We report the synthesis of silicon-doped hematite (Si:a-Fe 2 O 3 ) single crystals via chemical vapor transport, with Si incorporation on the order of 10 19 cm À3. The conductivity, Seebeck and Hall effect were measured in the basal plane between 200 and 400 K. Distinct differences in electron transport were observed above and below the magnetic transition temperature of hematite at B265 K (the Morin transition, T M ). Above 265 K, transport was found to agree with the adiabatic small-polaron model, the conductivity was characterized by an activation energy of B100 meV and the Hall effect was dominated by the weak ferromagnetism of the material. A room temperature electron drift mobility of B10 À2 cm 2 V À1 s À1was estimated. Below T M , the activation energy increased to B160 meV and a conventional Hall coefficient could be determined. In this regime, the Hall coefficient was negative and the corresponding Hall mobility was temperature-independent with a value of B10 À1 cm 2 V À1 s À1. Seebeck coefficient measurements indicated that the silicon donors were fully ionized in the temperature range studied. Finally, we observed a broad infrared absorption upon doping and tentatively assign the feature at B0.8 eV to photon-assisted small-polaron hops. These results are discussed in the context of existing hematite transport studies.

The identification of minerals, including uranium-bearing species, is often a labor-intensive process using X-ray diffraction (XRD), fluorescence, or other solid-phase or wet chemical techniques. While handheld XRD and fluorescence instruments can aid in field applications, handheld infrared (IR) reflectance spectrometers can now also be used in industrial or field environments, with rapid, nondestructive identification possible via analysis of the solid's reflectance spectrum providing information not found in other techniques. In this paper, we report the use of laboratory methods that measure the IR hemispherical reflectance of solids using an integrating sphere and have applied it to the identification of mineral mixtures (i.e., rocks), with widely varying percentages of uranium mineral content. We then apply classical least squares (CLS) and multivariate curve resolution (MCR) methods to better discriminate the minerals (along with two pure uranium chemicals UO and UO) against many common natural and anthropogenic background materials (e.g., silica sand, asphalt, calcite, K-feldspar) with good success. Ground truth as to mineral content was attained primarily by XRD. Identification is facile and specific, both for samples that are pure or are partially composed of uranium (e.g., boltwoodite, tyuyamunite, etc.) or non-uranium minerals. The characteristic IR bands generate unique (or class-specific) bands, typically arising from similar chemical moieties or functional groups in the minerals: uranyls, phosphates, silicates, etc. In some cases, the chemical groups that provide spectral discrimination in the longwave IR reflectance by generating upward-going (reststrahlen) bands can provide discrimination in the midwave and shortwave IR via downward-going absorption features, i.e., weaker overtone or combination bands arising from the same chemical moieties.

Hyperspectral imaging (HSI) continues to grow as a method for remote detection of vegetation, materials, minerals, and pure chemicals. We have used a longwave infrared (7.7 to 11.8 μm) imaging spectrometer in a static outdoor experiment to collect HSI data from 24 minerals and background materials to determine the efficacy with which HSI can remotely detect and distinguish both pure minerals and mineral mixtures at a 45-deg tilt angle relative to ground using two different backgrounds. Measurements were obtained separately for the minerals and materials mounted directly on both a bare plywood board and a board coated with aluminum foil: 19 powders (3 mixtures and 16 pure mineral powders) held in polyethylene bottle lids as well as five samples in rock form were taped directly to the boards. The primary goal of the experiment was to demonstrate that a longwave infrared library of solids and minerals collected as directional-hemispherical reflectance spectra in the laboratory could be used directly for HSI field identification along with simple algorithms for a rapid survey of the target materials. Prior to the experiment, all 24 mineral/inorganic samples were measured in the laboratory using a Fourier transform infrared spectrometer equipped with a gold-coated integrating sphere; the spectra were assimilated as part of a larger reference library of 21 pure minerals, 3 mixtures, and the polyethylene lid. Principal component analysis with mean-centering was used in an exploratory analysis of the HSI images and showed that, for the aluminum-coated board, the first principal component captured the difference between the signal that resembled a blackbody and the highly reflective aluminum background. In contrast, the second, third, and fourth principal components were able to discriminate the materials including phosphates, silicates, carbonates, and the mixtures. Results from generalized least squares target detection clearly showed that laboratory reference spectra of minerals could be utilized as targets with high fidelity for field detection.