INTRODUCTIONThe patterns, colors, and shapes of crystals are as beautifulas they are challenging to understand. And like the patternsof many star clusters, the general developmental historyproducing igneous textural patterns seems, at first thought,so very obvious. Indeed, at one level this may be so formany rocks. The magma simply seems to have cooled andcrystallized into scattered discrete grains that have crowdedinto one another due either to a massive flood of nucleationand limited growth or to limited nucleation and prolongedgrowth, however slow, causing impingement betweenneighboring crystals. This is an easy conclusion, reached forover a century by geologists pondering the extremely fine-grained chilled margins of sills and dikes. Ringing under thestroke of a hammer, these fine-grained rocks are almost likeceramics. The crystals are almost too small to see with amicroscope. But just as with snow crystals (Nakaya 1954;Libbrecht 2007), it may be much less than obvious howcrystals nucleate and grow in magma to generate familiartextures. Yet it is critical to understand every nuance ofigneous textures because contained in these textures, in away perhaps loosely akin to Egyptian hieroglyphics, is theintimate history of the magma. The history is both local,reflecting the final cooling event, and global, relating thegeneration at depth, the rigors of transport, and the tem-

porary storage of the magma. Atone extreme, all the constituentcrystals of a hand sample may beindigenous, having nucleated andgrown from a single cooling eventduring transport, emplacement, oreruption in a clean, simply-generatedmelt. At the other extreme, all theconstituent crystals may be exoge-nous. In this case, each crystal has anexotic history: it may have nucleatedin one magma and grown over aprolonged period, during which itwas transported over a tortuouspath in a composite magma, madeup of pieces of magmas from sev-eral source materials and contami-nated by avalanching wall rockand accidental infusions of mag-mas alien to the principal eventitself. We are coming to realize thatcombinations of these extremes are

more common than not. And above all, it is clear that a vast,detailed record of magmatic history is locked in the texturesof igneous rocks. This is much more than a simple record ofthe nucleation and growth of individual crystals—it is animprint of the full dynamic history. Moreover, not only docrystals forming everyday textures have storied pasts, thefinal textures of even some of the fastest-cooled rocks maybe very different from what they started out as in the earlystages of nucleation and growth. And the process of crystalgrowth itself may be unlike anything we commonly imagine.

IGNEOUS WORDSWith so much possibility for variety, it is startling that thereare markedly distinct classes and types of crystallizationuniquely characteristic of certain styles of magmatism.Subtle, systematic differences in magma composition andmode of emplacement and eruption seem, remarkably, tobe reflected in the final rock texture. We have no shortageof words to describe igneous textures (e.g. Williams et al.1954). Textural descriptions encompass three things: degreeof crystallinity, grain size, and fabric (geometrical relation-ships among the constituent minerals). The first two arefairly straightforward; it is the third that holds the mystery.Besides simply identifying the kinds of crystals present,which most often reflect the chemical composition andconditions of crystallization, some words relate to the geneticheritage of crystals, and buried in the meaning of thesewords are inherent physical processes. We want to knowthe words and, especially, the processes behind the words.

In volcanic rocks, where arrested textural development andperhaps the kinetic history are more obvious, the overalltexture and the distinction between bigger crystals and the

E L E M E N T S , V O L . 3 , P P . 2 4 7 – 2 5 2 AUGUST 2007

Taber G. Hersum1 and Bruce D. Marsh2

1 Lamont-Doherty Earth ObservatoryColumbia UniversityNew York, NY 10025, USAE-mail: hersum@ldeo.columbia.edu

2 M.K. Blaustein Dept. Earth & Planetary ScienceThe Johns Hopkins UniversityBaltimore, MD 21218, USAE-mail: bmarsh@jhu.edu

Igneous Textures: On theKinetics behind the Words

247

That igneous textures can be collectively described, classified, andrelated to magma composition, style of emplacement, and spatialposition speaks deeply to the existence of a specific set of fundamental

kinetic processes controlling all magma crystallization. Textures record magmalife history, telling the most recent, local conditions of cooling and also wherethe magma has been. Yet it is largely a mystery how silicate melts crystallize,how they become what they are, and, especially, how the final texture relatesto the early transient textures more closely linked to the governing kineticsof nucleation and growth. These rich and intriguing processes can be understoodby deciphering textures. This is done by first dismantling and quantifyingthem, then by rebuilding them and simulating magma crystallization andtransport, and last by taking the results to the final court of appeal,the rocks themselves.

KEYWORDS: magma, texture, kinetics, growth, nucleation,

crystal size distribution, magma history, crystallization

groundmass are important. A whole class of terms exists forthe apparent heritage of crystals. A large homegrown crys-tal is a phenocryst, and an exotic, accidentally included crys-tal is a xenocryst. There are even microphenocrysts. Rocks witha population of large crystals are porphyritic or phyric, andthose without are aphyric. Other terms tell of the apparentsequence of crystallization. Rocks with large, optically con-tinuous crystals enclosing an assortment of smaller crystalsare poikilitic. When such crystals are as large as or largerthan a hand sample, the rocks are oikocrystic. Where plagio-clase is mostly or completely enclosed in pyroxene, the tex-ture is ophitic, and where partly enclosed, it is subophitic.The extensive articulation of crystals in the groundmassgives the larger-scale integrated fabric. Tiny, birefringentcrystals are microlites, and even smaller ones are crystallites;these sometimes occur in a cryptocrystalline mass or a messymesostasis. The texture produced by these small appressedcrystals can be granular or, if the crystals are arranged hap-hazardly, felty. If they are aligned as in a flow field, the tex-ture is pilotaxitic (also called trachytic for the rocks where thetexture is commonly found). If the interstices are filled withglass or tiny crystalline bits and pieces, the texture is intersertal.There are additional special terms for gabbros and granites.

The fact that there is a large but finite number of texturalnames suggests that certain key kinetic processes involvedin crystallization operate over and over. They may be spe-cific to a certain kind of magma but, evidently, given cer-tain prescribed conditions, a characteristic texture will beproduced. The problem with textural descriptions is thatthey are just words and not numbers. The degree of crys-tallinity, the modal amount of each mineral, and the grainsize can be easily measured, but how do these relate to thekinetics of crystallization? Modal abundances are directlyrelated to magma chemical composition, and the inspiredoriginators of the CIPW norm (Cross, Iddings, Pirsson, andWashington) showed us over a hundred years ago how topredict with amazing accuracy what kind and how much ofeach mineral a magma will produce if left alone to crystal-lize slowly and completely. And now the MELTS program(e.g. Sack and Ghiorso 1991) will tell us the exact sequenceof crystallization at almost any pressure and water content.But none of this tells us what the final rock will look like.Even the crystal sizes are unknown, and there is no chanceat all of actually calculating what the texture may be.Without texture, a rock has no face. Moreover, how do weknow if the constituent crystals in a rock belong there?Even if they look at equilibrium with one another, theycould well be accidental participants, orphans from kineticevents in other magmas. In fact, detailed microanalysis ofneighboring, seemingly identical crystals often shows themto be total aliens: antecrysts (Charlier et al. 2005; Davidsonet al. 2007). Our magmatic universe is wrapped up in texture.To understand this universe, we must measure it and thentry to build an artificial one.

ROCK ARCHITECTURE: HOW TO BUILD A ROCKThe best way to understand how something is built is totake it apart, measure everything, see how everything fitstogether, and then rebuild it and see if it still works. Cuttingthin sections is the first step. These are two-dimensionalviews of an inherently three-dimensional world, but theyare a good start, and more sophisticated 3D approaches areavailable (e.g. Mock and Jerram 2005; Jerram and Higgins2007 this issue). We have been doing such work for 150years. The next step, measuring the parts, is trickier.Sedimentologists and volcanologists often disaggregate theirsamples without damaging the grains. Then by passing the

grains through a series of sieves, they can measure the over-all population as a function of grain size; for historic rea-sons of analysis, they plot up the data using a logarithmicscale at base 2, producing the so-called phi-index. There aretwo major problems with this approach when applied toigneous materials. First, disaggregating most igneous rocksdamages the very crystals needing to be measured. Second,the approach is an analytical dead-end. It is well-nighimpossible to obtain kinetic information from phi-indexmeasurements. Chemical engineers faced the same problemwhen designing factories to produce attractive equigranularsalt. Needing to delicately adjust crystal nucleation andgrowth cycles for optimum production, they developed amethod called crystal size distributions (CSDs), and we haveborrowed heavily from them (Marsh 1988).

The rich fundamental value of the CSD approach istwofold. First, the basic unit of measurement is populationdensity, which is the number of crystals of a certain size perunit volume of rock. Being a measure of number density, itis a very stable numerical entity, like rock density. To makethese measurements, image processing is applied to thinsections (FIG. 1). Second, highly versatile equations, basedon the principle of conservation of number density, areused to interpret and model CSD data at almost any level ofcomplexity. CSDs force us to think about how magmascrystallize and help us to understand the deeper meaning oftextural descriptions. A good example is the understandingof phenocrysts.

Volcanic rocks commonly have a bimodal size population:a population of phenocrysts and a groundmass assemblageof, for example, plagioclase. Phenocrysts are classicallythought to grow at depth in a quiescent environment priorto the emplacement of the magma as a pluton or to its erup-tion as lava. The mass of small crystals is thought to resultfrom a sudden pressure drop, rapid cooling, and burst ofnucleation attending final ascent and eruption. But a kinet-ically active population of crystals (similar to active popu-lations of plants and animals involving birth and growth)should exhibit an ongoing process of nucleation andgrowth. Small and large crystals should always exist side byside. The population of crystals should march continuouslyfrom the smallest to the largest sizes. When the CSD ofmost seemingly porphyritic rocks is measured, a continu-ous, log-normal distribution of crystal population density isfound (FIG.1). Crystal populations are deceptive to the humaneye, which always seeks to identify and classify objectsaccording to a few specific size classes. The presence ofsome big crystals and many small ones suggests bimodalityto the eye. It is especially difficult visually to appreciateintermediate crystal sizes.

If we are to build a rock through nucleation and growth, thefinal product must look like a real rock and possess a realis-tic CSD. Any crystallization process starts with nucleationand proceeds with growth. The numbers or populations ofcrystals come from nucleation, and crystal size comes fromgrowth; without crystal growth, rocks would all be of thesame grain size. A fine-grained rock means that there wasno time for growth. On a CSD plot of log population den-sity versus crystal size (FIG. 1), nucleation rate is recordedalong the y-axis and growth is measured by the x-axis.Although we treat nucleation and growth as two processes,in the final result they are really kindred processes. That is,both mechanisms supply solid material, and in this sense,nucleation is just a special form of growth, and vice versa.This relationship is especially apparent in the fundamentalequations (Marsh 1998) governing the characteristic time of

248248E L E M E N T S AUGUST 2007

crystallization (tC), the characteristic number of crystals (No)in a rock per unit volume, and the characteristic size (Lo) ofcrystals in a rock:

CRYSTALLIZATION TIME (1)

NUMBER OF CRYSTALS (2)

SIZE OF CRYSTALS (3)

where JO = typical nucleation rate, GO = typical growth rate,and Ct,N,L = constants. The higher the characteristic rates ofnucleation (JO) and growth (GO), the quicker the rock crys-tallizes. The larger the nucleation rate and the smaller thegrowth rate, the greater will be the number of crystals in arock, as in chilled margins. The larger the growth rate andthe smaller the nucleation rate, the fewer and the larger thecrystals will be in a rock; plutons are coarser than dikes.These valuable equations make sense to us as geologists, butthey don’t tell us how rocks crystallize. They don’t give usthe laws of nucleation and growth. We basically know that,to a point, crystals get bigger with time, but we know muchless about how this happens, and we know even less aboutthe details of nucleation.

The fact that silicate minerals almost never form crystals largerthan about 2 cm suggests that growth might be controlledand limited by diffusion. In highly viscous silicate melts,chemical diffusivities are typically small (e.g. D ~10-12 m2/s;Dingwell 2006), and diffusion time (tD) varies according totD ! L2/D, where L is crystal radius. Because magmas arecomplex multicomponent systems, for any single mineraltype, like olivine or plagioclase, many components are notused in growth, and these rejected components accumulatearound crystals and impede growth unless diffusion carriesthem away as rapidly as they appear. But diffusion is slow.It takes about ten years for a component to move about 1 cm,and the movement of one component is expected to becoupled to the movement of others; the slowest-movingspecies slows down all the others. The net effect is thatgrowth rates are greatly limited by the polymeric nature ofsilicate melts; they mostly fall in the range of about 10-12 to10-9 m/s, and for any one magmatic body the range may beless. But nucleation is not similarly limited and can rangeenormously from about 10 to 1012 nuclei/m3/s as a result ofvariations in the rate of cooling. These characteristics ofalmost unlimited nucleation rate coupled with severely lim-ited growth rate give the general textural habits of igneousrocks. These general insights are valuable when trying tounderstand how to build a rock.

HOMEMADE ROCKSThe most direct way to build a rock is to assume that nucle-ation varies exponentially with time in a cooling event andthat growth rate (G) is approximately constant (Go). Crystalsize (L), then, increases according to L = Got. Because wewant to produce an actual texture, it is important to makesure that crystallinity varies with time or temperature in afashion similar to that observed for actual magmas. Thebulk crystallinity of almost all magmas increases in a sig-moidal fashion from liquidus to solidus. Almost any com-bination of exponential nucleation and growth will givethis sigmoidal distribution. Yet, almost without exception,especially for intrusions, magmas always seem to crystallizecompletely (becoming holocrystalline) regardless of the rateof cooling (Marsh 1998). (The major exceptions are glassyrhyolites, obsidians, and other holohyaline rocks, and theprocess of glass formation is not necessarily always a ther-mal effect, but may be the result of quenching by rapid lossof water pressure.) This means that to achieve holocrys-tallinity during crystallization, nucleation and growth mustsubstitute freely for one another according to the rate ofcooling. And, more important, it suggests that growth andnucleation are decoupled from the thermal regime. That is,regardless of the local rate of cooling, nucleation andgrowth will adjust themselves automatically to achieveholocrystallinity. This condition was first noted by Hortand Spohn (1991), who found that the timescale for cool-ing is generally much longer than that for the kinetics ofcrystallization; the ratio of these timescales is called theAvrami number. Crystallization can respond quickly to anyimposed thermal regime. This important natural conditionis of great fundamental value to building a rock because itallows the kinetics of crystallization to be calculated inde-pendently of the thermal regime.

In this light, the most direct approach is to start the calcu-lation by generating a finite population of nuclei andletting them grow in specified general shapes for a certain,arbitrarily small, period of time. The degree of crystallinityis then checked against a given sigmoidal variation ofcrystallinity with temperature or time. If the calculatedcrystallinity is on track, the existing crystals are allowed togrow through another time cycle. If crystallinity is not ontrack, nucleation is allowed to make up the difference.

249E L E M E N T S AUGUST 2007

Photomicrographs of the chilled margin and interior of aFerrar Dolerite sill, with the associated CSD for each sam-

ple. The chilled margin CSD is very steep, reflecting a high nucleationrate and small crystal sizes resulting from short growth times. In con-trast, the interior CSD has a low intercept and a gentle slope. Thesmaller inset diagram indicates how an idealized CSD develops due tonucleation and growth. The numbers (N) of crystals and typical crystalsize (L) in each sample, as ascertained from the CSD systematics, simi-larly reflect these conditions. The chilled margin contains about six mil-lion crystals per cubic centimeter with a typical size of about 28 microns.The interior sample contains only about four thousand crystals per cubiccentimeter, and the typical crystal size, at 360 microns, is much larger.

FIGURE 1

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Recall that with a constant rate of growth, once crystallinitymismatches, it can never catch up by growth alone unlessthe growth rate is increased. This procedure is continueduntil the rock is fully crystallized. The resulting syntheticrock is shown in both two and three dimensions in FIGURE 2(Hersum and Marsh 2006). Because the approach is identi-cal regardless of how many minerals are involved—although each can have different rates of growth andnucleation—a “true” texture can be calculated for severalminerals. In these examples, all crystals are represented bylaths of shape 1:2:5. The calculated process of crystallizationproceeds in a fashion similar to that of real rocks, and theresulting CSD is realistic. In spite of the assumed lineargrowth law, crystal size does not steadily increase; rather,the growth rate wanes and stops increasing altogether inlater times. This cessation of growth is due to physicalimpingement between neighboring crystals, whichbecomes a serious liability in all rocks once crystallinityreaches about 50 vol% (Burkhard 2002).

It would thus seem easy to make a realistic texture with asimple model of exponential nucleation and constantgrowth. When we say a texture is realistic, we mean that itcould pass under casual observation for a real texture, albeitsomewhat rudimentary. Using this test, it is revealing tofind conditions of growth and nucleation that produceunnatural-looking textures. Dispersive crystal growth is oneprocess that produces unnatural textures. Although growthat a constant, or approximately constant, rate is common inmany industrial systems, in some aqueous systems individ-ual crystals have been observed to grow at distinct growthrates, evidently depending on subtle unique local condi-tions. The overall family of growth rates thus spans a finiterange, and growth rates are assigned randomly to the pop-ulation of crystals. The ensuing texture is, by and large, also

realistic, but not for a simple, single-stage crystallizationevent (FIG. 2, right-hand panel). After about 25% crystal-lization, the rock appears unusually porphyritic, which is anatural texture most commonly observed in the case ofpiecemeal crystallization or in magmas that have inheritedcrystals from an entirely independent event (i.e. xenocrystsand antecrysts). The resulting CSD is not unusual, but theearly appearance of “phenocrysts” perhaps makes this tex-ture unrealistic.

A feature of this numerical crystallization approach thatmay seem too artificial, especially in light of all that weknow about diffusion-controlled growth, is the assumptionof a constant rate of growth. Yet, it seems to hold or workexceedingly well, and it also seems to be a safe assumptionwhen interpreting many CSDs in both geologic and indus-trial systems (Randolph and Larson 1988; Cashman andMarsh 1988; Cashman 1993; Marsh 1998; Zieg and Marsh2002). How could this be so?

CONSTANT CRYSTAL GROWTH RATESIn messy, multicomponent silicate magmas, other crystal-lization processes probably operate to maintain a steadygrowth rate. These processes may have very little to do withdiffusion; in fact they may short-circuit diffusion. The prob-lem with diffusion-controlled growth is that the larger acrystal becomes, the more difficult it is to sustain growth(Frank 1950). This is because the halos or blankets of rejectedchemical components surrounding each crystal becomeincreasingly large, choking further growth. In low-viscositysolutions, these chemical boundary layers can be swept awayby bulk fluid flow or sinking of the crystal, or they can belost through their own buoyancy. But in magmas, theseconditions are not easily met. A more direct way to erase theseboundary layers is by nucleating and growing new mineralphases that use the rejected components as nutrients.

Most basalts are near multiple saturation at the liquidus. Forexample, initial crystallization of Hawaiian tholeiiticbasalts, which can be carefully observed in lava lakes(Wright and Okamura 1977) and lavas (e.g. Cashman et al.1999), takes place in highly concentrated clusters of olivineand plagioclase (FIG. 3). Careful inspection shows these clus-ters to be dense concentrations of tiny crystals of olivineand plagioclase, shoulder to shoulder in almost-interlock-ing masses. Chemical components rejected by olivine stim-ulate nucleation and growth of plagioclase, and vice versa.As temperature drops, first clinopyroxene and then theFe–Ti oxides crystallize and repeat the process. As crystal-lization proceeds, large euhedral crystals appear, in time,from these densely populated clusters of tiny crystals. Thetiny crystals attach to one another, combine and, throughgrain boundary migration, become optically continuous.When two neighboring crystals meet, the one with thelower total surface free energy, which is normally the largerone, effectively consumes the smaller crystal. Growth isthus through nucleation followed by limited growth andthen by aggregation into larger and larger crystals.

Once recognized, this process can be clearly seen operatingin all quickly chilled magmas where the quenched crystalsare large enough to be studied at high magnification. Theprocess may also continue, given the proper opportunities,at high crystallinities where quenching is uncommon; tell-tale signs can often be seen in subtle dusty internal bound-aries within otherwise normal euhedral crystals. Theresulting kinetics of this process of grain annexation, whichis, in effect, a form of high-temperature annealing, are sorapid that little evidence of such growth is left in the finalrock record. Another form of this process very likely takesplace in the final crystallization of initially monomineralic

Monomineralic crystallization simulations involving rec-tangular prisms and an exponential nucleation rate. The

upper figures depict true 3D visualizations of the computed texturesand the lower figures show thin-section-like representations of the tex-tures during four stages of crystallization (3.4, 22.9, 57.5, and 99.0vol% crystals). (Left panel) Uniform and constant crystal growth rategenerates microstructures with less variance in crystal size compared todispersive crystal growth (right panel), which allows each crystal to havea different growth rate that is constant throughout crystallization. Ran-dom colors are assigned to connected crystals.

FIGURE 2

cumulate beds. To further crystallize the residual, inter-granular melt, a second mineral nucleates and often growsunusually large, almost as a large aspect ratio pegmatite.This is possible because the components rejected by thenew mineral are devoured by the initially existing crystals,and growth can be sustained almost indefinitely withregard to size, especially if the initial crystals are small withlarge exposed surface areas.

Silicate crystals may, indeed, exhibit linear growth, but thegrowth process is diffusion controlled only at the stage ofthe smallest crystals, just beyond the nucleation stage. Theoverall process is very likely the net result of a multitude ofprocesses, only a few of which we currently understand.

TEXTURE MATURATION AND INTEGRITYA major advantage of studying crystallization numericallyis that the resulting simulated microstructures can be stud-ied in various ways to understand changes in magma rhe-ology and macroscale physical properties that are otherwiseexceedingly difficult or impossible to obtain by laboratorymeasurements. These changes control a multitude of fun-damental magmatic processes, including melt transport,eruption, and chemical differentiation, as well as geophysi-cal processes at active magmatic centers. The permeabilityof the full 3D texture, for example, can be estimated as afunction of melt content, crystallinity, and porosity by sim-ulating a Darcian flow through the sample from one side tothe other (Hersum et al. 2005). This method can also beused to study natural samples that have been deconstructedby serial sectioning (Marschallinger 1998; Mock and Jerram2005) and microtomography (e.g. Ketcham and Carlson 2001;see also Jerram and Higgins 2007). But the rarity of existingnatural samples at arbitrary states of arrested crystallizationseverely hampers this approach. Nevertheless, Philpotts et al.(1996) manufactured a partially melted and quenched sam-ple of Holyoke basalt and measured the melt distribution bymicrotomography. The permeability of this specimen is vir-tually indistinguishable from those of the numerically gen-erated samples (Hersum et al. 2005). FIGURE 4 shows atypical pattern of internal interstitial melt flow in a numer-ical sample. The flow is strongly heterogeneous within thetexture and concentrated along specific channels where thetexture happens to be conducive to flow. These channelsare thin, with a thickness or lengthscale (d) roughly com-parable to the grain size. The presence of these channelsmay have a profound effect on the final rock.

251

Photomicrographs of Kilauea Iki basalt undergoing crys-tallization (all in plane light unless otherwise noted).

(A) The overall style of crystallization near the liquidus: clusters of smallcrystals of granular olivine and laths of plagioclase in brown glass [fieldof view (FOV) is about 1 mm]. (B) Close-up view of swarms of inter-locking olivine grains and plagioclase laths (FOV ~0.1 mm). (C) Close-upview of growth styles of olivine (center) and plagioclase as touchinggrains in apparently separate clusters and as interpenetrating grains(upper left) (FOV ~0.1 mm). (D) Intimate interlocking intergrowths ofolivine and plagioclase; some plagioclase crystals (upper left) haveannealed into a single larger grain (FOV ~0.05 mm). (E) Intimate inter-growth of plagioclase laths and olivine grains, where intergrowth isalong crystal edges and interpenetrates each mineral (FOV ~0.025 mm).(F) Several grains of olivine in the process of annealing into a singlegrain (crossed polars, FOV ~0.015 mm).

FIGURE 3

Numerical simulation ofmicrostructure and

intercrystalline residual melt flow dur-ing basalt crystallization. The left paneldepicts the two-dimensional pattern ofcrystals after 30 vol% crystallization;the black matrix is melt and the tinywhite arrows are melt velocity vectors.The panel on the right more clearlyindicates the residual melt flow patternand flow intensity, where the hottercolors indicate stronger flow (see sidebar). The flow field is strongly channel-ized even at this relatively low crys-tallinity. The flow field was calculatedusing the Lattice-Boltzmann method;for details on this approach see Her-sum et al. (2005).

FIGURE 4

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BA

DC

FE

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Cashman KV, Thornber C, Kauahikaua JP(1999) Cooling and crystallization of lavain open channels, and the transition ofPahoehoe lava to ‘A’a. Bulletin ofVolcanology 61: 306-323

Charlier BLA, Wilson CJN, Lowenstern JB,Blake S, van Calsteren PW, Davidson JP(2005) Magma generation at a large,hyperactive silicic volcano (Taupo, NewZealand) revealed by U–Th and U–Pbsystematics in zircons. Journal ofPetrology 46: 3-32

Davidson JP, Morgan DJ, Charlier BLA,Harlou R, Hora JM (2007) Microsamplingand isotopic analysis of igneous rocks:Implications for the study of magmaticsystems. Annual Review of Earth &Planetary Sciences 35: 273-311

Dingwell D (2006) Transport properties ofmagma: Diffusion and rheology. Elements2: 281-286

Frank FC (1950) Radially symmetric phasegrowth controlled by diffusion. Proceedingsof the Royal Society A: 586-599

Hersum TG, Marsh BD (2006) Igneousmicrostructures from kinetic models ofcrystallization. Journal of Volcanologyand Geothermal Research 154: 34-47

Hersum TG, Hilpert M, Marsh B (2005)Permeability and melt flow in simulatedand natural partially molten basalticmagmas. Earth and Planetary ScienceLetters 237: 798-814

Hort M, Spohn T (1991) Crystallizationcalculations for a binary melt cooling atconstant rates of heat removal:implications for the crystallization ofmagma bodies. Earth and PlanetaryScience Letters 107: 463-474

Jerram DA, Higgins MD (2007) 3D analysisof rock textures: Quantifying igneousmicrostructures. Elements 3: 239-245

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Zieg MJ, Marsh BD (2002) Crystal sizedistributions and scaling laws in thequantification of igneous textures.Journal of Petrology 43: 85-101 !

As the melt flows in response to spatial density differencesdue to crystallization and volatile buildup, it carries bothheat and chemical components along these channels. Thedistance the flow travels before it re-equilibrates with itssurroundings is measured by the magnitude of the Pecletnumber (Pe), which is a non-dimensional number measur-ing the rate of the Darcian melt flow (UD) relative to diffusiveflow of heat (PeT = UDd/") or mass (PeC = UDd/D), where "is thermal diffusivity (~10-6 m2/s) and D is chemical diffu-sivity (~10-12 m2/s). The channel width (d) is on the orderof the grain size (d ~1 mm), and the flow velocity can beestimated from Darcy’s equation, UD ! # $%g/µ, where #(&10-9m2) is permeability, $% (&100 kg/m3) is density differ-ence, g is gravity, and µ (&10 Pa s) is melt viscosity. Theresulting values of Pe are PeT ! 10-4 and PeC ! 1. This meansthat the transport of heat at this scale is dominated by localdiffusion, and the specimen will not become unevenlyheated along these channels. On the other hand, masstransport is affected equally by diffusion and fluid flow(advection), and for any smaller D, which is likely, advec-tion will dominate over diffusion. This may make the finaldistribution of incompatible trace elements highly unevenin the final rock, and the effects of late stage buildup involatiles may be concentrated along these zones. Thisprocess may be important in the later stages of crystalliza-tion, and also during reheating (Bachmann and Bergantz2006), when the rock has great strength and a volatile phaseappears, promoting first dissolution and then alterationand ore deposition.

CONCLUSIONBy measuring the crystals in igneous rocks systematically,simulating crystallization numerically, cutting rocks apart,X-raying rocks, and puzzling over beautiful thin sections,we are beginning to understand the secrets of textures asintimate records of the life history of magma. The qualita-tive knowledge gathered through a century of relating textureto process is being reinforced by quantitative approaches.Yet, new and mysterious kinetic processes are beingrevealed to us in these same textures. As in the days of clas-sical petrography, much can still be gained using theseinsights in the careful study of igneous rocks in thin section.Numerous natural experiments in crystallization can beobserved, from quickly cooled dolerite dikes to long-simmeredplutons. Tempered with a basic grounding in the kineticcontrols on crystallization and the process of cooling, know-ing what to expect, and carefully observing what is there,modern studies of texture promise rich rewards.

ACKNOWLEDGMENTSHelpful reviews by Jon Davidson, Michael Zieg, GeorgeBergantz, Dougal Jerram, Bruce Watson and Olivier Bachmannare much appreciated. Our long-term interest in the gener-ation, transport and crystallization of magma is supportedby the U.S. National Science Foundation, and is currentlyapplied to our work on the Ferrar magmatic system of theMcMurdo Dry Valleys, Antarctica (OPP 0440718). !