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What you see and what you get: combining near-infrared spectroscopy with powder diffraction

Published online by Cambridge University Press:  24 August 2017

Helen E. Maynard-Casely ,
Norman Booth ,
Leo Anderberg ,
Helen E.A. Brand  and
Daniel V. Cotton
Helen E. Maynard-Casely*
Affiliation:
Australian Nuclear Science and Technology Organisation, Kirrawee DC, 2232, Australia
Norman Booth
Affiliation:
Australian Nuclear Science and Technology Organisation, Kirrawee DC, 2232, Australia
Leo Anderberg
Affiliation:
University of Newcastle, Callaghan, 2308, Australia
Helen E.A. Brand
Affiliation:
Australian Synchrotron, 800 Blackburn Road, Clayton 3168, Australia
Daniel V. Cotton
Affiliation:
School of Physics, UNSW Australia, Sydney 2052, Australia Australian Centre for Astrobiology, UNSW Australia, Sydney 2052, Australia
*
a)Author to whom correspondence should be addressed. Electronic mail: [email protected]
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Abstract

Knowledge of the surface composition of planetary bodies comes from a number of sources; such as landers, remote sensing and meteorites. However, the bulk mapping of the composition of planetary surfaces has been undertaken by analysis of reflected sunlight and these data—principally collected in the near-infra-red (IR) region—are notoriously broad and ambiguous. Hence, if laboratory spectra could be tied to physical properties measurements, such as diffraction, this would substantially aid our understanding of processes occurring in these extra-terrestrial environments. This contribution presents the capability of collecting near-IR data at the same time as neutron and synchrotron X-ray diffraction in a range of conditions (low temperature, vacuum, and humidity variations) and highlights two examples where this capability could enhance our understanding of planetary surfaces.

Keywords

near-IR spectroscopyplanetaryneutronsynchrotron
Type
Technical Articles
Information
Powder Diffraction , Volume 32 , Supplement S2 , December 2017 , pp. S3 - S8
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Copyright
Copyright © International Centre for Diffraction Data 2017 

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