Laboratory Spectroscopy in Herschel/PACS Range of Astrophysically Important Minerals

Mineralogical characterization and far-infrared spectroscopy of laboratory analogues in the wavelength range 57 - 210 micron is performed for interpreting data from the Herschel Space Observatory's Photodetector Array Camera and Spectrometer (PACS). Minerals of particular interest include silicates, metal sulfides, carbonates, and phyllosilicates. Unique and novel characteristics of this work include direct measurement of 1 - 250 micron particle sizes, use of the American Museum of Natural History (AMNH) mineral, rock, and meteorite collections for real physical analogues, detailed physical characterization of those samples, measurement of far-IR temperature dependent dust and icy dust properties, and far-IR effects of crystalline disorder. Specimens and data are curated as part of the AMNH collections. Grains are examined under a microscope to manually select those with similar appearance, morphology, and absence of inclusions. Where applicable, crushing is used to separate sample from inclusions, magnetic impurities are removed, and calcite deposits are dissolved in HCl. X-ray scattering analysis is performed on powdered samples to verify crystal structure. Individual grains are mounted and analyzed by X-ray microprobe to verify chemical formula and spatial distribution of cations with the goal of selecting homogeneous grains. Presence of impurities is noted. The powders are further ground using a micronizing mill to 1 μm sizes, after which the grain size distribution is determined using a scanning electron microscope. Stokes precipitation is employed to isolate the smaller size fraction. Then the powders are dispersed into polyethylene pellets, their far-IR spectra collected, and mass absorption coefficients calculated and interpreted. Of the approximately 150 mineral species so far sampled, about one third have distinct spectral features in the PACS wavelength range. The presence or absence of such features can be correlated with mid-wave-IR Spitzer data to improve confidence of mineral identifications in astrophysical dust populations. NASA-JPL funded.