Free Energy Functionals for Efficient Phase Field Crystal Modelingof Structural Phase Transformations

Michael Greenwood,1,2 Nikolas Provatas,2 and Jörg Rottler1

1Department of Physics and Astronomy, University of British Columbia,6224 Agricultural Road Vancouver, British Columbia, V6T 1Z1, Canada

2Department of Materials Science and Engineering, McMaster University,1280 Main Street West, Hamilton, Ontario, L8S 4L7, Canada

(Received 30 December 2009; revised manuscript received 20 June 2010; published 23 July 2010)

The phase field crystal (PFC) method is a promising technique for modeling materials with atomic

resolution on mesoscopic time scales. While numerically more efficient than classical density functional

theory (CDFT), its single mode free energy limits the complexity of structural transformations that can be

simulated. We introduce a new PFC model inspired by CDFT, which uses a systematic construction of

two-particle correlation functions that allows for a broad class of structural transformations. Our approach

considers planar spacings, lattice symmetries, planar atomic densities, and atomic vibrational amplitudes

in the unit cell, and parameterizes temperature and anisotropic surface energies. The power of our

approach is demonstrated by two examples of structural phase transformations.

DOI: 10.1103/PhysRevLett.105.045702 PACS numbers: 64.70.K�, 46.15.�x, 61.50.Ah, 81.10.Aj

Solid-state transformations involve structural changesthat couple atomic-scale elastic and plastic effects withdiffusional processes [1–3]. These phenomena are pres-ently impossible to compute at experimentally relevanttime scales using molecular dynamics simulations. Onthe other hand, mesoscale continuum models wash outmost of the relevant atomic-scale physics that leads toelasticity, plasticity, defect interactions, and grain bound-ary nucleation and migration. Traditional phase field stud-ies of precipitate and ledge growth [3,4] thus introducethese effects phenomenologically. To our knowledge, thereare no phase field models presently available that self-consistently model polycrystalline interactions and elasticand plastic effects at the atomic scale.

Classical density function theory (CDFT) provides aformalism that describes the emergence of crystalline orderfrom a liquid or solid phase through a coarse-graineddensity field [5]. Unfortunately, it requires high spatialresolution and is inefficient for dynamical calculations[6] due to sharp density spikes in the solid phases. Therecently introduced phase field crystal (PFC) model hasbeen gaining widespread recognition as a hybrid methodbetween CDFT and traditional phase field methods. Thisnew formalism captures the essential physics of CDFTwithout having to resolve the sharp atomic density peaks[7–11]. Despite their success, existing PFC free energiesallow for only a limited range of structural transformationsbetween different crystalline states. Moreover, extensionsof the original PFC concept to crystal symmetries such assquare [12,13] and fcc [6,14,15] have been somewhat adhoc and not self-consistently connected to materialproperties.

This Letter proposes an extension of the PFC model bysystematically constructing phenomenological kernelswith energy minima for targeted crystalline states. Our

approach preserves the PFC model’s numerical efficiency,and its utility is demonstrated by dynamically simulatingthe growth of solid phases into a liquid and the nucleationof precipitate phases within a parent phase of differentcrystallographic symmetry. We begin with a free energyfunctional,

�F½nð~rÞ� ¼ �Fid½nð~rÞ� þ�Fex½nð~rÞ�; (1)where �F is the free energy difference with respect to auniform reference density �0 [16], and has contributionsfrom a noninteracting term �Fid and an excess energy�Fex responsible for the formation of structured phases.Equation (1) is expanded around the uniform reference

density using the dimensionless number density nð ~rÞ ¼�ð~rÞ=�o � 1, where �ð ~rÞ is the coarse-grained local den-sity. The ideal contribution to the energy is approximatedby expanding the Helmholtz free energy of an ideal gas,

�Fid ¼ �okBTZ

d~r½1þ nð ~rÞ� ln½1þ nð ~rÞ� � nð ~rÞ

� �okBTZ

d~r

�nð ~rÞ22

� nð ~rÞ3

6þ nð ~rÞ

4

12

�: (2)

The excess energy is expanded to include only secondorder correlations [9,16–18],

�Fex ¼ ��okBT2Z

d~rnð~rÞZ

d~r0½C2ðjr� r0jÞnð~r0Þ�; (3)

where C2ðj ~r� ~r0jÞ plays the role of a two-particle directcorrelation function. The PFC model evolves the di-mensionless number density field nð~rÞ in time using thetypical conserved dissipative dynamics [7], @nð ~rÞ@t ¼Mr2½��F=�nð ~rÞ� þ Anr2� where M is a kinetic mo-bility parameter and conserved noise � with an amplitudeof An is added to facilitate nucleation from metastable

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states [7,19]. Equation (3) is integrated in reciprocal spaceusing a semi-implicit technique [8,11].

Periodic structures emerge in the PFC model by theintroduction of the kernel C2ðkÞ that results in free energyminima corresponding to particular modes in the densityfield. Here we do not aim to construct such kernels fromfirst principles, but rather seek the simplest possible formsthat result in the desired crystal structure. To this end, weexpand the free energy functional about a uniform refer-ence density [18] and choose modes in the correlationfunctions that will create an energy minimum for thedesired structure. The original PFC model by contrastuses only a single mode [7]. Figure 1 shows two examplesof direct pair correlation functions that produce stablesquare (a) and simple cubic (sc) (b) lattices for minimizedfree energies. The functions C2ðkÞ are constructed in re-ciprocal space by combining multiple peaks whose posi-tion, amplitude, and width are determined as follows:

The number and position of peaks in the reciprocal spacecorrelation function is determined by the desired unit cell.In diffraction theory a reciprocal lattice has families ofpeaks derived from the interplanar spacings. For a 2Dsquare lattice, for instance, the unit cell contains twofamilies of planes, f10g and f11g, with spacings �1 and�2 as shown in the inset of Fig. 1(a). For a perfect crystal,there are an infinite number of peaks located at integer

multiples of the wave vector ki ¼ 2�=�i, where i denotesthe plane. For square and cubic lattices, it is sufficient, inour PFC formalism, to keep only the lowest frequencymode for each family of these peaks in the correlationfunction.Temperature enters our correlation function via modu-

lation of the peak heights by a factor e��2k2i =2�i�i , where theeffective temperature � acts as a control parameter. Theform of this term is motivated by the effect of thermalmotion of atoms about their equilibrium positions withamplitude �v, which modulates the scattering intensity

by a Debye-Waller-Factor e��2vk2i =2. The peak heights inthe correlation function are additionally influenced by the(dimensionless) atomic density �i within a plane and thenumber of planes �i in each family. We therefore enterthese effects into the excess energy phenomenologically by

modulating the peaks in C2ðkÞ with a factor exp½� �2k2i

2�i�i�.

For example, in a square lattice the families of f11g andf10g planes each consist of 4 sets of planes [i.e., the f11gfamily contains (11), (�11), (1�1), and (�1 �1 )] and therefore�11 ¼ �10 ¼ 4. The (11) plane has an atomic density�11 ¼ 1=

ffiffiffi2

pand the (10) plane has a density of �10 ¼ 1.

Incorporating both the decay of correlation peak heightsthrough an effective temperature � and the inclusion ofonly the lowest frequency peaks of each family of planes inthe excess energy leads to the broad real-space densitypeaks that give this model its numerical efficiency.The peaks in the reciprocal space correlation function

are represented by Gaussians exp½� ðk�kiÞ22�2i

� of finite width�i rather than the �—peaks of a perfect lattice. Theparameter �i accounts for changes in the free energy dueto interfaces, defects, and strain. Varying �i changes thewidth of a liquid-solid interface, which directly affects thesurface energy [20]. The relationship between the interfacewidth and the peak width in the correlation function is1=�i / Wi as illustrated in Fig. 2. This result can be arrivedat by the inverse Fourier transform ofC2ðkÞ and agrees wellwith the traditional phase field models, which incorporatesurface energy through square gradient terms in the orderparameter.In summary, each family of planes i in the unit cell

contributes a peak to the kernel in the form of C2ðkÞi ¼exp½�ð�2k2i Þ=ð2�i�iÞ� expf�½ðk� kiÞ2�=ð2�2i Þg. To fur-ther simplify the construction, the correlation functionsin this work (Fig. 1) comprise the numerical envelope ofthe superposition of all relevant peaks for the crystalstructure, to avoid shifts in the peak positions and corre-spondingly changes to the stable structure that would resultfrom a simple sum. This provides a general and robustmethod by which to generate desired crystal structures,incorporating temperature dependence through modulationof the correlation peak heights. Through the use of �1 and�2 we can also change the anisotropy of a given crystalstructure.The phase diagram is constructed from the free energy

curves obtained for each bulk phase. Free energy curves

FIG. 1 (color online). (a) Direct pair correlation function for asquare lattice at two effective temperatures (� ¼ 0:82, solid and� ¼ 0:5, dotted, see text). The two peaks in the correlation func-tion each represent one of two planes in the unit cell with inter-planar spacings �1 and �2 (see inset). (b) Correlation functionfor a simple cubic (sc) lattice at two different temperatures. In3D, a cubic lattice is represented by three planes in the unit cell.

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are calculated by an iterative relaxation technique for eachstructure using the kernel for the structure of interest. Forthe liquid state, the energy is calculated by imposing aconstant density field, and the energy per unit volume iscalculated by numerically integrating Eq. (1). For the solidstate, the structures corresponding to the correlation func-tion are fit using a Gaussian density field and then relaxed.For example, for the correlation function of Fig. 1(a),density fields for square and triangular lattices with lattice

spacings of 1 and 2=ffiffiffi3

pare relaxed using the conserved

dynamics to allow density peaks to obtain an amplitudecorresponding to the local minimum energy state. Thisprocess is repeated for a series of mean densities to pro-duce energy-density curves for each phase at a giveneffective temperature � [Fig. 3(b), inset]. The doubletangent construction is performed for many values of �,giving the phase diagrams in Fig. 3(a) for the squarecorrelation function and in Fig. 3(b) for the fcc correlationfunction.

In both 2D and 3D, the phase that possesses the sym-metry of the underlying correlation function emerges atlow temperatures and intermediate densities. As the effec-tive temperature is increased the lower frequency modes ofthe correlation function dominate over the higher fre-quency modes, which changes the particular structurethat minimizes the free energy. For example, the square(fcc) crystal transforms into a triangular (bcc) crystal sincethe triangular (bcc) structure minimizes the energy in thesingle mode approximation. Note that our model alsopredicts transformation of coexisting liquid and solidphases into a new single solid phase at a peritectic pointin both two and three dimensions. This remarkable featureopens an important window into the study of structural

phase transformations. Coexistence between fcc crystalswith the liquid phase is also obtained, as is coexistence ofthe liquid and sc phases using the kernel shown in Fig. 1(b).Our model is applied to two important examples of

solid-state processes using the phase diagram of Fig. 3.The first is the growth of two structurally different latticesin coexistence, initialized in rectangular domains, into aliquid phase as illustrated in the inset of Fig. 3(a). Thesquare phase is oriented such that the f10g planes are incontact with the liquid phase. Since each peak in the two-particle correlation function represents a single family ofplanes, the surface energy of the interface of the squarephase {10}-facet is derived from the width �2 of thesecond peak of the correlation function, while the surfaceenergy of triangular phase facets are derived directly fromthe width �1 of the first peak. Anisotropy of surface energycan be controlled by increasing or decreasing �1 whileholding �2 constant. This effect also extends to the solid-solid surfaces between boundaries of different structure(for example, triangle-square boundaries). The trianglestructure is derived directly from a single mode approxi-mation, therefore the magnitude of the anisotropy is deter-

FIG. 2. Effect of peak width �i in the correlation functions onplanar interface width Wi. Left: Three values of �i and theirresulting interface widths. Top right: Peak shapes correspondingthe interface widths to the left. Bottom right: Dependence ofsimulated interface width on the correlation peak width (seetext).

FIG. 3. (a) Phase diagram for a square lattice correlationfunction showing coexistence between liquid, solid, and trian-gular phases. The inset contains stripes of square and triangularlattices in a liquid phase quenched to a temperature � ¼ 0:79.The square phase density was initialized to nsq ¼ 0:067 and thetriangular phase density to ntri ¼ 0:076. The mean density of thesystem is set to �n ¼ 0:07 and the surface energy parameters are�1 ¼

ffiffiffi2

pand �2 ¼ 1. (b) Phase diagram for a fcc correlation

function. The insets show the peritectic point and the energycurves for the liquid, fcc and bcc states at � ¼ 0:06.

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mined strictly by the underlying structure. Small changesin the strength of the anisotropy lead to small changes inthe angle of the solid liquid interfaces at vertices betweenthe three phases.

The second application of interest is the nucleation of astructural phase by a quench into the second phase regionof the phase diagram. To illustrative this, the simple 2Dcase of square-triangle structural transformations is shownhere. A liquid with a homogeneous density field isquenched into the triangular region of the phase diagram[point A on the quench path in Fig. 3(a)]. Small amplitudenoise facilitates the nucleation of randomly oriented trian-gular phase seeds in the liquid phase. These seeds grow,impinge and coarsen over time. A small grain is illustratedin Fig. 4(a). After the triangular grains undergo somecoarsening, the material is quenched into the square por-tion of the phase diagram (point B). A thermodynamicdriving force leads to the nucleation, growth, and coarsen-ing of the square phase. The nucleation events occur atvertex positions in the triangular grain structures, as ob-served in experiments [1]. The driving force for the trans-formation is greatest at these positions and can overcomethe nucleation barrier. Two such nucleation points areshown in Fig. 4(b). The orientation of a nucleus andcoherency strains can inhibit the growth of the new phasethat precipitates, eventually to be dominated by another

more favorable precipitate. This effect is illustrated inpanels (c) and (d) of Fig. 4. These results demonstratethat our approach is capable of modeling the distributionof square or fcc precipitate orientations, an importantphenomenon that can be compared to experiments.We introduced new PFC free energy functionals for

efficient numerical study of solid-state transformations.In contrast to earlier work [13], we find that two-pointcorrelations are sufficient to generate stable cubic lattices,and higher order terms in the expansion of�Fex can still beneglected. The correlation functions are systematicallybuilt up from fundamental principles and desired crystallo-graphic properties of phases of interest at a finite tempera-ture. Our approach can model peritectic transitions as wellas the nucleation and growth of second-phase precipitateswith different crystalline structures. Our model can bevalidated against numerous experiments, as well as MDsimulations of triple junctions.This work has been supported by the Natural Science

and Engineering Research Council of Canada (NSERC).

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FIG. 4 (color online). 2D nucleation from triangles to squareswith noise amplitude of An ¼ 0:01 (a) A liquid with density �n ¼0:09 is quenched into the triangular region of the phase diagram(� ¼ 0:82), marked (A) in Fig. 3(a), produces grains withtriangular symmetry. (b)–(d) A further quench into the squareportion of the phase diagram (� ¼ 0:6), marked (B) in Fig. 3(a),illustrating the nucleation and subsequent growth of squaregrains at the vertices of the triangular grains.

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