A model for calculating the errors of 2D bulk analysis relative to the true 3D bulk composition of an object, with application to chondrules

Certain problems in Geosciences require knowledge of the chemical bulk composition of objects, such as, for example, minerals or lithic clasts. This 3D bulk chemical composition (bcc) is often difficult to obtain, but if the object is prepared as a thin or thick polished section a 2D bcc can be easily determined using, for example, an electron microprobe. The 2D bcc contains an error relative to the true 3D bcc that is unknown. Here I present a computer program that calculates this error, which is represented as the standard deviation of the 2D bcc relative to the real 3D bcc. A requirement for such calculations is an approximate structure of the 3D object. In petrological applications, the known fabrics of rocks facilitate modeling. The size of the standard deviation depends on (1) the modal abundance of the phases, (2) the element concentration differences between phases and (3) the distribution of the phases, i.e. the homogeneity/heterogeneity of the object considered. A newly introduced parameter ''@t'' is used as a measure of this homogeneity/heterogeneity. Accessory phases, which do not necessarily appear in 2D thin sections, are a second source of error, in particular if they contain high concentrations of specific elements. An abundance of only 1vol% of an accessory phase may raise the 3D bcc of an element by up to a factor of ~8. The code can be queried as to whether broad beam, point, line or area analysis technique is best for obtaining 2D bcc. No general conclusion can be deduced, as the error rates of these techniques depend on the specific structure of the object considered. As an example chondrules-rapidly solidified melt droplets of chondritic meteorites-are used. It is demonstrated that 2D bcc may be used to reveal trends in the chemistry of 3D objects.

[1]  R. T. DeHoff,et al.  Quantitative serial sectioning analysis: preview , 1983 .

[2]  John C. Tipper A method and fortran program for the computerized reconstruction of three-dimensional objects from serial sections , 1977 .

[3]  Z. P. Budka 28th Lunar and Planetary Science Conference. , 1997 .

[4]  Robert H. Hunter,et al.  Precision serial lapping, imaging and threedimensional reconstruction of minus-cement and post-cementation intergranular pore-systems in the Penrith Sandstone of north-western England , 1995 .

[5]  R. Ketcham,et al.  Three‐dimensional quantitative textural analysis of metamorphic rocks using high‐resolution computed X‐ray tomography: Part I. Methods and techniques , 1997 .

[6]  William D. Carlson,et al.  Three‐dimensional quantitative textural analysis of metamorphic rocks using high‐resolution computed X‐ray tomography: Part II. Application to natural samples , 1997 .

[7]  T. Grove,et al.  Ternary feldspar experiments and thermodynamic models , 1990 .

[8]  Dougal A. Jerram,et al.  Crystal Size Distributions (CSD) in Three Dimensions: Insights from the 3D Reconstruction of a Highly Porphyritic Rhyolite , 2005 .

[9]  H. Hirai,et al.  High Resolution X-Ray CT Images of Chondrites and Chondrules, and Their Three-Dimensional Structures , 1997 .

[10]  Christopher B. Jones,et al.  Contour correspondence for serial section reconstruction: complex scenarios in palaeontology , 2001 .

[11]  Lutz Nasdala,et al.  Evidence for fractional condensation and reprocessing at high temperatures in CH chondrites , 2003 .

[12]  Lutz Nasdala,et al.  Origin of SiO2-rich components in ordinary chondrites , 2006 .

[13]  R. Marschallinger,et al.  A method for three-dimensional reconstruction of macroscopic features in geological materials , 1998 .

[14]  Klaus Keil,et al.  The Genetic Relationship between Refractory Inclusions and Chondrules , 2005 .

[15]  Rhian H. Jones,et al.  Petrology and mineralogy of Type II, FeO-rich chondrules in Semarkona (LL3.0) - Origin by closed-system fractional crystallization, with evidence for supercooling , 1990 .

[16]  Don D. Eisenhour,et al.  Determining chondrule size distributions from thin‐section measurements , 1996 .

[17]  Jeffrey N. Grossman,et al.  Refractory precursor components of Semarkona chondrules and the fractionation of refractory elements among chondrites , 1983 .

[18]  H. Nekvasil,et al.  SOLVCALC: an interactive graphics program package for calculating the ternary feldspar solvus and for two-feldspar geothermometry , 1994 .

[19]  M. Atherton,et al.  The interpretation of granitic textures from serial thin sectioning, image analysis and three-dimensional reconstruction , 1995, Mineralogical Magazine.

[20]  K. D. Tocher,et al.  Petrographic Modal Analysis. , 1957 .

[21]  Scott E. Johnson,et al.  Surface reconstruction from parallel serial sections using the program Mathematica : example and source code , 1993 .

[22]  Mark L. Rivers,et al.  Meteorite 3‐D synchrotron microtomography: Methods and applications , 2007 .

[23]  Dork Sahagian,et al.  3D particle size distributions from 2D observations : stereology for natural applications , 1998 .

[24]  Shogo Tachibana,et al.  Correlation between relative ages inferred from 26Al and bulk compositions of ferromagnesian chondrules in least equilibrated ordinary chondrites , 2003 .

[25]  Ian A. Franchi,et al.  Cristobalite- and tridymite-bearing clasts in Parnallee (LL3) and Farmington (L5) , 1995 .

[26]  Alan E. Rubin,et al.  Chemical, Mineralogical and Isotopic Properties of Chondrules: Clues to Their Origin , 2004 .