Beiswenger Toya N, Gallagher Neal B, Myers Tanya L, Szecsody James E, Tonkyn Russell G, Su Yin-Fong, Sweet Lucas E, Lewallen Tricia A, Johnson Timothy J
1 6865 Pacific Northwest National Laboratory , Richland, WA, USA.
2 Eigenvector Research, Inc., Manson, WA, USA.
Appl Spectrosc. 2018 Feb;72(2):209-224. doi: 10.1177/0003702817743265. Epub 2017 Dec 28.
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.
鉴定包括含铀物种在内的矿物，通常是一个劳动密集型过程，需使用X射线衍射（XRD）、荧光或其他固相或湿化学技术。虽然手持式XRD和荧光仪器有助于现场应用，但手持式红外（IR）反射光谱仪现在也可用于工业或现场环境，通过分析固体的反射光谱可实现快速、无损鉴定，提供其他技术无法获得的信息。在本文中，我们报告了使用实验室方法，通过积分球测量固体的红外半球反射率，并将其应用于鉴定矿物混合物（即岩石），这些混合物中铀矿物含量差异很大。然后，我们应用经典最小二乘法（CLS）和多元曲线分辨（MCR）方法，以更好地将矿物（以及两种纯铀化学品UO和UO）与许多常见的天然和人为背景材料（如硅砂、沥青、方解石、钾长石）区分开来，取得了良好的效果。矿物含量的真实情况主要通过XRD获得。无论是纯铀样品还是部分由铀组成的样品（如钒钾铀矿、钙铀云母等）或非铀矿物样品，鉴定都既简便又具特异性。特征红外波段会产生独特的（或特定类别的）波段，通常源于矿物中相似的化学基团或官能团：铀酰、磷酸盐、硅酸盐等。在某些情况下，通过产生向上的（剩余射线）波段在长波红外反射率中提供光谱区分的化学基团，可通过向下的吸收特征在中波和短波红外中提供区分，即由相同化学基团产生的较弱泛音或组合波段。
