1. Background
Rare earth elements (REE) are necessary for the development of modern industrial technology. Now 97% of the world ’s rare earth element supply comes from the Baiyun Ebo mine in China. With China's modernization development, China's own demand for rare earth elements continues to increase. In order to ensure China's own supply of rare earth elements, the Chinese government may restrict the export of rare earth elements and require other developed countries to find other sources of rare earth elements. Rare earth elements in the form of electronic valence (3 +) are widely distributed on the surface of the earth.
The electromagnetic spectrum of some rare earth elements in the visible near infrared (VNIR; 400-1000 nm) spectral range shows obvious absorption characteristics. These rare elements include Nd, Sm, Dy, Er, etc. Nd, Sm are light rare earth elements (LREE), Dy, Er are heavy rare earth elements (HREE). Among them, Dy is particularly important because it greatly expands the temperature range and anti-demagnetization of Nd2Fe14B magnets.
2. Basic Theory
Mineral spectroscopy studies have shown that rock minerals have a series of diagnosable spectral feature information between 0.4 and 2.5 μm, the bandwidth of these features is mostly between 10 and 20 μm, and different rock minerals and mineralization alterations have different spectral characteristics . Because the width of the continuous band obtained by the high-spectral resolution remote sensing system is generally within 10 nm, such data can separate those rock minerals with diagnostic spectral characteristics with sufficient spectral resolution. Regional geological mapping and mineral exploration are one of the main application fields of hyperspectral remote sensing technology. The diagnostic spectral characteristics of various rocks and minerals displayed on the electromagnetic spectrum can help people identify different mineral compositions. The absorption characteristics of rare earth elements are caused by charge transfer (IVCT). Hyperspectral images can easily detect the absorption characteristics of rare earth elements. Therefore, it is an effective remote sensing technology method to extract the spectral information of minerals from hyperspectral remote sensing data and then directly distinguish rare earth elements according to their diagnostic spectral characteristics.
2.1 Spectral mechanism
There is a strict physical mechanism for the generation of the spectrum of any substance. For a molecule, its energy is composed of electron energy, vibration energy and rotation energy. According to the calculation of molecular vibration energy level difference, when the energy level difference is small, the spectrum in the near infrared region is generated; the energy gap between the molecular electronic levels is generally large, and the generated spectrum is located in the range of near infrared and visible light. The spectral characteristics in the 0.4-1.3 μm spectral range mainly depend on the presence of transition metal elements such as iron in the mineral lattice structure; the spectral characteristics in the 1.3-2.5 μm spectral range are carbonate ions, hydrogen in the composition of minerals Oxygen ions and possible water molecules are determined; the spectral characteristics of the mid to far infrared band in the 3 to 5 μm spectral range are determined by the vibration modes of molecular bonds such as Si-O and Al-O.
2.2 Characteristic parameters of mineral spectrum identification
The mineral spectrum mainly depends on the interaction of electrons and crystal fields in the object, and the molecular vibrations in the object. In the action of the crystal field, due to the transition of the ion energy level, the absorption characteristics will change, but the reflection spectrum is mainly caused by the difference of the minerals, which has nothing to do with the particle size. The transfer of electrons from one atom to another will also affect the spectrum. For example, the electron transfer of Fe-O will cause the absorption position of the spectrum to move in the ultraviolet direction. Therefore, the mineral absorption mechanism includes the electronic process of metal cations in the visible region and the vibration process of anionic groups in the near infrared region.
Because the transition of electrons between different energy levels absorbs or emits electromagnetic radiation of specific wavelengths, thereby forming spectral characteristics of specific wavelengths, rock mineral compositions with different lattice structures have different spectral characteristics. This is the physical premise of using hyperspectral data to find rock deposits.
Hyperspectral geological remote sensing mainly uses hyperspectral data to identify various mineral components, their abundance and mapping (spatial distribution of mineral components). Its main research content includes extracting qualitative and quantitative information of various geological minerals from many spectral parameters. Spectral absorption characteristics include parameters such as wavelength position, depth, width, slope, symmetry, area, and absolute reflectance of the absorption band.
JPL's Airborne's airborne visible infrared hyperspectral sensor (AVIRIS) collected hyperspectral data at the California Pass and the Carbonate Pass in Colorado. NASA's hyperspectral sensors collected hyperspectral data at the Baiyun Ebo rare earth mine. Based on the evaluation of these data, the preliminary results show that it is feasible to use the visible light near infrared hyperspectral sensor to obtain hyperspectral data to detect the existence of REE.
The spectral range of SOC700 series hyperspectral imaging spectrometer covers 400-1000nm, 900-1700nm, 1000-2350nm and mid-infrared wave band. It has powerful functions and is used in precision agriculture, forestry, mining, environmental science, oceanography, and rare earth element detection. Inside, all are ideal hyperspectral imaging systems.
Figure 1: SOC710 Hyperspectral imager, built-in scanning device, no need to move the gimbal
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