VOL. 13, NO. 4 REVIEWS OF GEOPHYSICSAND SPACEPHYSICS AUGUST 1975 Classificationand Properties of Iron Meteorites EI•W^RI• R. D. SCOTT 1 AND JOHN T. WASSON Departmentsof Chemistry and Planetary and Space Science and Institute of Geophysicsand Planetary Physics Universityof California,Los Angeles,California 90024 Most (86%)iron meteoritescan be assignedto one of 12 geneticgroups on the basisof systematic variationsin their chemical,mineralogical, and structuralproperties; the remaining14% are termed anomalous.The groups are best resolved on Ga-Ni or Ge-Ni plots,but they may also be defined using other elements,the distributionand morphologyof characteristicminerals, and very often kamacite bandwidths.The powerof thisclassification to revealcorrelations of numerousand diverseproperties withinthese,groups and systematic variations between groups emphasizes its validity. Its useis essential for understandingthe formationof ironmeteorites. A cornpar!sonof the 12groups suggests that there are two typeswith very different histories: (1) themajor groups IIAB, IIIAB, andIVA (11, 32,and 8% of all irons, lCalJCCuvciy/,- ...... :"•"" probably I•,•, '•-' liD, and IVB, andpossibly CtI•U•'*- IC, IIIE, andIIIF ' withinthese groups, mostproperties are correlatedand chemicaland mineralogicaltrends closely similar and (2) the large groupIAB (19%of all irons),IIICD, andprobably IIE, in whichcorrelations between properties are gen- erallymuch weaker and the observedtrends distinctly different from thosein groupsof the formertype. Eachgroup very probably formed in itsown parent body. Groups of thesecond type seem to havediverse formationalhistories, but we believethat, unlike the first type, they were not oncepart of molten cores. Thisstudy is basedon results from nearly 500 different iron meteorites, which are listed with their classifi- cationtogether with 70 otherpaired irons. We presenta comparativestudy of the propertiesof the 12 groupswithout attempting to fit thesedata to detailedmodels for their formation. CONTENTS we can apply to the classificationscheme: (1) whether the distributionsof other parametersreinforce this classification, Taxonomicproperties .................................. 527 Chemical classification .................................. 528 for example,by delineatingthe samegroups when taken in Iron meteoriteproperties ............................... 530 combination with each other or with one of the defining Iron meteoritegroups .................................. 534 parameters,and (2) whetherthe classificationcan reveal cor- Group characteristics................................... 540 relationswithin groupswhich are absentfor all the ironstaken Implications ........................................... 540 as a whole. Our faith in the geneticusefulness of a scheme INTRODUCTION will dependon its successat interpretingother propertiesin The iron meteorites were earlier considered as a fairly this way. We first describesome of the propertieswhich may homogeneouspopulation which shareda commonorigin. be usedto classifyirons and reviewsome of the schemespro- Detailedinvestigations have revealed this assumption to be er- posed.Our aim is to demonstratethat there is now a highly roneous and showed that there is a need for a classification successfulgenetic classification of iron meteorites. systemthat groupstogether genetically related irons, i.e., those TAXONOMIC PROPERTIES that formed in the same locality in the solar systemand ex- perienceda similarchemical and physical history. In thispaper Structural. The structural classificationsystem has been we describe a classification scheme for the irons which has widely usedsince it was developedby Tscherrnak[1872, 1883] beendeveloped during the last 9 yearsand whichwe believe and Brezina [1885, 1904]. It is based on the structure which is fulfils theserequirements. Although these investigations have visible when a polishedsurface is etchedin acid. The majority providednumerous constraints on the historyof the irons,we of irons show an octahedral array of kamacite (a-Fe, Ni) will not attempt to discussthe interpretationof the data in- bands and are classifiedaccording to the width of thesebands. sofar as it relates to the various models that have been pro- Nearly all the remainder are either hexahedritescomposed posedfor the formation of the irons. Instead,we will describe almost entirely of kamacite, which showsa cubic cleavage,or the classificationscheme and the most Usefultaxonomic pa- ataxites composedlargely of taenite (•-Fe, Ni). For a discus- sion of the octahedral Widmanst•itten structure see Axon rameters and review the general chemical and mineralogical properties of the irons. In the secondhalf of this paper we [1968a] and GoldsteinandAxon [1973]. A recentversion of this give a comparative survey of the groups. classificationscheme by V. F. Buchwald (private communica- A varietyof parametershave been used at different times to tion in Wasson[1970a]) is shown in Table 1 together with the classifyiron meteorites.These includethe more obviousones bandwidth divisions of Brezina [1885]. Slightly different values for the limits of the octahedrite classes have also been such as chemical, structural, or mineralogicalproperties and less obvious ones which were determined indirectly, e.g., proposedby Loveringet al. [1957] and Goldstein[1969]. Each cosmicray exposureages or coolingrates. There is no a priori systemrepresents an attemptto fit the limitsto the minima in a method for guessingwhich parameteror set of parameterswill histogramof bandwidthmeasurements. We preferBuchwald's' be the most useful for establishinga genetically significant schemein which the bandwidths in each classvary by a factor classification.In the absenceof a singleparameter that shows of 2.5, since, as we will see, his bandwidth divisionsgenerally several well-defined hiatuses the best combination is that which fall at the edgeof geneticgroups. Figure 5, which is discussed most clearly resolvesthe irons into groups.There are two tests later, showsa histogramof bandwidthvalues for the iron meteorites. •Now at Department of Mineralogy and Petrology,University of As we demonstratebelow, this single-parameterclassifica- Cambridge, Cambridge, England. tion schemedoes not divide the irons into geneticallyrelated Copyright¸ 1975by the AmericanGeophysical Union. groups. The fact that bandwidth itself is a function of two 527 528 SCOTTAND WASSON:CLASSIFICATION AND PROPFRTIFSOF IRON METFORITFS parameters, bulk Ni content and cooling rate, does not, as Brown [1965], who definedthree Ru-Rh and three Ir-Pt groups Goldstein [1969] suggested,necessarily mean that it could from their analysesof 24 irons. There was however, no clear never be usedto classifyirons into genetically related groups. relationshipbetween these two setsof groups or with the Ga- In fact, virtually all hexahedritesdo form one geneticgroup. Ge groups.Such conflictingquantizations would be difficult to However, in many other casesthere is overlap of bandwidths comprehendbut might conceivablyreflect earlier fractionation betweenthe groups. Nevertheless,the relatively small overlap events,evidence for which had not been completelyerased by of the major groups and the easeand simplicityof the method the event which fractionatedGa and Ge. However, subsequent have ensured the continued usefulness of this scheme. investigations[Wasson, 1967; Crocket, 1972] showed that' Chemical. Although it was recognizedvery early [e.g., Far- these gaps were filled by other irons and the quantizations rington, 1907] that the bulk Ni contentsgenerally increaseas were entirely spurious. the bandwidths decrease,chemical parameterswere not an es- Otherproperties. Here we briefly summarizeother proper- sential part of the classification scheme described above. ties of the irons which might give useful genetic clues. The Goldberget al. [1951] found a good correlation between the results will all be discussedin greater detail in later sections. bandwidthsand the Ga content. But, more importantly, their Theoretical models for the growth of kamacite have been Ga data on 45 irons were quantized into three fairly well developedby Wood [1964] and Goldsteinand Short [1967a, b]. separatedranges: 45-100, 17-22, and 1.7-2.5 ppm. Lovering et Using the relevant equilibrium phasecompositions and diffu- al. [1957] analyzed 88 irons for Ga and Ge and discoveredthat sioncoefficients, these authors calculated cooling rates for the the first of theseranges could be dividedin two. Becausethe Ge irons (at •500øC) by matchingpredicted and observedNi in- concentrations were also quantized, these clusterswere called homogeneitiesin taenite. Goldstein and Short found that they Ga-Ge groups and labeled I-IV in order of decreasingGa could estimatethe cooling ratesof many irons from a knowl- and Ge contents.Eleven of the irons fell outside thesegroups edgeof their bulk Ni contentand kamacitebandwidth. Gold- and were called anomalous. It was this pioneering work of stein [1969] usedthese parameters to developa cooling rate Brown and co-workers which provided the basis for a classificationscheme which supportedthe chemicalclassi- geneticallysignificant classification scheme. fication and is discussed below. Workingwith greatersensitivity, Wasson [i967] resolvedthe Another parameter available for classificationis the cosmic lowest Ga-Ge group into two clusters which were also cor- ray exposureage, which datesthe time when the meteoritewas related with structure. These were designatedIVA and IVB reducedto