit theory of carcinogenesis to show how the cancer cell is created. The number of oncogenic mutations in cellular DNA can be treated as nucleation particles which can transform whole DNA molecule into cancerous one (neoplastic transformation). This model was applied to clinical data of gastric cancer, and shows that Avrami's constant n is between 4 and 5 which suggest the fractal geometry of carcinogenic dynamics. [9] Similar findings were published for breast and ovarian cancers, where n=5.3. [10]

Multiple Fitting of a Single Dataset (MFSDS)

Multiple Fitting of a Single Data Set. The Avrami equation was used to fit multiple times a dataset published by Min et al. in 2005. MFSDS.png
Multiple Fitting of a Single Data Set. The Avrami equation was used to fit multiple times a dataset published by Min et al. in 2005.

The Avrami equation was used by Ivanov et al. to fit multiple times a dataset generated by another model, the so called αDg to а sequence of the upper values of α, always starting from α=0, in order to generate a sequence of values of the Avrami parameter n. This approach was shown effective for a given experimental dataset [11] , see the plot, and the n values obtained follow the general direction predicted by fitting multiple times the αDg model. [12]

Related Research Articles

In a chemical reaction, chemical equilibrium is the state in which both the reactants and products are present in concentrations which have no further tendency to change with time, so that there is no observable change in the properties of the system. This state results when the forward reaction proceeds at the same rate as the reverse reaction. The reaction rates of the forward and backward reactions are generally not zero, but they are equal. Thus, there are no net changes in the concentrations of the reactants and products. Such a state is known as dynamic equilibrium.

<span class="mw-page-title-main">Radioactive decay</span> Emissions from unstable atomic nuclei

Radioactive decay is the process by which an unstable atomic nucleus loses energy by radiation. A material containing unstable nuclei is considered radioactive. Three of the most common types of decay are alpha, beta, and gamma decay. The weak force is the mechanism that is responsible for beta decay, while the other two are governed by the electromagnetism and nuclear force.

In the special theory of relativity, four-force is a four-vector that replaces the classical force.

<span class="mw-page-title-main">Instanton</span> Solitons in Euclidean spacetime

An instanton is a notion appearing in theoretical and mathematical physics. An instanton is a classical solution to equations of motion with a finite, non-zero action, either in quantum mechanics or in quantum field theory. More precisely, it is a solution to the equations of motion of the classical field theory on a Euclidean spacetime.

In physics, the Hamilton–Jacobi equation, named after William Rowan Hamilton and Carl Gustav Jacob Jacobi, is an alternative formulation of classical mechanics, equivalent to other formulations such as Newton's laws of motion, Lagrangian mechanics and Hamiltonian mechanics.

Compartmental models are a very general modelling technique. They are often applied to the mathematical modelling of infectious diseases. The population is assigned to compartments with labels – for example, S, I, or R,. People may progress between compartments. The order of the labels usually shows the flow patterns between the compartments; for example SEIS means susceptible, exposed, infectious, then susceptible again.

The equilibrium constant of a chemical reaction is the value of its reaction quotient at chemical equilibrium, a state approached by a dynamic chemical system after sufficient time has elapsed at which its composition has no measurable tendency towards further change. For a given set of reaction conditions, the equilibrium constant is independent of the initial analytical concentrations of the reactant and product species in the mixture. Thus, given the initial composition of a system, known equilibrium constant values can be used to determine the composition of the system at equilibrium. However, reaction parameters like temperature, solvent, and ionic strength may all influence the value of the equilibrium constant.

In thermodynamics, an activity coefficient is a factor used to account for deviation of a mixture of chemical substances from ideal behaviour. In an ideal mixture, the microscopic interactions between each pair of chemical species are the same and, as a result, properties of the mixtures can be expressed directly in terms of simple concentrations or partial pressures of the substances present e.g. Raoult's law. Deviations from ideality are accommodated by modifying the concentration by an activity coefficient. Analogously, expressions involving gases can be adjusted for non-ideality by scaling partial pressures by a fugacity coefficient.

The Havriliak–Negami relaxation is an empirical modification of the Debye relaxation model in electromagnetism. Unlike the Debye model, the Havriliak–Negami relaxation accounts for the asymmetry and broadness of the dielectric dispersion curve. The model was first used to describe the dielectric relaxation of some polymers, by adding two exponential parameters to the Debye equation:

In general relativity, a geodesic generalizes the notion of a "straight line" to curved spacetime. Importantly, the world line of a particle free from all external, non-gravitational forces is a particular type of geodesic. In other words, a freely moving or falling particle always moves along a geodesic.

<span class="mw-page-title-main">KMS state</span> Type of state in thermal systems

In the statistical mechanics of quantum mechanical systems and quantum field theory, the properties of a system in thermal equilibrium can be described by a mathematical object called a Kubo–Martin–Schwinger (KMS) state: a state satisfying the KMS condition.

<span class="mw-page-title-main">Recrystallization (metallurgy)</span> Process of forming new, defect-free crystal grains within a material

In materials science, recrystallization is a process by which deformed grains are replaced by a new set of defect-free grains that nucleate and grow until the original grains have been entirely consumed. Recrystallization is usually accompanied by a reduction in the strength and hardness of a material and a simultaneous increase in the ductility. Thus, the process may be introduced as a deliberate step in metals processing or may be an undesirable byproduct of another processing step. The most important industrial uses are softening of metals previously hardened or rendered brittle by cold work, and control of the grain structure in the final product. Recrystallization temperature is typically 0.3–0.4 times the melting point for pure metals and 0.5 times for alloys.

The Mason–Weaver equation describes the sedimentation and diffusion of solutes under a uniform force, usually a gravitational field. Assuming that the gravitational field is aligned in the z direction, the Mason–Weaver equation may be written

In many-body theory, the term Green's function is sometimes used interchangeably with correlation function, but refers specifically to correlators of field operators or creation and annihilation operators.

<span class="mw-page-title-main">Viscoplasticity</span> Theory in continuum mechanics

Viscoplasticity is a theory in continuum mechanics that describes the rate-dependent inelastic behavior of solids. Rate-dependence in this context means that the deformation of the material depends on the rate at which loads are applied. The inelastic behavior that is the subject of viscoplasticity is plastic deformation which means that the material undergoes unrecoverable deformations when a load level is reached. Rate-dependent plasticity is important for transient plasticity calculations. The main difference between rate-independent plastic and viscoplastic material models is that the latter exhibit not only permanent deformations after the application of loads but continue to undergo a creep flow as a function of time under the influence of the applied load.

In thermal quantum field theory, the Matsubara frequency summation is a technique used to simplify calculations involving Euclidean path integrals.

Heat transfer physics describes the kinetics of energy storage, transport, and energy transformation by principal energy carriers: phonons, electrons, fluid particles, and photons. Heat is thermal energy stored in temperature-dependent motion of particles including electrons, atomic nuclei, individual atoms, and molecules. Heat is transferred to and from matter by the principal energy carriers. The state of energy stored within matter, or transported by the carriers, is described by a combination of classical and quantum statistical mechanics. The energy is different made (converted) among various carriers. The heat transfer processes are governed by the rates at which various related physical phenomena occur, such as the rate of particle collisions in classical mechanics. These various states and kinetics determine the heat transfer, i.e., the net rate of energy storage or transport. Governing these process from the atomic level to macroscale are the laws of thermodynamics, including conservation of energy.

Hoffman nucleation theory is a theory developed by John D. Hoffman and coworkers in the 1970s and 80s that attempts to describe the crystallization of a polymer in terms of the kinetics and thermodynamics of polymer surface nucleation. The theory introduces a model where a surface of completely crystalline polymer is created and introduces surface energy parameters to describe the process. Hoffman nucleation theory is more of a starting point for polymer crystallization theory and is better known for its fundamental roles in the Hoffman–Weeks lamellar thickening and Lauritzen–Hoffman growth theory.

Classical nucleation theory (CNT) is the most common theoretical model used to quantitatively study the kinetics of nucleation.

Tau functions are an important ingredient in the modern mathematical theory of integrable systems, and have numerous applications in a variety of other domains. They were originally introduced by Ryogo Hirota in his direct method approach to soliton equations, based on expressing them in an equivalent bilinear form.

References

  1. Avramov, I. (2007). "Kinetics of distribution of infections in networks". Physica A. 379 (2): 615–620. Bibcode:2007PhyA..379..615A. doi:10.1016/j.physa.2007.02.002.
  2. Avrami, M. (1939). "Kinetics of Phase Change. I. General Theory". Journal of Chemical Physics. 7 (12): 1103–1112. Bibcode:1939JChPh...7.1103A. doi: 10.1063/1.1750380 .
  3. Avrami, M. (1940). "Kinetics of Phase Change. II. Transformation-Time Relations for Random Distribution of Nuclei". Journal of Chemical Physics. 8 (2): 212–224. Bibcode:1940JChPh...8..212A. doi:10.1063/1.1750631.
  4. Avrami, M. (1941). "Kinetics of Phase Change. III. Granulation, Phase Change, and Microstructure". Journal of Chemical Physics. 9 (2): 177–184. Bibcode:1941JChPh...9..177A. doi: 10.1063/1.1750872 .
  5. A. K. Jena; M. C. Chaturvedi (1992). Phase Transformations in Materials. Prentice Hall. p. 243. ISBN   0-13-663055-3.
  6. A. K. Jena; M. C. Chaturvedi (1992). Phase Transformations in Materials. Prentice Hall. p. 247. ISBN   0-13-663055-3.
  7. J. W. Cahn (1956). "Transformation kinetics during continuous cooling". Acta Metallurgica. 4 (6): 572–575. doi:10.1016/0001-6160(56)90158-4.
  8. Goris NA, Castañeda AR, Ramirez-Torres EE, Reyes JB, Randez L, Cabrales LE, Montijano JI (2020). "Correspondence between formulations of Avrami and Gompertz equations for untreated tumor growth kinetics". Revista Mexicana de Física. 66 (5): 632–636. doi: 10.31349/RevMexFis.66.632 . S2CID   221755883.
  9. Fornalski K.W.; Dobrzyński L. (2022). "Modeling of single cell cancer transformation using phase transition theory: application of the Avrami equation". Radiation and Environmental Biophysics. 61 (1): 169–175. doi:10.1007/s00411-021-00948-0. PMC   8897338 . PMID   34665303.
  10. Zawadzka A.; Brzozowska B.; Matyjanka A.; Mikula M.; Reszczyńska J.; Tartas A.; Fornalski K.W. (2024). "The Risk Function of Breast and Ovarian Cancers in the Avrami–Dobrzyński Cellular Phase-Transition Model". International Journal of Molecular Sciences. 25 (2): 1352. doi: 10.3390/ijms25021352 . PMC   10816518 . PMID   38279352.
  11. Min, K-H. "Crystallization behaviour of ALD-Ta2O5 thin films: the application of in-situ TEM". Philosophical Magazine. Taylor & Francis.
  12. Ivanov, Vassil. "Modelling crystallization: When the normal growth velocity depends on the supersaturation". Journal of Physics and Chemistry of Solids. Elsevier.