Hostname: page-component-848d4c4894-mwx4w Total loading time: 0 Render date: 2024-06-30T14:06:11.152Z Has data issue: false hasContentIssue false
  • English
  • Français

Reducing Supervision of Quantitative Image Analysis of Meteorite Samples

Published online by Cambridge University Press:  20 December 2019

Ellen J. Crapster-Pregont  and
Denton S. Ebel
Ellen J. Crapster-Pregont*
Affiliation:
Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY10964, USA Department of Earth and Planetary Science, American Museum of Natural History, Central Park West at 79th Street, New York, NY10024, USA
Denton S. Ebel
Affiliation:
Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY10964, USA Department of Earth and Planetary Science, American Museum of Natural History, Central Park West at 79th Street, New York, NY10024, USA
*
*Author for correspondence: Ellen J. Crapster-Pregont, E-mail: ellencp@ldeo.columbia.edu
Get access

Abstract

When selecting a method for determining modal mineralogy and elemental composition of geological samples (e.g., meteorites), a number of factors should be considered, includingthe number of objects or the area to be analyzed; the scale of expected chemical variation; instrument time restrictions; and post-processing time. This study presents a method that minimizes acquisition time while maintaining the ability to distinguish minerals based on combinations of intensities of electron probe micro-analyzer-generated X-ray element maps. While some other methods yield similar outcomes, this method's post-processing utilizes standard parameterized, X-ray intensity “map math” in an algorithm that is adaptable and requires minimal supervision once implemented. This study's minimized supervision in the post-processing of X-ray intensity maps decreases analysis time and its adaptability increases the number of potential applications. The method also facilitates calibration of the exact locations of analysis using laser ablation methods. While the method described here has advantages, the choice of method always depends on the question being asked.

Keywords

chondriteEPMAphase analysisquantitative image analysisX-ray intensity
Type
Materials Science Applications
Information
Microscopy and Microanalysis , Volume 26 , Issue 1 , February 2020 , pp. 63 - 75
Copyright
Copyright © Microscopy Society of America 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alpert, SP, Neiman, JR, Ebel, DS & Gemma, ME (2019). Using WDS mapping to identify the modal mineralogy of meteorites. In MAS Quantitative Analysis 2019, Topical Conference Program, June 24–27, 2019, University of Minnesota, Minneapolis, pp. 50–51.Google Scholar
Bence, AE & Albee, AL (1968). Empirical correction factors for the electron microanalysis of silicates and oxides. J Geol 76, 382.CrossRefGoogle Scholar
Buse, B & Kearns, S (2018). Evaluating X-ray microanalysis phase maps using principal component analysis. Microsc Microanal 24, 116–125.CrossRefGoogle ScholarPubMed
Carpenter, PK, North, SN, Jolliff, BL & Donovan, JJ (2013). EPMA quantitative compositional mapping and analysis of lunar samples. In 44th Lunar and Planetary Science Conference, The Woodlands, TX, March 18–22, 2013, LPI Contribution No. 1719, p. 182.Google Scholar
Chouinard, J & Donovan, J (2015). Quantitative elemental mapping with electron microprobe and automated data analysis. Microsc Microanal 21(S3), 2193–2194.CrossRefGoogle Scholar
Clarke, GL, Daczko, NR & Nockolds, C (2001). A method for applying matrix corrections to X-ray intensity maps using the Bence-Albee algorithm and MATLAB. J Metamorph Petrol 19, 635–645.CrossRefGoogle Scholar
Cossio, R & Borghi, A (1998). PetroMap: MS-DOS software package for quantitative processing of X-ray maps of zoned minerals. Comput Geosci 24, 805–814.CrossRefGoogle Scholar
Crapster-Pregont, EJ (2017). Constraining the chemical environment and processes in the protoplanetary disk: Perspective from populations of calcium- and aluminum-rich inclusions in Ornans-group and metal-rich chondrules in Renazzo-group carbonaceous chondrites. Dissertation. Columbia University. Proquest. Available at https://doi.org/10.7916/D8SN0N85.CrossRefGoogle Scholar
De Andrade, V, Vidal, O, Lewin, E, O'Brien, P & Agard, P (2006). Quantification of electron microprobe compositional maps of rock thin sections: An optimized method and examples. J Metamorph Geol 24, 655–668.CrossRefGoogle Scholar
Donovan, JJ (2019). Probe for EPMA User's Guide and Reference: Xtreme Edition, Kremser, D, Fournelle, J & Goemann, K (Eds.), p. 431. Probe Software, Inc. Available at https://probesoftware.com/download/PROBEWIN.pdf.Google Scholar
Donovan, JJ, Lowers, HA & Rusk, BG (2011). Improved electron probe microanalysis of trace elements in quartz. Am Mineral 96, 274–282.CrossRefGoogle Scholar
Donovan, JJ, Rivers, ML & Armstrong, JT (1992). PRSUPR: Automation and analysis software for wavelength dispersive electron-beam microanalysis on a PC. Am Mineral 77, 444–445.Google Scholar
Donovan, JJ, Singer, JW & Armstrong, JT (2016). A new EPMA method for fast trace element analysis in simple matrices. Am Mineral 101, 1839–1853.CrossRefGoogle Scholar
Donovan, JJ & Tingle, TN (1996). An improved mean atomic number background correction for quantitative microanalysis. J Microsc Soc Am 2, 1–7.Google Scholar
Ebel, DS (2006). Condensation of rocky material in astrophysical environments. In Meteorites and the Early Solar System II, Lauretta, DS & McSween, HY Jr. (Eds.), pp. 253–277. Tucson, AZ, USA: University of Arizona Press.Google Scholar
Ebel, DS, Brunner, CE, Konrad, K, Leftwich, K, Erb, IR, Lu, M, Rodriguez, H, Crapster-Pregont, EJ, Friedrich, JM & Weisberg, MK (2016). Abundance, major element composition and size of components and matrix in CV, CO and Acfer 094 chondrites. Geochim Cosmochim Acta 172, 322–356.CrossRefGoogle Scholar
Ebel, DS, Weisberg, MK, Hertz, J & Campbell, AJ (2008). Shape, metal abundance, chemistry and origin of chondrules in the Renazzo (CR) chondrite. Meteorit Planet Sci 43, 1725–1740.CrossRefGoogle Scholar
Erda Imagine (2019). Available at https://www.hexagongeospatial.com/products/power-portfolio/erdas-imagine/erdas-imagine-remote-sensing-software-package (accessed October 5, 2019).Google Scholar
Friedrich, JM, Weisberg, MK, Ebel D, S, Biltz, AE, Corbett, BM, Iotzov, IV, Khan, WS & Wolman, MD (2014). Chondrule size and related physical properties: A compilation and evaluation of current data across all meteorite groups. Chemie der Erde – Geochem 75, 419–443.CrossRefGoogle Scholar
Friel, JJ (2004). X-ray and Image Analysis in Electron Microscopy, 2nd ed. Rocky Hill, NJ: Princeton Gamma-Tech, p. 113.Google Scholar
Goldstein, JI, Newbury, DE, Michael, JR, Ritchie, NWM, Scott, JHJ & Joy, DC (2018). Scanning Electron Microscopy and X-Ray Microanalysis, 4th ed. New York: Springer, p. 554.CrossRefGoogle Scholar
Hezel, DC (2010). A mathematica code to produce phase maps from two element maps. Comput Geosci 36, 1097–1099.CrossRefGoogle Scholar
Hezel, DC, Russell, SS, Ross, AJ & Kearsley, AT (2008). Modal abundances of CAIs: Implications for bulk chondrite element abundances and fractionations. Meteorit Planet Sci 43, 1879–1894.CrossRefGoogle Scholar
IDL (2019). IDL programming language. Available at https://www.harrisgeospatial.com/Software-Technology/IDL (accessed October 5, 2019).Google Scholar
ImageJ (2019). NIH image analysis software, also known as FIJI. Available at http://rsbweb.nih.gov/ij/ (accessed October 5, 2019).Google Scholar
Itoh, H, Kojima, H & Yurimoto, H (2004). Petrography and oxygen isotopic compositions in refractory inclusions from CO chondrites. Geochim Cosmochim Acta 68, 183–194.CrossRefGoogle Scholar
Jones, RH (1994). Petrology of FeO-poor, porphyritic pyroxene chondrules in the Semarkona chondrite. Geochim Cosmochim Acta 58, 5325–5340.CrossRefGoogle Scholar
Jones, RH (2012). Petrographic constraints on the diversity of chondrule reservoirs in the protoplanetary disk. Meteorit Planet Sci 47, 1176–1190.CrossRefGoogle Scholar
Jones, RH & Scott, ERD (1989). Petrology and thermal history of type IA chondrules in the Semarkona (LL3.0) chondrite. In Proc. 19th LPSC, vol. 19, pp. 523–536.Google Scholar
Lanari, P, Vho, A, Boway, T, Airaghi, L & Centrella, S (2018). Quantitative compositional mapping of mineral phases by electron probe micro-analyser. In Metamorphic Geology: Microscale to Mountain Belts, vol. 478, Ferrero, S, Lanari, P, Goncalves, P & Grosch, EG (Eds.), pp. 39–63. Geological Society, London, Special Publications.Google Scholar
Lanari, P, Vidal, O, De Andrade, V, Dubacq, B, Lewin, E, Grosch, EG & Schwartz, S (2014). XMapTools: A MATLAB©-based program for electron microprobe X-ray image processing and geothermobarometry. Comput Geosci 62, 227–240.CrossRefGoogle Scholar
Liebske, C (2015). iSpectra: An open source toolbox for the analysis of spectral images recorded on scanning electron microscopes. Microsc Microanal 21, 1006–1016.CrossRefGoogle ScholarPubMed
Lineweaver, J (1963). Oxygen outgassing caused by electron bombardment of glass. J Appl Phys 34, 1786–1791.CrossRefGoogle Scholar
Lodders, K (2003). Solar system abundances and condensation temperatures of the elements. Astrophys J 591, 1220–1247.CrossRefGoogle Scholar
Maloy, AK & Treiman, AH (2007). Evaluation of image classification routines for determining modal mineralogy of rocks from X-ray maps. Am Mineral 92, 1781–1788.CrossRefGoogle Scholar
MATLAB (2019). The MathWorks, Inc., Natick, MA, USA. Available at https://www.mathworks.com/ (accessed October 5, 2019).Google Scholar
McSween, HY Jr. (1977 a). Carbonaceous chondrites of the Ornans type: A metamorphic sequence. Geochim Cosmochim Acta 41, 477–491.CrossRefGoogle Scholar
McSween, HY Jr. (1977 b). Petrographic variations among carbonaceous chondrites of the Vigarano type. Geochim Cosmochim Acta 41, 1777–1790.CrossRefGoogle Scholar
MultiSpec (2019). Image analysis software for hyperspectral image data. Available at https://engineering.purdue.edu/~biehl/MultiSpec/ (accessed October 5, 2019).Google Scholar
Nadeau, PA, Webster, JD, Mandeville, CW, Goldoff, BA, Shimizu, N & Monteleone, B (2015). A glimpse into Augustine volcano's Pleistocene past: Insight from the petrology of a massive rhyolite deposit. J Volcanol Geotherm Res 304, 304–323.CrossRefGoogle Scholar
Newbury, DE (2006). The new X-ray mapping: X-ray spectrum imaging above 100 kHz output count rate with the silicon drift detector. Microsc Microanal 12, 26–35.CrossRefGoogle ScholarPubMed
Newbury, DE & Ritchie, NWM (2015). Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS). J Mater Sci 50, 493–518.CrossRefGoogle Scholar
Nielsen, CH & Sigurdsson, H (1981). Quantitative methods for electron microprobe analysis of sodium in natural and synthetic glasses. Am Mineral 66, 547–552.Google Scholar
Nissinboim, A, Ebel, DS, Harlow, GE, Boesenber, JS, Sherman, KM, Lewis, ER, Brusentsova, TN, Peale, RE, Lisse, CM & Hibbitts, CA (2010). The American Museum of Natural History mineral library for spectroscopic standards. In 41st LPSC, abstract #2518. Lunar and Planetary Institute.Google Scholar
Paque, JM & Cuzzi, JN (1997). Physical characteristics of chondrules and rims, and aerodynamic sorting in the solar nebula. In 28th LPSC, abstract #1189. Lunar and Planetary Institute.Google Scholar
Pouchou, JL & Pichoir, F (1985). “PAP” φ(ρZ) procedure for improved quantitative microanalysis. In Microbeam Analysis, Armstrong, JT (Ed.), pp. 104–106. San Francisco, CA, USA: San Francisco Press.Google Scholar
Pret, D, Sammartino, S, Beaufort, D, Meunier, A, Fialin, M & Michot, LJ (2010). A new method for quantitative petrography based on image processing of chemical element maps: Part I. Mineral mapping applied to compacted bentonites. Am Mineral 95, 1379–1388.CrossRefGoogle Scholar
Rubin, AE (1998). Correlated petrologic and geochemical characteristics of CO3 chondrites. Meteorit Planet Sci 33, 385–391.CrossRefGoogle Scholar
Rubin, AE, James, JA, Keck, BD & Weeks, K (1985). The Colony meteorite and variations in CO3 chondrite properties. Meteoritics 20, 175–196.CrossRefGoogle Scholar
Russell, SS, Huss, GR, Fahey, AJ, Greenwood, AJ, Hutchison, R & Wasserburg, GJ (1998). An isotopic and petrologic study of calcium-aluminum-rich inclusions from CO3 meteorites. Geochim Cosmochim Acta 62, 689–714.CrossRefGoogle Scholar
Schindelin, J, Arganda-Carreras, I, Frise, E, Kaynig, V, Longair, M, Pietzsch, T, Preibisch, S, Rueden, C, Saalfeld, S, Schmid, B, Tinevez, J-Y, White, DJ, Hartenstein, V, Eliceiri, K, Tomancak, P & Cardona, A (2012). Fiji: An open-source platform for biological-image analysis. Nat Methods 9, 676–682.CrossRefGoogle ScholarPubMed
Scott, ERD & Jones, RH (1990). Disentangling nebular and asteroidal features of CO3 carbonaceous chondrite meteorites. Geochim Cosmochim Acta 54, 2485–2502.CrossRefGoogle Scholar
Smith, JV & Stenstrom, RC (1965). Chemical analysis of olivines by the electron microprobe. Mineral Mag 34, 436–459.Google Scholar
Sparks, J (2013). LasyBoy Version 3.77. An Excel Program for Processing ICP-MS Data. Boston University.Google Scholar
TerrSet (2019). TerrSet 18.3 Software System. Worcester, MA: Clark University. Available at https://clarklabs.org/ (accessed October 5, 2019).Google Scholar
Valencia, SN, Carpenter, PK & Joliff, BL (2018). Quantitative x-ray compositional mapping by electron probe microanalysis of complex lunar samples. Geol Soc Am Abstr Prog 50(6). DOI: 10.1130/abs/2018AM-324567.Google Scholar
Wasson, JT & Rubin, AE (2009). Composition of matrix in the CR chondrite LAP 02342. Geochim Cosmochim Acta 73, 1436–1460.CrossRefGoogle Scholar
Weisberg, MK, McCoy, TJ & Krot, AN (2006). Systematics and evaluation of meteorite classification. In Meteorites and the Early Solar System II, Lauretta, DS & McSween, HY Jr. (Eds.), pp. 19–52. Tucson, AZ, USA: University of Arizona Press.Google Scholar
Yasumoto, A, Yoshida, K, Kuwatani, T, Nakamura, D, Svojtka, M & Hirajima, T (2018). A rapid and precise quantitative electron probe chemical mapping technique and its application to an ultrahigh-pressure eclogite from the Moldanubian Zone of the Bohemian Massif (Nove Dvory, Czech Republic). Am Mineral 103, 1690–1698.CrossRefGoogle Scholar
Supplementary material: PDF

Crapster-Pregont and Ebel supplementary material

Crapster-Pregont and Ebel supplementary material 1

Download Crapster-Pregont and Ebel supplementary material(PDF)
PDF 93.3 KB
Supplementary material: PDF

Crapster-Pregont and Ebel supplementary material

Crapster-Pregont and Ebel supplementary material 2

Download Crapster-Pregont and Ebel supplementary material(PDF)
PDF 195.9 KB
Supplementary material: PDF

Crapster-Pregont and Ebel supplementary material

Crapster-Pregont and Ebel supplementary material 3

Download Crapster-Pregont and Ebel supplementary material(PDF)
PDF 91.8 KB