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Meteorite chemistry and comparison with Rosetta comet data

Meteorite chemistry and comparison with Rosetta comet data

Kurt Varmuza (ORCID: 0000-0002-3534-4001)
  • Grant DOI 10.55776/P26871
  • Funding program Principal Investigator Projects
  • Status ended
  • Start October 1, 2014
  • End September 30, 2019
  • Funding amount € 354,214
  • Project website

Disciplines

Chemistry (20%); Computer Sciences (30%); Mathematics (30%); Physics, Astronomy (20%)

Keywords

    Meteorites, Surface Analysis, Spectroscopy, Astronomy, Chemometrics, Statistics

Abstract Final report

The chemical composition of selected meteorites will be characterized by a combination of spectroscopic methods. Principal instrument is a time-of-flight secondary ion mass spectrometer (TOF-SIMS) which is a twin laboratory instrument of the COmetary Secondary Ion Mass Analyzer (COSIMA), one of the instruments on board of the Rosetta mission flying towards a comet, and operated by the European Space Agency (ESA). COSIMA will analyze cometary dust grains collected in the vicinity of the comet nucleus from November 2014 onwards. These cometary dust grains are expected to have chemical similarities with carbonaceous chondrite meteorite matter, an intimate mixture of minerals and organic compounds. The results from meteorite samples will allow a more efficient and safer evaluation of the expected data from cometary matter obtained on Rosetta. Additional methods for analyzing meteorite sample surfaces in this project will be a high-performance TOF- SIMS instrument, a laser desorption/ionization tandem mass spectrometer with molecular imaging capability, an infrared microscope, and a Raman microscope. Measurement areas will have diameters between 0.001 and 0.1 mm. Meteorite samples will be selected and provided by experts of the Natural History Museum Vienna which has the largest, oldest and most diverse collection of meteorites worldwide. For the evaluation of the obtained multi-instrument data new methods from multivariate statistical data analysis will be developed and implemented in the open source programming environment "R". Development of appropriate and powerful data analysis by chemometric methods is an essential part of the project. Principal aims of the project are the characterization and classification of meteorite surfaces in analogy to the expected data from the comet. In the final part of the project also Rosetta data will be available. Several research groups will be responsibly involved in this interdisciplinary project: In Austria two institutes at the Vienna University of Technology (one for the analytical chemistry, another for the statistics), a chemistry department at the University of Natural Resources and Life Sciences in Vienna, and the Natural History Museum in Vienna. Outside of Austria will collaborate at own cost: an astrophysics group at the Max Planck Institute for Solar System Research (responsible for the COSIMA instruments), the Department of Chemistry and Material of the Swedish Technical Research Institute (high-performance TOF-SIMS), and an expert for micro meteorites and comet research at the Université Paris Sud. The planned collaborations are expected to be fruitful and will open up new avenues in space research because of past successful collaborations of project partners. The project results are expected to increase our knowledge about meteorites and asteroids. They will provide substantial support for the interpretation of Rosetta data (inorganic and organic composition of cometary matter), and will yield fundamental contributions to surface analyses and the involved chemometrics.

The space mission Rosetta of ESA (European Space Agency) was launched 2 March 2004 and reached in August 2014 the neighborhood of the comet 67P/Churyumov-Gerasimenko. In November 2014 a lander module provided measurements from the surface of the comet. Instruments onboard of Rosetta explored the comet from distances typically between 20 and 500 km for more than 2 years. One of the instruments onboard was COSIMA (COmetary Secondary Ions Mass Analyzer), developed by a group of scientists, headed by Jochen Kissel, and operated by the COSIMA team (about 30 scientists) with principal investigator (P.I.) Martin Hilchenbach, Max Planck Institute for Solar System Research (MPS), Göttingen. The chemist Kurt Varmuza (TU Wien), author of this report, was Co-P.I. of COSIMA, particularly involved in the data analysis and interpretation. The support by the FWF (P26871-N20) of the project CoMeCS (Comet and Meteorite Materials - Studied by Chemometrics of Spectroscopic Data, project investigator K. Varmuza, http://www.lcm.tuwien.ac.at/comecs/) was essential for contributions of Austrian scientists to the results derived from the COSIMA data. COSIMA collected about 1400 particles (0.02 - 0.9 mm), imaged them (1 cm 1 cm, 1024 1024 pixel) and measured about 33000 mass spectra (characterizing the chemical composition, each a table of about 128000 numbers). For comparison, several meteorite samples, provided by the Natural History Museum Wien, were measured on a laboratory twin instrument of COSIMA operated at MPS. An aim of the CoMeCS project was the development and adaptation of methods and software for multivariate statistics and machine learning - supported by the statistician Peter Filzmoser (TU Wien, Research Unit Computational Statistics). Essential results obtained from the COSIMA data are a characterization of the organic material in cometary particles as a high molecular substance, in a mixture with silicates, with atomic ratios C/Si ~5, C/H ~ 1, C/N ~ 30. Machine learning approaches found signals from carbon and hydrogen containing ions in the mass spectra, and indicated different compositions of the particles collected in different periods of the mission (with different distances to the Sun). Cometary material contains more carbon than C-rich meteorites. No distinct molecules could be identified, and no compounds could be detected related to a supposed interaction of cometary material in the development of life on Earth. The CoMeCS project resulted (in collaboration with the COSIMA team) in 14 scientific papers (2 of them in Nature), 2 PhD theses (statistics, chemistry), 4 bachelor/diploma theses, and more than 40 presentations at conferences. The developed software and a database with more than 120000 mass spectra from cometary material can be used in future studies.

Research institution(s)
  • Naturhistorisches Museum Wien
  • Universität für Bodenkultur Wien
  • Technische Universität Wien
Project participants
  • Christian Köberl, Naturhistorisches Museum Wien , associated research partner
  • Notburga Gierlinger, Universität für Bodenkultur Wien , associated research partner
International project participants
  • Cecile Engrand, Université Paris Sud 11 - France
  • Harald Krüger, Max-Planck-Institut für Sonnensystemforschung - Germany
  • Martin Hilchenbach, Max-Planck-Institut für Sonnensystemforschung - Germany
  • Sandra Siljeström, SP Technical Research Institute of Sweden - Sweden

Research Output

  • 903 Citations
  • 19 Publications
Publications
  • 2016
    Title High-molecular-weight organic matter in the particles of comet 67P/Churyumov–Gerasimenko
    DOI 10.1038/nature19320
    Type Journal Article
    Author Fray N
    Journal Nature
    Pages 72-74
  • 2016
    Title Sparse and robust PLS for binary classification
    DOI 10.1002/cem.2775
    Type Journal Article
    Author Hoffmann I
    Journal Journal of Chemometrics
    Pages 153-162
  • 2015
    Title COSIMA data analysis using multivariate techniques
    DOI 10.5194/gi-4-45-2015
    Type Journal Article
    Author Silén J
    Journal Geoscientific Instrumentation, Methods and Data Systems
    Pages 45-56
    Link Publication
  • 2019
    Title H/C elemental ratio of the refractory organic matter in cometary particles of 67P/Churyumov-Gerasimenko
    DOI 10.1051/0004-6361/201834797
    Type Journal Article
    Author Isnard R
    Journal Astronomy & Astrophysics
    Link Publication
  • 2020
    Title Electrical properties of cometary dust particles derived from line shapes of TOF-SIMS spectra measured by the ROSETTA/COSIMA instrument
    DOI 10.1016/j.pss.2019.104758
    Type Journal Article
    Author Hornung K
    Journal Planetary and Space Science
    Pages 104758
    Link Publication
  • 2020
    Title Robust and sparse multigroup classification by the optimal scoring approach
    DOI 10.1007/s10618-019-00666-8
    Type Journal Article
    Author Ortner I
    Journal Data Mining and Knowledge Discovery
    Pages 723-741
  • 2020
    Title Optical properties of cometary particles collected by COSIMA: Assessing the differences between microscopic and macroscopic scales
    DOI 10.1016/j.pss.2019.104815
    Type Journal Article
    Author Langevin Y
    Journal Planetary and Space Science
    Pages 104815
    Link Publication
  • 2017
    Title Nitrogen-to-carbon atomic ratio measured by COSIMA in the particles of comet 67P/Churyumov–Gerasimenko
    DOI 10.1093/mnras/stx2002
    Type Journal Article
    Author Fray N
    Journal Monthly Notices of the Royal Astronomical Society
    Link Publication
  • 2017
    Title Similarities in element content between comet 67P/Churyumov–Gerasimenko coma dust and selected meteorite samples
    DOI 10.1093/mnras/stx1908
    Type Journal Article
    Author Stenzel O
    Journal Monthly Notices of the Royal Astronomical Society
    Link Publication
  • 2017
    Title Mechanical and electrostatic experiments with dust particles collected in the inner coma of comet 67P by COSIMA onboard Rosetta
    DOI 10.1098/rsta.2016.0255
    Type Journal Article
    Author Hilchenbach M
    Journal Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
    Pages 20160255
    Link Publication
  • 2017
    Title Carbon-rich dust in comet 67P/Churyumov-Gerasimenko measured by COSIMA/Rosetta
    DOI 10.1093/mnras/stx2640
    Type Journal Article
    Author Bardyn A
    Journal Monthly Notices of the Royal Astronomical Society
    Link Publication
  • 2017
    Title Robust and sparse estimation methods for high dimensional linear and logistic regression
    DOI 10.48550/arxiv.1703.04951
    Type Preprint
    Author Kurnaz F
  • 2015
    Title Sparse partial robust M regression
    DOI 10.1016/j.chemolab.2015.09.019
    Type Journal Article
    Author Hoffmann I
    Journal Chemometrics and Intelligent Laboratory Systems
    Pages 50-59
    Link Publication
  • 2015
    Title Comet 67P/Churyumov-Gerasimenko sheds dust coat accumulated over the past four years
    DOI 10.1038/nature14159
    Type Journal Article
    Author Schulz R
    Journal Nature
    Pages 216-218
  • 2020
    Title Composition of cometary particles collected during two periods of the Rosetta mission: multivariate evaluation of mass spectral data
    DOI 10.1002/cem.3218
    Type Journal Article
    Author Varmuza K
    Journal Journal of Chemometrics
    Link Publication
  • 2018
    Title Significance of variables for discrimination: Applied to the search of organic ions in mass spectra measured on cometary particles
    DOI 10.1002/cem.3001
    Type Journal Article
    Author Varmuza K
    Journal Journal of Chemometrics
    Link Publication
  • 2018
    Title A laser desorption ionization/matrix-assisted laser desorption ionization target system applicable for three distinct types of instruments (LinTOF/curved field RTOF, LinTOF/RTOF and QqRTOF) with different performance characteristics from three vendor
    DOI 10.1002/rcm.8075
    Type Journal Article
    Author Rados E
    Journal Rapid Communications in Mass Spectrometry
    Pages 649-656
    Link Publication
  • 2018
    Title Robust and sparse estimation methods for high-dimensional linear and logistic regression
    DOI 10.1016/j.chemolab.2017.11.017
    Type Journal Article
    Author Kurnaz F
    Journal Chemometrics and Intelligent Laboratory Systems
    Pages 211-222
    Link Publication
  • 2016
    Title COMET 67P/CHURYUMOV–GERASIMENKO: CLOSE-UP ON DUST PARTICLE FRAGMENTS
    DOI 10.3847/2041-8205/816/2/l32
    Type Journal Article
    Author Hilchenbach M
    Journal The Astrophysical Journal Letters
    Link Publication

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