Other
Scientific paper
Jan 1999
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1999nvm..conf...42m&link_type=abstract
Workshop on New Views of the Moon 2: Understanding the Moon Through the Integration of Diverse Datasets, p. 42
Other
Fast Neutrons, Iron Oxides, Lunar Rocks, Lunar Soil, Thermal Neutrons, Moon, Lunar Composition, Clementine Spacecraft, Gamma Ray Spectrometers, Lunar Prospector, Models
Scientific paper
Galactic cosmic rays that impact the lunar soil produce neutrons with energies from fractions of eV's to about 100 MeV. The high-energy band from 0.6 to 8.0 MeV is referred as the "fast neutron" band, which is measured by Lunar Prospector (LP) Gamma Ray Spectrometer. Fast neutrons play an important role in neutron spectroscopy that may be summarized as follows: Fast neutrons define the total neutron input to the moderating process toward low-energy populations, so that epithermal and thermal neutron leakage currents must be normalized to the leakage of fast neutrons; they allow the determination of the burial depth of H, a measure necessary to understand characteristics of water deposits; they provide information on the surface content in heavy elements, such as Ti and Fe; and they provide a direct insight into the evaporation process. As discussed hereafter, fast neutrons may yield information on other oxides, such as Si02. missing data. Mare have numerous features, that are resolved in fast neutrons. For instance, the region extending northwest of Aristarchus (23.7 deg N, 47.4 W) is clearly separated from Montes Harbinger (27.0N, 41.0W) by a high-emission channel, and Mare Vaporum (13.3 N, 3.6 E) is separated from Sinus Aestuun (10.9N, 8.8W) by a low-emission area. We present a new technique to extract information on soil composition from the fast-neutron measurements. The analysis is applied to the central mare region. There are two steps for the development of the technique. 1. For the first step, which has been fully completed, we assume that variations of fast-neutron counting rates are due solely to TiO. and FeO. Upon this assumption, we correlate Clementine Spectral Reflectance Fe and Ti oxide maps with fast measurements. Above 16.5% of FeO, effects of Ti02 variations show in LP data. Below 6.5% of FeO, Fe cannot be discriminated; this is the region of most highland terrains. Under assumption of only two oxides to modulate the signal, we show that fast counts are 3.2x more sensitive to FeO than to Ti02. The resolution in FeO is 1.2 wt% in Ti02 it is 3.8. These results are very satisfying, specially for the distribution of FeO. However, they do not permit reproduction of Clementine Ti02 map from the residual of the fast counting rates and Clementine FeO correlation. Particularly, the discrimination between hi-Ti and low-Ti mare is not striking. 2. The second step is still under development. We assume that variations of fast-neutron counting rates are primarily due to FeO, but also to TiO2, SiO2, CaO, A12O3, MgO, and Na2O. This simulation is for a FAN soil. It will have to be refined and iteratively adapted to the soil composition. With information on TiO2 and FeO distributions from Clementine and the coefficient above, we know the global soil content in the other oxides (weighted by Gasnault et al. coefficients). On the other hand, we have from return samples estimates of correlation between oxide concentrations. We demonstrate that such processing allows estimations of SiO2 variations in the lunar regolith. Additional information contained in original.
Duston C.
Elphic R. E.
Feldman William C.
Gasnault Olivier
Lawrence D. Jr. J.
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