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Analytical data on three Martian simulants.

Nicole Costa1,2, Alessandro Bonetto3, Patrizia Ferretti3

  • 1Dipartimento di Geoscienze, Università degli Studi di Padova, Via Gradenigo 6, 35131 Padova, (PD), Italy.

Data in Brief
|December 5, 2024
PubMed
Summary
This summary is machine-generated.

This study analyzes three Martian simulants (MGS-1, MMS-1, MMS-2), providing comprehensive chemical, mineralogical, and spectral data. This characterization aids in selecting appropriate simulants for Mars missions and interpreting remote sensing data.

Keywords:
GrainsizeHyperspectralMARSMass-spectrometerSEMSWIRVNIRXR-diffraction

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Area of Science:

  • Planetary Science
  • Geochemistry
  • Remote Sensing

Background:

  • Planetary missions and data analysis heavily rely on Martian simulants for testing and interpretation.
  • Commercial Martian simulants often lack comprehensive characterization data, hindering consistent use and comparison.

Purpose of the Study:

  • To provide a detailed dataset of chemical, mineralogical, granulometric, and spectral properties for three commercially available Martian simulants.
  • To establish a consistent analytical framework for comparing different Martian simulants.

Main Methods:

  • Grain size analysis using Laser Diffraction Particle Size Analyzer.
  • Chemical analysis via Inductively Coupled Plasma Mass Spectroscopy (ICP-MS).
  • Mineralogical analysis using X-Ray powder Diffractometry (XRD).
  • Scanning Electron Microscope with Energy Dispersive Spectroscopy (SEM-EDS) for specific particle analysis.
  • Hyperspectral imaging in the VNIR-SWIR range using Headwall Photonics cameras.

Main Results:

  • Comprehensive datasets for Mars Global (MGS-1), Mojave Mars Simulant (MMS-1), and Enhanced Mars Simulant (MMS-2) were generated.
  • Detailed chemical, mineralogical, grain size, and spectral data were collected for each simulant.
  • SEM-EDS analysis confirmed the chemical composition of MGS-1 particles.

Conclusions:

  • The generated dataset enables informed selection of Martian simulants for experiments and instrument testing.
  • This data will aid in interpreting Martian surface composition from remote sensing data.
  • The findings support the development of improved Martian simulants that better reflect regolith variability.