The Moon in a Box: Thermal Infrared Spectroscopy of Silicate Mineral
Mixtures in a Simulated Lunar Environment
Abstract
A planetary surface’s thermal infrared (TIR) emissions provide insight
into the surface’s composition. Different minerals can be identified by
their characteristic TIR spectral signatures. Therefore one can retrieve
surface mineral composition by comparing TIR observations of a planetary
surface against a library of known mineral TIR spectra measured on
Earth. However for airless bodies such as the Moon, creating such a
spectral library poses a challenge: minerals exhibit different TIR
characteristics when measured in typical terrestrial conditions versus
in lunar surface-like environments. We work to overcome this challenge
by measuring TIR emission spectra of mineral samples in a chamber that
simulates the lunar environment. The Simulated Airless Body Emission
Laboratory (SABEL) chamber heats particulate samples under vacuum to
generate a thermal gradient akin to that found in the upper regolith
(i.e. epiregolith) of airless bodies. The presence of this thermal
gradient—modeled to be as steep as ~60K/100 μm for the
Moon—is due to airless bodies lacking the convective heat transfer
provided by an atmosphere. This thermal gradient is responsible for the
altered TIR spectral emission characteristics of the lunar surface, so
simulating it in SABEL allows us to measure TIR spectra that are
directly comparable to remotely sensed TIR observations from the Diviner
Lunar Radiometer (Diviner) instrument aboard the Lunar Reconnaissance
Orbiter (LRO). The work presented here focuses on one particular
application of SABEL: characterizing the TIR emission spectra of
silicate mineral mixtures with the endmembers plagioclase, pyroxene, and
olivine. These endmembers bound the typical mineral compositions of the
lunar surface. By understanding the TIR characteristics of these
endmembers’ mixtures, and in particular how the wavelength position of
the Christiansen feature—an emissivity maximum sensed by
Diviner—changes for different mixtures, we can better interpret TIR
data and their implications for surface composition.