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Nucleation
Nucleation
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In thermodynamics, nucleation is the first step in the formation of either a new thermodynamic phase or structure via self-assembly or self-organization within a substance or mixture. Nucleation is typically defined to be the process that determines how long an observer has to wait before the new phase or self-organized structure appears. For example, if a volume of water is cooled (at atmospheric pressure) significantly below 0 °C, it will tend to freeze into ice, but volumes of water cooled only a few degrees below 0 °C often stay completely free of ice for long periods (supercooling). At these conditions, nucleation of ice is either slow or does not occur at all. However, at lower temperatures nucleation is fast, and ice crystals appear after little or no delay.[1][2]

Nucleation is a common mechanism which generates first-order phase transitions, and it is the start of the process of forming a new thermodynamic phase. In contrast, new phases at continuous phase transitions start to form immediately.

Nucleation is often very sensitive to impurities in the system. These impurities may be too small to be seen by the naked eye, but still can control the rate of nucleation. Because of this, it is often important to distinguish between heterogeneous nucleation and homogeneous nucleation. Heterogeneous nucleation occurs at nucleation sites on surfaces in the system.[1] Homogeneous nucleation occurs away from a surface.

Characteristics

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Nucleation at a surface (black) in the 2D Ising model.[3] Up spins (particles in lattice-gas terminology) shown in red, down spins shown in white.

Nucleation is usually a stochastic (random) process, so even in two identical systems nucleation will occur at different times.[1][2][3][4] A common mechanism is illustrated in the animation to the right. This shows nucleation of a new phase (shown in red) in an existing phase (white). In the existing phase microscopic fluctuations of the red phase appear and decay continuously, until an unusually large fluctuation of the new red phase is so large it is more favourable for it to grow than to shrink back to nothing. This nucleus of the red phase then grows and converts the system to this phase. The standard theory that describes this behaviour for the nucleation of a new thermodynamic phase is called classical nucleation theory. However, the CNT fails in describing experimental results of vapour to liquid nucleation even for model substances like argon by several orders of magnitude.[5]

For nucleation of a new thermodynamic phase, such as the formation of ice in water below 0 °C, if the system is not evolving with time and nucleation occurs in one step, then the probability that nucleation has not occurred should undergo exponential decay. This is seen for example in the nucleation of ice in supercooled small water droplets.[6] The decay rate of the exponential gives the nucleation rate. Classical nucleation theory is a widely used approximate theory for estimating these rates, and how they vary with variables such as temperature. It correctly predicts that the time you have to wait for nucleation decreases extremely rapidly when supersaturated.[1][2][4]

It is not just new phases such as liquids and crystals that form via nucleation followed by growth. The self-assembly process that forms objects like the amyloid aggregates associated with Alzheimer's disease also starts with nucleation.[7] Energy consuming self-organising systems such as the microtubules in cells also show nucleation and growth.

Heterogeneous nucleation often dominates homogeneous nucleation

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Three nuclei on a surface, illustrating decreasing contact angles. The contact angle the nucleus surface makes with the solid horizontal surface decreases from left to right. The surface area of the nucleus decreases as the contact angle decreases. This geometrical effect reduces the barrier in classical nucleation theory and hence results in faster nucleation on surfaces with smaller contact angles. Also, if instead of the surface being flat it curves towards fluid, then this also reduces the interfacial area and so the nucleation barrier.

Heterogeneous nucleation, nucleation with the nucleus at a surface, is much more common than homogeneous nucleation.[1][3] For example, in the nucleation of ice from supercooled water droplets, purifying the water to remove all or almost all impurities results in water droplets that freeze below around −35 °C,[1][3][6] whereas water that contains impurities may freeze at −5 °C or warmer.[1]

This observation that heterogeneous nucleation can occur when the rate of homogeneous nucleation is essentially zero, is often understood using classical nucleation theory. This predicts that the nucleation slows exponentially with the height of a free energy barrier ΔG*. This barrier comes from the free energy penalty of forming the surface of the growing nucleus [8]. For homogeneous nucleation the nucleus is approximated by a sphere, but as we can see in the schematic of macroscopic droplets to the right, droplets on surfaces are not complete spheres and so the area of the interface between the droplet and the surrounding fluid is less than a sphere's . This reduction in surface area of the nucleus reduces the height of the barrier to nucleation and so speeds nucleation up exponentially.[2]

Nucleation can also start at the surface of a liquid. For example, computer simulations of gold nanoparticles show that the crystal phase sometimes nucleates at the liquid-gold surface.[9]

Computer simulation studies of simple models

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Classical nucleation theory makes a number of assumptions, for example it treats a microscopic nucleus as if it is a macroscopic droplet with a well-defined surface whose free energy is estimated using an equilibrium property: the interfacial tension σ. For a nucleus that may be only of order ten molecules across it is not always clear that we can treat something so small as a volume plus a surface. Also nucleation is an inherently out of thermodynamic equilibrium phenomenon so it is not always obvious that its rate can be estimated using equilibrium properties.

However, modern computers are powerful enough to calculate essentially exact nucleation rates for simple models. These have been compared with the classical theory, for example for the case of nucleation of the crystal phase in the model of hard spheres. This is a model of perfectly hard spheres in thermal motion, and is a simple model of some colloids. For the crystallization of hard spheres the classical theory is a very reasonable approximate theory.[10] So for the simple models we can study, classical nucleation theory works quite well, but we do not know if it works equally well for (say) complex molecules crystallising out of solution.

The spinodal region

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Phase-transition processes can also be explained in terms of spinodal decomposition, where phase separation is delayed until the system enters the unstable region where a small perturbation in composition leads to a decrease in energy and, thus, spontaneous growth of the perturbation.[11] This region of a phase diagram is known as the spinodal region and the phase separation process is known as spinodal decomposition and may be governed by the Cahn–Hilliard equation.

The nucleation of crystals

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In many cases, liquids and solutions can be cooled down or concentrated up to conditions where the liquid or solution is significantly less thermodynamically stable than the crystal, but where no crystals will form for minutes, hours, weeks or longer; this process is called supercooling. Nucleation of the crystal is then being prevented by a substantial barrier. This has consequences, for example cold high altitude clouds may contain large numbers of small liquid water droplets that are far below 0 °C.

In small volumes, such as in small droplets, only one nucleation event may be needed for crystallisation. In these small volumes, the time until the first crystal appears is usually defined to be the nucleation time. Calcium carbonate crystal nucleation depends not only on degree of supersaturation but also the ratio of calcium to carbonate ions in aqueous solutions.[12] In larger volumes many nucleation events will occur. A simple model for crystallisation in that case, that combines nucleation and growth is the KJMA or Avrami model.

When sugar is supersaturated in water, nucleation will occur, allowing sugar molecules to stick together and form large crystal structures.

Although the existing theories including the classical nucleation theory explain well the steady nucleation state when the crystal nucleation rate is not time dependent, the initial non-steady state transient nucleation,[13] and even more mysterious incubation period, require more attention of the scientific community. Chemical ordering of the undercooling liquid prior to crystal nucleation was suggested to be responsible for that[14] feature by reducing the energy barrier for nucleation.[15]

Primary and secondary nucleation

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The time until the appearance of the first crystal is also called primary nucleation time, to distinguish it from secondary nucleation times. Primary here refers to the first nucleus to form, while secondary nuclei are crystal nuclei produced from a preexisting crystal. Primary nucleation describes the transition to a new phase that does not rely on the new phase already being present, either because it is the very first nucleus of that phase to form, or because the nucleus forms far from any pre-existing piece of the new phase. Particularly in the study of crystallisation, secondary nucleation can be important. This is the formation of nuclei of a new crystal directly caused by pre-existing crystals.[16]

For example, if the crystals are in a solution and the system is subject to shearing forces, small crystal nuclei could be sheared off a growing crystal, thus increasing the number of crystals in the system. So both primary and secondary nucleation increase the number of crystals in the system but their mechanisms are very different, and secondary nucleation relies on crystals already being present.

Experimental observations on the nucleation times for the crystallisation of small volumes

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It is typically difficult to experimentally study the nucleation of crystals. The nucleus is microscopic, and thus too small to be directly observed. In large liquid volumes there are typically multiple nucleation events, and it is difficult to disentangle the effects of nucleation from those of growth of the nucleated phase. These problems can be overcome by working with small droplets. As nucleation is stochastic, many droplets are needed so that statistics for the nucleation events can be obtained.

The black triangles are the fraction of a large set of small supercooled liquid tin droplets that are still liquid, i.e., where the crystal state has not nucleated, as a function of time. The data are from Pound and La Mer (1952). The red curve is a fit of a function of the Gompertz form to these data.

To the right is shown an example set of nucleation data. It is for the nucleation at constant temperature and hence supersaturation of the crystal phase in small droplets of supercooled liquid tin; this is the work of Pound and La Mer.[17]

Nucleation occurs in different droplets at different times, hence the fraction is not a simple step function that drops sharply from one to zero at one particular time. The red curve is a fit of a Gompertz function to the data. This is a simplified version of the model Pound and La Mer used to model their data.[17] The model assumes that nucleation occurs due to impurity particles in the liquid tin droplets, and it makes the simplifying assumption that all impurity particles produce nucleation at the same rate. It also assumes that these particles are Poisson distributed among the liquid tin droplets. The fit values are that the nucleation rate due to a single impurity particle is 0.02/s, and the average number of impurity particles per droplet is 1.2. Note that about 30% of the tin droplets never freeze; the data plateaus at a fraction of about 0.3. Within the model this is assumed to be because, by chance, these droplets do not have even one impurity particle and so there is no heterogeneous nucleation. Homogeneous nucleation is assumed to be negligible on the timescale of this experiment. The remaining droplets freeze in a stochastic way, at rates 0.02/s if they have one impurity particle, 0.04/s if they have two, and so on.

These data are just one example, but they illustrate common features of the nucleation of crystals in that there is clear evidence for heterogeneous nucleation, and that nucleation is clearly stochastic.

Ice

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The freezing of small water droplets to ice is an important process, particularly in the formation and dynamics of clouds.[1] Water (at atmospheric pressure) does not freeze at 0 °C, but rather at temperatures that tend to decrease as the volume of the water decreases and as the concentration of dissolved chemicals in the water increases.[1]

Survival curve for water droplets 34.5 μm in diameter. Blue circles are data, and the red curve is a fit of a Gumbel distribution.

Thus small droplets of water, as found in clouds, may remain liquid far below 0 °C.

An example of experimental data on the freezing of small water droplets is shown at the right. The plot shows the fraction of a large set of water droplets, that are still liquid water, i.e., have not yet frozen, as a function of temperature. Note that the highest temperature at which any of the droplets freezes is close to -19 °C, while the last droplet to freeze does so at almost -35 °C.[18]

Examples

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Nucleation of fluids (gases and liquids)

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Nucleation of carbon dioxide bubbles around a finger
  • Clouds form when wet air cools (often because the air rises) and many small water droplets nucleate from the supersaturated air.[1] The amount of water vapour that air can carry decreases with lower temperatures. The excess vapor begins to nucleate and to form small water droplets which form a cloud. Nucleation of the droplets of liquid water is heterogeneous, occurring on particles referred to as cloud condensation nuclei. Cloud seeding is the process of adding artificial condensation nuclei to quicken the formation of clouds.
  • Bubbles of carbon dioxide nucleate shortly after the pressure is released from a container of carbonated liquid.
  • Nucleation in boiling can occur in the bulk liquid if the pressure is reduced so that the liquid becomes superheated with respect to the pressure-dependent boiling point. More often, nucleation occurs on the heating surface, at nucleation sites. Typically, nucleation sites are tiny crevices where free gas-liquid surface is maintained or spots on the heating surface with lower wetting properties. Substantial superheating of a liquid can be achieved after the liquid is de-gassed and if the heating surfaces are clean, smooth and made of materials well wetted by the liquid.
  • Some champagne stirrers operate by providing many nucleation sites via high surface-area and sharp corners, speeding the release of bubbles and removing carbonation from the wine.
  • The Diet Coke and Mentos eruption offers another example. The surface of Mentos candy provides nucleation sites for the formation of carbon-dioxide bubbles from carbonated soda.
  • Both the bubble chamber and the cloud chamber rely on nucleation, of bubbles and droplets, respectively.

Nucleation of crystals

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  • The most common crystallisation process on Earth is the formation of ice. Liquid water does not freeze at 0 °C unless there is ice already present; cooling significantly below 0 °C is required to nucleate ice and for the water to freeze. For example, small droplets of very pure water can remain liquid down to below -30 °C although ice is the stable state below 0 °C.[1]
  • Many of the materials we make and use are crystalline, but are made from liquids, e.g. crystalline iron made from liquid iron cast into a mold, so the nucleation of crystalline materials is widely studied in industry.[19] It is used heavily in the chemical industry for cases such as in the preparation of metallic ultradispersed powders that can serve as catalysts. For example, platinum deposited onto TiO2 nanoparticles catalyses the decomposition of water.[20] It is an important factor in the semiconductor industry, as the band gap energy in semiconductors is influenced by the size of nanoclusters.[21]

Nucleation in solids

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In addition to the nucleation and growth of crystals e.g. in non-crystalline glasses, the nucleation and growth of impurity precipitates in crystals at, and between, grain boundaries is quite important industrially. For example in metals solid-state nucleation and precipitate growth plays an important role e.g. in modifying mechanical properties like ductility, while in semiconductors it plays an important role e.g. in trapping impurities during integrated circuit manufacture.[22]

References

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Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
Nucleation is the initial process in phase transitions where small clusters of atoms, ions, or molecules aggregate to form stable nuclei capable of growing into a new thermodynamic phase, such as crystals from a solution or vapor, droplets in , or bubbles in . This phenomenon occurs in supersaturated, supercooled, or compressed systems and is governed by the balance between the bulk free energy gain driving and the surface free energy penalty of creating an interface. Nucleation marks the onset of spontaneous growth, distinguishing it from mere fluctuations, and is fundamental to processes in physics, chemistry, and . There are two primary types of nucleation: homogeneous, which arises uniformly within the bulk of a pure phase without external aids, requiring significant to overcome a high free energy barrier; and heterogeneous, which is facilitated by impurities, surfaces, or container walls that lower the barrier, making it the dominant mechanism in most practical scenarios. In homogeneous nucleation, the rate depends exponentially on the level and temperature, as clusters must reach a critical size beyond which growth is favored over dissolution. Heterogeneous nucleation, by contrast, reduces the effective interfacial , allowing initiation at lower driving forces and influencing the sites and orientation of the resulting phase. The theoretical foundation of nucleation is provided by , which models the process as a thermally activated event where the free energy of cluster formation, ΔG, combines a negative volume term proportional to the difference (Δμ) and a positive surface term involving interfacial tension (γ). Formulated in by and Döring based on earlier ideas from Gibbs, CNT predicts a maximum free energy barrier ΔG* at the critical nucleus radius r*, given approximately by ΔG* = (16πγ³)/(3(Δμ)²) for spherical nuclei in three dimensions, leading to a nucleation rate J ≈ exp(-ΔG*/kT). While CNT captures qualitative trends, it often overestimates rates due to assumptions like the capillary approximation and has been refined by observations of multistep pathways involving intermediate dense phases. Nucleation plays a pivotal role in diverse applications, from controlling crystal size and polymorphism in to influencing grain structure in and ice formation in atmospheric clouds. In materials processing, manipulating nucleation via additives or shear can tailor microstructures for enhanced properties, while in and , it governs phenomena like and . Understanding and controlling nucleation remains a challenge, driving ongoing into non-classical mechanisms and nanoscale effects.

Fundamentals

Definition and Importance

Nucleation is the process by which a new thermodynamic phase or structure forms within a phase through the aggregation of molecules or atoms into clusters, or embryos, that surpass a critical size and become stable nuclei capable of further growth. This phenomenon is particularly relevant to phase transitions, where thermodynamic properties such as , , and exhibit discontinuous changes at the transition point, in contrast to continuous, or second-order, phase transitions that involve gradual variations without or abrupt shifts./04:_Phase_Transitions/4.02:_Continuous_phase_transitions) The foundational understanding of nucleation emerged from the work of J. Willard Gibbs, who in 1876–1878 developed the thermodynamic framework for heterogeneous equilibria, elucidating how new phases arise under conditions of or in systems like fluids of varying density. Gibbs' analysis highlighted the energy barriers to phase formation, setting the stage for later models such as . Nucleation is pivotal across scientific and industrial domains, governing the initiation of in to control drug , polymorphism, and ; influencing and formation in atmospheric processes that drive patterns and development; and directing solidification in to refine grain structures that enhance material strength and . These roles underscore nucleation's impact on everything from material properties to large-scale environmental phenomena.

Thermodynamic Principles

Nucleation is driven by the thermodynamic tendency of a system to minimize its free energy by transitioning from a metastable phase to a more stable one, with the driving force quantified by the difference in between the and emerging phases. This difference, denoted as Δμ, arises from and is expressed as Δμ = kT \ln S, where is the , is the , and S is the ratio, typically defined as the ratio of the actual concentration (or activity) to the equilibrium saturation value. For S > 1, the system is supersaturated, providing the energetic impetus for , such as from solution or from vapor. The total change associated with forming a cluster of the new phase balances two competing contributions: a favorable bulk term and an unfavorable surface term. The bulk free energy gain per unit volume, ΔG_v, is negative and proportional to the chemical potential difference, given by ΔG_v = -Δμ / v_m, where v_m is the molecular volume in the new phase; this term scales with the cluster volume V as -|ΔG_v| V. Opposing this is the positive interfacial energy penalty due to the creation of a new interface, γ A, where γ is the interfacial free energy per unit area and A is the surface area of the cluster. The net free energy change is thus ΔG = -|ΔG_v| V + γ A. For a spherical cluster, this leads to the concept of a r^, below which clusters are unstable and dissolve, while those above r^ grow spontaneously. The is derived by maximizing ΔG with respect to r, yielding r^* = 2γ / |ΔG_v|. At this size, the bulk driving force exactly balances the surface tension penalty, marking the in the free energy landscape. The magnitude of ΔG_v, and thus the driving force, is modulated by and , which influence the degree of and the phase equilibrium. Lowering typically increases in solutions by reducing , thereby enhancing |ΔG_v|, while can shift the chemical potential difference through changes in the volume term in the , as per the relation Δμ = ∫ ΔV dP at constant T. These external parameters thus control the thermodynamic feasibility of nucleation across diverse systems, from atmospheric to materials processing.

Classical Nucleation Theory

Free Energy Barrier

In classical nucleation theory, the formation of a new phase within a metastable parent phase involves overcoming a free energy barrier associated with the creation of a small cluster or nucleus. The total change in , ΔG, for forming a spherical nucleus of rr in three dimensions is given by the balance between the bulk free energy gain and the interfacial energy penalty: ΔG(r)=43πr3ΔGv+4πr2γ\Delta G(r) = -\frac{4}{3} \pi r^3 |\Delta G_v| + 4 \pi r^2 \gamma where ΔGv|\Delta G_v| is the magnitude of the volumetric free energy difference driving the phase transformation (positive for supersaturation or undercooling), and γ\gamma is the isotropic interfacial energy per unit area between the nucleus and the parent phase. To find the critical nucleus size, ΔG(r)\Delta G(r) is maximized by taking the derivative with respect to rr and setting it to zero, yielding the critical radius r=2γΔGvr^* = \frac{2 \gamma}{|\Delta G_v|}. Substituting this back into the expression for ΔG(r)\Delta G(r) gives the height of the free energy barrier, ΔG\Delta G^*: ΔG=16πγ33ΔGv2\Delta G^* = \frac{16 \pi \gamma^3}{3 |\Delta G_v|^2} This barrier represents the maximum free energy required to form a stable nucleus; clusters smaller than rr^* tend to dissolve, while those larger grow spontaneously. The derivation relies on key assumptions, including isotropic interfacial energy γ\gamma (independent of orientation) and the capillary approximation, which treats the nucleus as having bulk-like properties inside a sharp interface, valid for sufficiently small clusters where curvature effects dominate. These assumptions stem from thermodynamic principles governing phase equilibria, where ΔGv\Delta G_v arises from the chemical potential difference between phases, and γ\gamma from the excess free energy at the interface. The implications of ΔG\Delta G^* are profound for phase formation: the probability of successful nucleation events exhibits an exponential dependence on the barrier height, roughly exp(ΔG/kBT)\exp(-\Delta G^* / k_B T), where kBk_B is Boltzmann's constant and TT is temperature, explaining the rarity of nucleation in mildly supersaturated systems. Moreover, ΔG\Delta G^* decreases inversely with the square of supersaturation (via increasing ΔGv|\Delta G_v|), enabling control of nucleation through driving force adjustments, as seen in processes like crystallization or condensation.

Nucleation Rate Expression

In classical nucleation theory, the steady-state nucleation rate JJ, which quantifies the number of critical nuclei formed per unit volume per unit time, is derived from the balance between attachment and detachment rates of monomers to clusters at the critical size, as formulated by Becker and Döring. This rate incorporates the free energy barrier ΔG\Delta G^* from the preceding thermodynamic considerations and is expressed as J=ZβNexp(ΔGkBT),J = Z \beta^* N \exp\left(-\frac{\Delta G^*}{k_B T}\right), where ZZ is the Zeldovich factor accounting for fluctuations around the critical cluster size, β\beta^* is the attachment rate of monomers to the critical cluster, NN is the concentration of monomers (or single molecules) in the parent phase, kBk_B is Boltzmann's constant, and TT is the absolute temperature. This expression shifts the focus from the static free energy barrier to the kinetic process of forming stable nuclei, predicting rates that are highly sensitive to the exponential term. The Zeldovich factor ZZ corrects for the likelihood that a cluster reaching the critical size nn^* (in terms of number of molecules) will proceed to supercritical growth rather than dissolve due to , and it is given by Z=Δμ6πnkBT,Z = \sqrt{\frac{ |\Delta \mu| }{ 6 \pi n^{*} k_B T }},
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