Lunar and Planetary Science XLVIII (2017)
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RADIATIVE TRANSFER MODELING OF LABORATORY DERIVED ILMENITE-SILICATE
MIXTURES: INSIGHTS INTO THE CLASSIFICATION OF HIGH-TITANIUM LUNAR BASALTS. K.M.
Robertson, S. Li., R.E. Milliken and C. M. Pieters. Dept. of Earth, Environmental and Planetary Sciences, Brown
University, Providence, RI, 02912. [email protected]
Introduction: The measurement of Fe-Ti oxides in
returned lunar samples has helped to refine our
understanding of the processes responsible for the
formation of mare basalts [1]. Limited sampling
however, means that we must rely on orbital remote
sensing techniques to understand the global distribution
of high-Ti lunar basalts. To date, remote sensing
analyses of Ti-bearing minerals have largely focused on
an empirical correlation between TiO2 content and
spectral slope [2,3] across the UV-VIS range that is not
uniquely linked to material properties/mineral physics
and can have relative uncertainties >50% [4].
Hapke’s radiative transfer model [5] is commonly
used for un-mixing of spectra acquired for regolith on
airless planetary surfaces, including the Moon [6]. Such
models have the potential to provide quantitative
information on Ti-bearing phases on the lunar surface,
but important issues persist in using these models for
mapping the distribution of Fe-Ti oxides. Ilmenite is
the most common Fe-Ti oxide in lunar basalts, and has
complex spectral properties that include λ dependent
opacity, highly variable albedos across the λ range, and
strong textural effects on the mixing systematics [7,8].
These effects must be better understood at the individual
level in order to constrain Fe-Ti abundance from
remotely-sensed data.
Here, we present results of a systematic analysis of
laboratory derived ilmenite-silicate mixtures to test the
ability of RTM’s to quantify the ilmenite abundance and
to evaluate textural effects on the mixing systematics.
Fig. 1. Endmember VIS-NIR spectra for the sieved size ranges as
measured on the bi-directional spectrometer at RELAB. A small
(20-32um) and coarse (75-125 um) ilmenite was mixed with the 4
size fractions of the silicates to test the Hapke model’s ability to
model ilmenite with varying particle size.
Methods:
Mineral endmembers included a
synthetic ilmenite sample from Alfa Aesar, San Carlos
olivine, Tanzanian enstatite and a gem quality
labradorite (Fig. 1). Endmembers were ground and wet
sieved to four particle sizes (20-38 μm, 38-45 μm, 63-75
μm, 75-125 μm) to be combined for spectral modeling.
The coarse ilmenite (75-125 µm) and small ilmenite
(20-38 µm) were mixed (5 wt% increments up to 25
wt%) with all 4 size fractions of each silicate to test the
effect of ilmenite particle size on the modeling results.
The ternary suite started with 60 wt% pyroxene and 40
wt% plagioclase with ilmenite being added in 5 wt%
increments up to 25 wt%. Ternary mixtures used the
same particle sizes (38-45 μm or 75-125 μm) for each
endmember within a given sample.
Samples were measured once on the Bi-directional
spectrometer in RELAB at Brown University and 8
times on an ASD FieldSpec3 spectroradiometer using
similar geometries (i=30º, e=0º, g=30º) relative to
spectralon. Samples were also measured on a Bruker
D2 Phaser XRD to validate abundance values.
The overall parameterization of the Hapke model
used in this study is the same as that of Li and Li (2011)
[9] however; it is revised slightly to account for the
complex nature of the ilmenite phase. Here we use
single scattering albedo (SSA) of mineral endmembers
as opposed to optical constants for the un-mixing. The
model inputs are, the measured reflectance data,
viewing geometry (i, e, g), end-member single
scattering albedo and densities.
Results: The reflectance spectra for the binary
mixtures of pyroxene/olivine (63-75 µm) and ilmenite
(20-32 µm) are presented in Fig. 2. There is a dramatic
decrease in the band depth of diagnostic features as well
as the overall albedo for all silicates with as little as 5%
ilmenite added. While not unexpected, these results
highlight the significant non-linear effects that opaque
phases have on the mixing systematics.
Fig. 2. ASD measurements of the pyroxene-ilmenite and olivineilmenite binary mixing suite. In the example given, a size
fraction of 75-125 µm was used for pyroxene and olivine and 2032 µm for ilmenite
Lunar and Planetary Science XLVIII (2017)
2127.pdf
Fig. 5. A) Modeled abundance
values for the 38-45μm ternary
mixtures. Pyroxene is overestimated at the expense of
plagioclase. Modeled spectra
for the 5 and 20wt% ilmenite
are shown below.
Fig. 3. A) Averaged modeled ilmenite abundance values with
standard deviation for the ilmenite (20-32 μm) - silicate (20-32
μm) binary mixtures. B) Averaged modeled ilmenite abundance
values for ilmenite and pyroxene mixtures spanning the small
(20-32 μm) and coarse (75-125 μm) size fractions.
Fig. 4. Examples of
the modeled (black)
and the measured
ASD spectra for the
ilmenite and silicate
mixtures (20-38 μm)
from Fig. 3. All
spectra are of the 20
wt%
ilmenite
mixtures.
The Hapke un-mixing results of the BDR and ASD
data for all size fractions are promising when using the
SSA as opposed to optical constants. The values
reported here are averages of 8 separate measurements
on the ASD instrument with standard deviations.
Modeled abundance values for the small ilmenite
fraction (20-32 um) and silicates (20-32 um) are
reported in Fig. 3a. The average ilmenite abundance
across all 8 measurements are within 2% of the
measured values while the standard deviations are all
within ±5%.These results show little variation between
measurements when similar particle sizes are used. The
modeled spectra for the 20 wt% ilmenite mixtures (Fig.
4) all have RMS values ~ 10-5.
Modeled ilmenite abundances for mixtures with
variable particle sizes are shown in Fig. 3b. The average
weight fraction estimates for both the small and coarse
ilmenite suites are all within 5% of actual values. A
larger error is associated with individual measurements
however, when the mixtures involve large differences in
particle size between endmembers. The variations are
not systematic and likely a result of sample preparation
effects. Images of the sample mounts suggest that
settling of the finer grained particles between the larger
grains is occurring and could be causing the observed
variation. Particle size effects are a real issue that must
be acknowledged in any results pertaining to evaluating
opaque phases on the lunar surface.
Ternary fits are shown in Fig. 5. These mixtures
involved similar grain sizes between the ilmenite and
silicates therefore there were no particle size effects to
contend with from sample preparation. The abundance
estimates for binary plagioclase-pyroxene mixture is
accurate (Fig 5); however as ilmenite is added, the
pyroxene is overestimated at the expense of plagioclase.
These results do not appear to be unique to this work as
they were also reported in [10].
Conclusions: The addition of small amounts of
ilmenite causes suppression of absorption features,
reduced albedo and a ‘red’ spectral slope a longer
wavelengths [8]. The plagioclase-ilmenite mixtures of
Fig 4 are particularly illuminating where ilmenite
absorptions dominate.
The RTM modeling of the ternary mixtures resulted
in an offset of the plagioclase and pyroxene abundance.
A similar result was observed with Apollo 17 basalt
samples (70017 and 70035) that we modeled as well as
observed in previous studies [10]. The revised RTM is
promising for ilmenite-bearing binary mixtures but,
results vary when the particle size differences increase.
In this case, the variations can be attributed to sample
preparation however; significant work is still needed to
address the effect of very fine ilmenite phases in a basalt
mixture. Specifically, how much of the red continuum
is due to the absorption properties of fine-grained
ilmenite vs scattering of generic fine-grained opaques
(micron and nano phase) in a silicate matrix?
Acknowledgments: The authors acknowledge the
support of NASA SSWP grant NNS15AR68G.
References: [1] Neal and Taylor, (1992) Geochim.
Cosmochim. Acta. 79. [2] Gillis et al., (2003) JGR.
108b. [3] Lucey et al., (2000) JGR. 105. [4] Gillis-Davis
et al., (2006) Geochim. Cosmochim. Acta.70. [5] Hapke,
B., (2005) Cambridge university press. [6] Mustard, J.F.
and C.M. Pieters, JGR 94. [7] Riner et al., (2009)
Geophys. Res. Let.36. [8] Isaacson et al., (2011)
Meteorit. Planet. Sci. 46. [9] Li and Li, (2011) JGR.
E09001. [10] Hiroi et al., (2009) LPSC abstract # 1723.