論文

2022年11月4日

Trace-element analysis of mineral grains in Ryugu rock fragment sections by synchrotron-based confocal X-ray fluorescence

Earth, Planets and Space
  • Benjamin Bazi
  • Pieter Tack
  • Miles Lindner
  • Bart Vekemans
  • Ella De Pauw
  • Beverley Tkalcec
  • Frank E. Brenker
  • Jan Garrevoet
  • Gerald Falkenberg
  • Hikaru Yabuta
  • Hisayoshi Yurimoto
  • Tomoki Nakamura
  • Kana Amano
  • Megumi Matsumoto
  • Yuri Fujioka
  • Yuma Enokido
  • Daisuke Nakashima
  • Masayuki Uesugi
  • Hiroshi Naraoka
  • Takaaki Noguchi
  • Ryuji Okazaki
  • Kanako Sakamoto
  • Toru Yada
  • Masahiro Nishimura
  • Aiko Nakato
  • Akiko Miyazaki
  • Kasumi Yogata
  • Masanao Abe
  • Tatsuaki Okada
  • Tomohiro Usui
  • Makoto Yoshikawa
  • Takanao Saiki
  • Satoshi Tanaka
  • Fuyuto Terui
  • Satoru Nakazawa
  • Shogo Tachibana
  • Sei-ichiro Watanabe
  • Yuichi Tsuda
  • Laszlo Vincze
  • 全て表示

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記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1186/s40623-022-01726-y
出版者・発行元
Springer Science and Business Media LLC

Abstract

A fundamental parameter-based quantification scheme for confocal XRF was applied to sub-micron synchrotron radiation X-ray fluorescence (SR-XRF) data obtained at the beamline P06 of the Deutsches Elektronen-Synchrotron (DESY, Hamburg, Germany) from two sections C0033-01 and C0033-04 that were wet cut from rock fragment C0033 collected from Cb-type asteroid (162173) Ryugu by JAXA’s Hayabusa2 mission. Trace-element quantifications show that C0033 bulk matrix is CI-like, whereas individual mineral grains (i.e., magnetite, pyrrhotite, dolomite, apatite and breunnerite) show, depending on the respective phase, minor to strong deviations. The non-destructive nature of SR-XRF coupled with a new PyMca (a Python toolkit for XRF data analysis)-based quantification approach, performed in parallel with the synchrotron experiments, proves to be an attractive tool for the initial analysis of samples from return missions, such as Hayabusa2 and OSIRIS-REx, the latter returning material from a B-type asteroid (101955) Bennu in 2023.

Graphical Abstract

リンク情報
DOI
https://doi.org/10.1186/s40623-022-01726-y
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000878676400001&DestApp=WOS_CPL
URL
https://link.springer.com/content/pdf/10.1186/s40623-022-01726-y.pdf
URL
https://link.springer.com/article/10.1186/s40623-022-01726-y/fulltext.html
ID情報
  • DOI : 10.1186/s40623-022-01726-y
  • eISSN : 1880-5981
  • Web of Science ID : WOS:000878676400001

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