Abstract

Remote sensing data reveal the presence of several igneous-rock forming silicates on the surfaces of various Solar System bodies. Mafic (Mg–Fe silicates) materials were clearly recognized in the past on Mars, Moon, Vesta, and recently the weak absorption of plagioclase has been detected on the lunar highland. The advance in the detection of these important mineral phases encourages the improvement in our capability to quantify the contribution of single end-members in mixed materials.Recently, Serventi et al. (Serventi, G., Carli, C., Sgavetti, M., Ciarniello, M., Capaccioni, F., Pedrazzi, G., 2013. Icarus 226 (1), 282–298.) discussed the plagioclase absorption effects on more evident mafic absorptions in mixtures made of these components. In this work, we apply a radiative transfer model to retrieve the imaginary part of the refractive index of three different particulate plagioclase samples, with variable amount of iron, and three mafic particulate assemblages (pyroxene-bearing and olivine-free, olivine-poor and olivine-rich) used in Serventi et al. (Serventi, G., Carli, C., Sgavetti, M., Ciarniello, M., Capaccioni, F., Pedrazzi, G., 2013. Icarus 226 (1), 282–298.). We considered powders with narrow particle size distributions to obtain a reference value of the refractive index for each end-member, while samples with two different wide particle size ranges were considered to investigate the influence of the size distribution on the model. The wide size distributions were described as monodisperse, using an average value, and as multidisperse, weighing the relative amount of material in particle size sub-ranges. In both these cases we computed the optical constants, concluding that an improved description of the material’s size distribution results in derived optical constants closer to the reference values.The retrieved optical constants have been used to model reflectance spectra of plagioclase–mafic assemblage mixtures and modeled spectra were compared to measured ones. We find that the particle size distribution of the material plays an important role also in modeling mixtures spectra. Plagioclase abundance is modeled within an error of ±4% for the most of the mixtures if a multidisperse distribution is assumed, with a higher uncertainty only for mixtures with low amount of plagioclase.

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